{"success":true,"data":{"username":"arc","posts":[{"id":"web-649khs","shareId":"olAvtAXziS","platform":"web","url":"https://www.theverge.com/ai-artificial-intelligence/982774/greg-brockman-openai-role-expansion#comments","title":"It’s Greg Brockman’s OpenAI now","shareMode":"full","createdAt":1787343214974,"postedAt":"2026-08-20T15:45:55.000Z","publishedDate":"2026-08-20T15:45:55.000Z","archivedAt":"2026-08-21T20:13:31.103Z","archivedDate":"2026-08-21T20:13:31.103Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/olAvtAXziS","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/2iCX4e20CM/media/0.webp","contentType":"article","content":{"text":"OpenAI has had a hell of a year. The company spent months battling former cofounder Elon Musk in a sensational jury trial, was hit with a high-profile trade secrets lawsuit from Apple, and faced widespread scrutiny after an unreleased model hacked another AI company. As it prepares for an IPO, a steady string of executives have departed, including some of the company’s biggest names.\n\nThroughout it all, one person has quietly amassed power: Greg Brockman.\n\nBrockman is currently OpenAI’s president and cofounder. He’s helped lead OpenAI since its inception, [described as](https://www.theverge.com/ai-artificial-intelligence/929864/achiam-talked-about-the-roles-of-greg-brockman-and-ilya-sutskever-in-openais-early-days) an “engineering workhorse that pushed to build scaled-up systems that would train the AI and make it work” during the company’s early days. He’s also been ambitious from the start, famously musing in a personal journal in 2017, “Financially what will take me to $1B?” (His current stake in OpenAI is worth nearly 30 times that.) But at that point he shared power with a handful of cofounders, like chief scientist Ilya Sutskever and CEO Sam Altman.\n\nNow, though Brockman’s title hasn’t changed in years, his purview and job description have expanded significantly. He’s essentially now second-in-command at the company — and, when it comes to day-to-day operations, the big boss.\n\nHigh-level figures have been leaving OpenAI all year, but April is when the departures really picked up. That month saw the exit of Bill Peebles, former head of Sora; Kevin Weil, VP of OpenAI’s science arm; and Srinivas Narayanan, CTO of B2B applications. Two others separately departed citing medical reasons: CMO Kate Rouch and Fidji Simo, OpenAI’s CEO of AGI deployment — who went on leave in April before officially stepping down in July. The changes have continued. Earlier this month, CRO Denise Dresser, who had taken on a slew of additional responsibilities after the April shake-ups, suddenly announced her departure after just eight months. Days later, Brad Lightcap — who had been in charge of “special projects” for a few months, but before that was OpenAI’s longtime COO — announced he would leave to start “something new.”\n\nOpenAI did not immediately respond to a request for comment.\n\nHe’s essentially now second-in-command at the company — and, when it comes to day-to-day operations, the big boss\n\nSeveral of these departures — like those of Rouch, Peebles, and Weil — didn’t seem to directly affect Brockman’s position. But others expanded his authority. When Simo went on [medical leave](https://www.theverge.com/ai-artificial-intelligence/906965/openais-agi-boss-is-taking-a-leave-of-absence), Brockman took charge of all things product, including leading OpenAI’s super app efforts.\n\nThat role took on even greater significance the following month, after OpenAI [underwent](https://www.theverge.com/ai-artificial-intelligence/911118/openai-memo-cro-ai-competition-anthropic) yet [another executive reorganization](https://www.theverge.com/ai-artificial-intelligence/931544/openai-keeps-shuffling-its-executives-in-bid-to-win-ai-agent-battle) to focus on growing revenue. The change put Brockman not only in charge of product strategy, but also the company’s entire “scaling” arm, giving him authority over virtually every part of its commercial operation. Simo’s official departure, just weeks after OpenAI officially [filed to IPO](https://www.theverge.com/ai-artificial-intelligence/946335/openai-ipo-s-1-confidential), solidified that arrangement. Notably, when Dresser departed last week, a quote from Brockman — rather than CEO Sam Altman — was included in the [press release](https://openai.com/index/dali-rajic-chief-revenue-officer/) about the changes; he wrote that the company would “build out the full system to make AI broadly useful for people and businesses.”\n\nTo outside observers, the changes demonstrate OpenAI’s growing focus on chasing revenue as its IPO approaches, as well as fostering products that will differentiate it from rival Anthropic. Big shifts in executives’ scope of work tend to be a “signal towards where the company is headed strategically,” Harrison Rolfes, a senior research analyst at PitchBook, told *The Verge*. “When you have someone like Greg Brockman, for example, he’s more of a product scale and commercial sort of guy. He has a deep technical knowledge that essentially will collapse certain decision-making layers.”\n\nThe change put Brockman not only in charge of product strategy, but also the company’s entire “scaling” arm\n\nIt also may naturally translate to some departures among lower-level employees, said Rolfes: “Whatever he says goes [now] … If, let’s say, you’re below Brockman and you don’t agree with his approach but you’re a lead researcher, whatever it may be, you’re not going to work there anymore — you’re going to say, ‘I’m going to leave.’”\n\nBrockman’s authority is exceeded only by Altman — who undertook a [deliberate consolidation of power](https://www.theverge.com/2023/11/22/23967223/sam-altman-returns-ceo-open-ai) after clashing with OpenAI’s board in 2023. The two didn’t always agree in OpenAI’s early days: Brockman sometimes sided with Sutskever in difficult decisions about power dynamics, [questioning some of Altman’s ambitions](https://www.theverge.com/ai-artificial-intelligence/920775/evidence-exhibits-elon-musk-sam-altman-openai-trial?fbclid=IwY2xjawTy95hwZG9mBWV4dG4DYWVtAjExAGJyaWQRMWZ3NUtsbHR2dDdqTThEcFBzcnRjBmFwcF9pZBAyMjIwMzkxNzg4MjAwODkyAAEefCZbyiBX0-jICBEZmlPSkKbn03B_PA3mRxAu6LhFcJai0eCNuawopeuOKt4_aem_BCLQyhKiyHPgWKmG6KydQA), although he also worried about Musk “steamrolling” Altman. But he’s generally stayed close to Altman personally and professionally. When Altman was ousted from his CEO role in November 2023, Brockman immediately resigned in solidarity and began [making plans](https://x.com/gdb/status/1725736242137182594) for a new AI endeavor with him. Since then, the two have only seemed to become more aligned.\n\nAny centralization of power has practical benefits for OpenAI, allowing it to cut some of its most expensive salary payouts to help its balance sheet, says Ross Carmel, a partner at Sichenzia Ross Ference Carmel (SRFC). “When you’re going into an IPO, particularly for a company like OpenAI, who is lagging behind Anthropic in terms of revenue, you want to decrease those expenses so that this way, you’re either more profitable or closer to profitable,” he said. However, he added, “While it’s not unusual to see high-level execs leave a company just prior to a public listing, I think the fact they’re all in this small time period — that part is unusual.”\n\nAlthough experts told *The Verge* the executive departures were more intense than usual and could raise red flags, Brockman said Monday on CNBC’s “ [Squawk Box](https://www.cnbc.com/2026/08/17/openai-brockman-leadership-changes.html) ” that nothing was amiss. “There have been different eras where we have different sets of leaders in place … I’m a constant, Sam [Altman] is a constant, and that, I think that we are stronger because of that resilience and diversity.”\n\n“In order for OpenAI to be successful and really differentiate themselves from Anthropic, they need hardware and consumer products to sell to consumers, and that’s what Greg does well.”\n\nBrockman’s own constant has been translating OpenAI’s research into practical products. Back in 2020, [he celebrated](https://www.techbrew.com/stories/2020/12/14/openai-turns-five-take-look-back) OpenAI’s GPT-3 and its developer API as “the first time that [OpenAI has] had a general-purpose AI system that’s immediately commercially valuable—it’s actually useful.” Fast-forward more than five years, and these products need to end up profitable as well.\n\nSRFC’s Carmel said OpenAI likely hopes Brockman can deliver consumer revenue instead of just trying to catch up with Anthropic on enterprise. “In order for OpenAI to be successful and really differentiate themselves from Anthropic, they need hardware and consumer products to sell to consumers, and that’s what Greg does well.” Rolfes predicted that OpenAI would develop some sort of consumer product under Brockman’s oversight by the end of September, so that he could “show that he deserves that position.”\n\n“That’s the biggest worry that a lot of public investors have now,” Rolfes said. “They’re going to say, ‘Hey, does Greg have what it takes to run more of OpenAI, and is OpenAI building this institution that can operate without really depending heavily on him — on both Greg and Sam?’”\n\n**Follow topics and authors** from this story to see more like this in your personalized homepage feed and to receive email updates."},"author":{"name":"Hayden Field","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/b7047028d9df993f/avatar-2981e96cea52.png","bio":"Throughout the past few months of changes at OpenAI, one person has quietly amassed power: Greg Brockman, the company’s president and cofounder."},"metadata":{"timestamp":"2026-08-20T15:45:55.000Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/2iCX4e20CM/media/0.webp","type":"image","width":1200,"height":624}],"aiComments":[]},{"id":"web-j240q2","shareId":"DOVPzB5PWu","platform":"web","url":"http://cheatengine.org/","title":"Cheat Engine","shareMode":"full","createdAt":1787315446535,"postedAt":"2026-08-21T12:30:41.399Z","publishedDate":"2026-08-21T12:30:41.399Z","archivedAt":"2026-08-21T12:30:43.498Z","archivedDate":"2026-08-21T12:30:43.498Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/DOVPzB5PWu","contentType":"article","content":{"text":"[Go here for other operating systems](https://cheatengine.org/downloads.php)\n\nTrouble installing/running Cheat Engine? Check out the [known github issue](https://github.com/cheat-engine/cheat-engine/issues/2099) here on how to solve it, or join the [cheat engine patreon](https://www.patreon.com/cheatengine)\n\nDo you wish to mod your games, but you do not like cheating? Then try [Runtime Modifier](https://rtmod.cheatengine.org/index.php) it's not cheating if you call it modding!\n\nRead before download: You must be 18 years or older, or deemed an adult, to install Cheat Engine. Cheat engine is for private and educational purposes only. Before you attach Cheat Engine to a process, please make sure that you are not violating the EULA/TOS of the specific game/application. cheatengine.org does not condone the illegal use of Cheat Engine\n\n**May 29 2026:**Cheat Engine 7.7 Released for Windows, Mac and Linux for [Patreons](https://www.patreon.com/posts/cheat-engine-7-7-159577986)\n\nIt took a bit too long for a new public release. (Sorry about that but the wait will be worth it). But there's finally a new version of cheat engine out\nMy patreon members can get it [here](https://www.patreon.com/posts/cheat-engine-7-7-159577986)\n\n(The public windows release will come in a few days)\nThe public version is out now as well: [Link](https://cheatengine.org/download/mac/CheatEngine77.zip)\n\nFor those wondering why they get an update notification even though they got 7.7 before: There was a small patch regarding performance and a bug related to the disassembler. That should be fixed now\n\nPlease reports bugs and give suggestions to improve Cheat Engine so next version can be even greater!\n\npatches after initial release (Your CE version will tell you there is an update, even if you're on 7.7):\nupdated the windows build to fix an issue with creating a process using the processwindow fixed an issue with disassembling invalid vex instructions Fixed a lag issue with symbols Fixed memoryleak in lua command getFunctionRange Fixed 32-bit VEH debug issue and loading old tables by certain table makers Fixed structure dissect issue when autodelete is used in combination with internal types, and fixed HOOK/HOOK5 not setting the preferred allocation 26-06-2026: linux version patches\n**Changes**:\nMemrec class now has an OnActivationFailure callback globalalloc symbols do not save in tables anymore added static field address lookup for.net core and microsoft clr script tag can now be hidden Lua: Added methods for OrderedList objects. Useful for accessing the History object of disassemblerview and hexview Lua: LuaEngine windows now have their own luastate so breakpointed states won't get messed up by potential timers or other luaengine dialogs fpu debug dialog now shows when values change while stepping speedhack: mono/il2cpp with unity now should freeze the game when the game sets the speed to 0 dotnetinfo: added an enumstatic dialog find what addresses this code accesses: changed the color of blue in the darkmode dialog New table specific options added completion to lua code in auto assembler You can now dissect structures directly from dotnetinfo added modulePreference for symbol loading. When multiple modules have the same symbol, this list determines which modules has priority. (Already populated for windows and linux) break and trace: new option to break on trace stop break and trace: trace until initial function exit threadname support waitForallsymbols now shows a dialog when it takes too long custom types of the integer variant are now 8 byte in 64-bit CE added several new custom type examples/templates added a.net 8 example plugin more info now has tabs AutoAssembler: added {$ifdef} /{$endif} and {$ifndef}/{$endif} blocks mono method lookup now supports generics and parameters AutoAssembler command: Hook(address, addresstogoto, originalcode) where originalcode will be allocated and filled for you AutoAssembler command: unhook(address) AutoAssembler command: aobscanfunction(name, functionstart, aob) Mono: Better class/method lookup (generic support and parameters for methods) lua:registerSymbolLookupCallback functions now also have access to the original string as well (only use it to determine if you should return nil or not) dotnetdatacollector now takes less time to determine if something is an object in the heap or not memoryviewer has a new 'marker' type of highlights also controllable from lua. memoryviewer has a new function to highlight all lines that are used as a jump destination so it's easier to determine where to hook .net plugins: The.net 9 runtime requirements also link with aspnetcore added OnMouseWheelEvent support added AI commands ported CE to linux .net info static field now has a context menu to copy the data Added binary notation in aobscan |010**010| lua memscan has a new propery called Results which will get your all the results without the need of a foundlist helper custom type now has an 'internalOnly' property so you can use the type without notifying the user it exists You can now view tablefile contents as text added a Markdown viewer control added stacktrace lua command added a new extensions folder to CE which will load files based on a loadorder.txt moved the AI stuff to the Extensions folder added some basic unreal engine structure dissect support added binary type to structure dissect structure dissect can now load pdb structures better added a preview fields to pointers and nested types, and an option to prioritize which fields to show first added json lua library adjusted getThreadList to return a threadlist in lua if no stringlist was provided added executeCodeExThread and executeMethodThread where you can specify the thread to let the code run form property Ghost, which allows you to click through it to the window behind it. Handy for overlays ceshare now supports multiple server lists ceserver can now deal with containered paths better\n**Fixes**:\nfixed injecting dll's while pdbs are being loaded fixed a memory leak with the memory scanner luacode not working when there's multiline comments at the top of the script pdb moduleload dialog showing the wrong info memoryrecord options not loading back speedhack causing lag on some games speedhack symbols saving inside tables while they should not speedhack hotkey not saving if you don't select another entry first assembling j* +# inside a region above 7fffffff would make it generate a wrong codeblock disassembling vmovdqu shows wrong parameters settings dialog: the option to handle unexpected exceptions isn't displayed as if it's set parameter passing when launch as admin is enabled access violation issue with break and trace dialog when loading a trace freeze/crash on autoattach related to the pick process flasher lua: Fixed single run timer running more than 1 time when the timer handler shows a dialog monodatacollector: fixed an issue with multiple threads at the same time causing a disconnect fix break on unexpected breakpoints fixed enum values in il2cpp ceserver: fixed modulesize lookup fixed always hide children option fixed loadPlugin lua command adding to the permanent list convertToUtf8 is now stable when giving it incorrect parameters reassemble can now handle call [] and jmp [] 'step out' when the stack contains an unparsable string works now disassembling rorx now doesn't show a double, anymore dialogs won't show on the wrong monitor anymore the previous build missed a few lua script extensions for structure to C lookup. They are present now fixed code finder doubleclick actually hiding the memoryview window instead of showing it fixed header passing when using postURL from the internet object fixed lua engine search direction parameter fixed aob template scripts for hook fixed inputQuery fixed CE loading.net9 runtimes close enough to 9.0.0 fixed relative notations using +/-xxx structure compare reload file now cleans up old buffers fixed groupscan double and float scans when scanning out of order fixed assembling of instructions with width size specific values (broke due to the calculation ability) fixed the full injection template fixed autoassembler targetself messing up the processid breaking modulelists don't render strings longer than 1000 characters in the addresslist fixed memory access on windows on windows64 for arm64 fixed mono unboxing dbvm fixed an issue with dr6 flags not being properly set in some rare cases mono: fixed enum handling for invoke method and dialog windows.net: fixed debugging: fixed avx state being set to 0 gdb: several fixes\n\n**February 12 2025:**Cheat Engine 7.6 Released for public:\n\n**January 20 2025:**Cheat Engine 7.6 Released for Windows for [Patreons](https://www.patreon.com/posts/cheat-engine-7-6-120395349) (Mac and public will be here soon):\n\nI'm glad to announce the release of Cheat Engine 7.6. It has taken a while but I did manage to cram in a few neat fixes and improvements\nMy patreon members can get it [here](https://www.patreon.com/posts/cheat-engine-7-6-120395349)\n\n(The public release is here now as well)\n\nPlease reports bugs and give suggestions to improve Cheat Engine so next version can be even greater!\n\n**Changes**:\nNo more version numbering in the main caption. Only the about screen now has it can run without admin and asks for admin if needed (you can set to run as admin in settings as well) better error reporting (Especially if using the debugsymbol version) symbol synchronization. Symbols are shared between CE instances and remembered when reopening CE Speedhack v3 now replaces the old speedhack in windows. No more speedhack dll's to inject (more dll's to follow in the future) Speedhack also works better in unity games now (no need to turn of vsync anymore) byteTableToxxx now support an start index autoassembler command AOBSCANEX - Scan only executable memory c compiler: added __stdcall define c compiler: windows: auto assembler can deal with stdcall mangled symbols names, and c compiler can deal with unmangled symbols when stdcall is used c compiler: header files are used as table files. And tablefiles can have any name now added Java info similar to.net/mono info improved the.net info classlist performance (especially noticable in ceserver) ctrl+space on selected bytes in hexview will make the disassembler go there bunch of mono info improvements lua: treenode.Index is now writable redesigned the internals of structure dissect. Expect many new bugs there, please report! (I already know a few of them, but just waiting to get a report on them before fixing;-) ) updated the tcc library to a more recent version {$luacode} doesn't need dll injection to function anymore auto assembler DB command has been updated to allow relative changes. e.g: DB +1 +2 will increase the bytes 'db' is done at with 1 and 2 respectively you can't destroy luafile stream objects anymore. You now have to destroy the luafile itself added more language support for AA scripts added a new debugger interface: gdbserver error out scripts that try to access GUI controls from other threads. (remove threadsafegui.lua if you don't want it. But you will have a buggy CE) tablist can't be clicked while scanning is active removed the close button from the comments dialog memoryregion view columns can be sorted now C code: ANDROID define set on android targets lua: disassembler view now has a SelectionSize property lua: caretX and caretY are now exposed to synedit lua: TSynAutoComplete can be created lua: ModuleLoader can now load streams and tablefiles memory records can now set a value on freeze/unfreeze/restore to original on unfreeze memory records can hide the checkbox and choose to move the description to the furthest left you can now link a memoryview hexview with a structure window column, so it's address changes when the hexview changes patchscan will now tell you it's not going to work when you don't select any module improved dark mode visuals added option to ignore the upper byte of a pointer when doing a pointerscan (ARM memory tag security feature) groupscan now supports aobscan types as well aobscan in hexadecimal mode now supports the following operators: >XX: value has to be higher than XX, disassembler ARM64: Added some colors .net info: improved the class search .net info: static methods don't need an address anymore .net info: static methods now have a different color .net info: added a config window where colors can be changed .net info: invoking a method allows you to create objects using the dialog encodeFunction results generated in another architecture can now can used by decodeFunction structure dissect now follows the setPointerSize() directive better added lua include files cpuid recording in dbvm complete redesign of error handling in the mono data collector the monodatacollector is now multithread aware added a bunch of lua commands to make it easier to create manual process and modulelists added dmahelper.lua, which is an example script to show how to use direct memory access to get a processlist, and modulelist, and how to hook that info up to CE some lua callback now have a first parameter so they run even before ce's internal handler added ceserver command EXTCMD_DLERROR to get the error when module injection fails improved il2cpp method enum speed the threadsafe script terminator now shows a dialog asking you if you wish to kill the script or not lua: Added loadNewSymbols() so not all symbols need to be reloaded on dll injection lua: Added setSpecialScanOptionsOverride so you can control which memory regions to scan (handy for emulators)\n**Fixes**:\nLoooots of fixes in ceserver from symbollookup to debugging, pipes, basic initialization going wrong, etc... fixed symbol to address lookup picking an old version of a same named symbol instead of later (was an issue with symbollists, like ccode) fixed an error with.net/mono info giving an error when looking at a string fixed disassembling of some vector instructions fixed VEX instructions not working in 32-bit targets fixed the translation files not being up to date in the installer dissectcode high dpi fix fixed structure dissect without using a structure dissect window yet even more disassembler issues related to x86 vex and aarch64 fixed issue when ticking and unticking a checkbox in the pointerscan config fixed some font colors and types so they adjust based on default windows config fixed luacode when the target is 32-bit fixed the memview disassembler bugging out when the window height is too small dbvm: fixed an issue that would crash DBVM Lua: Debugging scripts now doesn't delete existing debug routines Lua: Fixed StructureFrm.getSelectedStructElement() assembler x86_64: fix assembling ymm,m256 parameters assembler x86_64: fixed pextrd ultimap1: fixed the ret filter debug information is no longer available when no process has been opened yet c/ccode: windows.h and some other default header files can now be included without errors c/ccode: fixed issue with chkstk symbol mono: Fixed dealing with value_type parameters and method invoking fixed issue where dbvm trace would error out on the results fixed assembling pextrd some fixes regarding roundbraces and calculations android: fixed issue when il2cpp is inside an apk bunch of other android related fixes (java and mono) fixed network modulelist to be more accurate fixed pointerscan for value scan manual map dll's now also loads the exception handling structure"},"author":{"name":"cheatengine.org"},"metadata":{"timestamp":"2026-08-21T12:30:41.399Z"},"media":[],"aiComments":[]},{"id":"web-haz6ze","shareId":"2PcN72OjYg","platform":"web","url":"https://github.com/bikram-agarwal/ObtainX","title":"bikram-agarwal/ObtainX: Get Android app updates straight from the source. And install it any way you want.","shareMode":"full","createdAt":1787315308856,"postedAt":"2026-08-21T12:28:21.902Z","publishedDate":"2026-08-21T12:28:21.902Z","archivedAt":"2026-08-21T12:28:24.412Z","archivedDate":"2026-08-21T12:28:24.412Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/2PcN72OjYg","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/TjCEPn2wj3/media/0.png","contentType":"article","content":{"text":"## ObtainX\n\n[![ObtainX — get Android app updates straight from the source](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/featureGraphic.png)](https://github.com/bikram-agarwal/ObtainX/blob/main/fastlane/metadata/android/en-US/images/featureGraphic.png)\n\nObtainX is a modern and supercharged fork of Obtainium. Re-engineered with a stunning Material 3 Expressive UI, it delivers an ultra-smooth interface packed with power-user utilities that make managing your Android apps effortless.\n\nTip\n\nCurious how ObtainX stacks up against Obtainium? Check out my side-by-side [ObtainX vs Obtainium comparison](https://github.com/bikram-agarwal/ObtainX/blob/main/docs/Difference_with_Obtainium.md) featuring full interface screenshots.\n\n[![Android API](https://camo.githubusercontent.com/c19fec22096f11b2c0f5873904ccc0a1949e5febd641cdbd63f9f05273e1b41f/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f41706925323032312b2d3530663237303f6c6f676f3d616e64726f6964266c6f676f436f6c6f723d626c61636b267374796c653d666f722d7468652d6261646765)](https://camo.githubusercontent.com/c19fec22096f11b2c0f5873904ccc0a1949e5febd641cdbd63f9f05273e1b41f/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f41706925323032312b2d3530663237303f6c6f676f3d616e64726f6964266c6f676f436f6c6f723d626c61636b267374796c653d666f722d7468652d6261646765) [![Flutter](https://camo.githubusercontent.com/1e25fd3b3ac1a14b776e7609cb9a678bf216ad151d05a2c379c9e4bb21d96ca5/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f466c75747465722d3032353639423f6c6f676f3d666c7574746572266c6f676f436f6c6f723d7768697465267374796c653d666f722d7468652d6261646765)](https://camo.githubusercontent.com/1e25fd3b3ac1a14b776e7609cb9a678bf216ad151d05a2c379c9e4bb21d96ca5/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f466c75747465722d3032353639423f6c6f676f3d666c7574746572266c6f676f436f6c6f723d7768697465267374796c653d666f722d7468652d6261646765) [![Dart](https://camo.githubusercontent.com/1f5aba4612183b0728542b7c3fd2e3cda0824c329ea95ce26d93571f2570d816/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f446172742d3031373543323f6c6f676f3d64617274266c6f676f436f6c6f723d7768697465267374796c653d666f722d7468652d6261646765)](https://camo.githubusercontent.com/1f5aba4612183b0728542b7c3fd2e3cda0824c329ea95ce26d93571f2570d816/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f446172742d3031373543323f6c6f676f3d64617274266c6f676f436f6c6f723d7768697465267374796c653d666f722d7468652d6261646765) [![Material You](https://camo.githubusercontent.com/a4952bce91d53df1f54c703b580eba9c9d5eb9ebe090f2f6ad8f5759145c1a77/68747470733a2f2f637573746f6d2d69636f6e2d6261646765732e64656d6f6c61622e636f6d2f62616467652f6d6174657269616c253230796f752d6c69676874626c75653f7374796c653d666f722d7468652d6261646765266c6f676f436f6c6f723d333333266c6f676f3d6d6174657269616c2d796f75)](https://camo.githubusercontent.com/a4952bce91d53df1f54c703b580eba9c9d5eb9ebe090f2f6ad8f5759145c1a77/68747470733a2f2f637573746f6d2d69636f6e2d6261646765732e64656d6f6c61622e636f6d2f62616467652f6d6174657269616c253230796f752d6c69676874626c75653f7374796c653d666f722d7468652d6261646765266c6f676f436f6c6f723d333333266c6f676f3d6d6174657269616c2d796f75)\n[![Lines of Code](https://camo.githubusercontent.com/1a0d0fae6ac804996b08c0774bb3e174b0cf20c74e354dd29ea291e25e9de931/68747470733a2f2f696d672e736869656c64732e696f2f656e64706f696e743f75726c3d6874747073253341253246253246746f6b65692e6b6f6a6978322e6e6574253246626164676525324667697468756225324662696b72616d2d6167617277616c2532464f627461696e582532466c696e6573267374796c653d666f722d7468652d626164676526636f6c6f723d616566663464266c6162656c436f6c6f723d346237333161266c6162656c3d4c696e65732532306f66253230636f6465)](https://camo.githubusercontent.com/1a0d0fae6ac804996b08c0774bb3e174b0cf20c74e354dd29ea291e25e9de931/68747470733a2f2f696d672e736869656c64732e696f2f656e64706f696e743f75726c3d6874747073253341253246253246746f6b65692e6b6f6a6978322e6e6574253246626164676525324667697468756225324662696b72616d2d6167617277616c2532464f627461696e582532466c696e6573267374796c653d666f722d7468652d626164676526636f6c6f723d616566663464266c6162656c436f6c6f723d346237333161266c6162656c3d4c696e65732532306f66253230636f6465) [![Forks](https://camo.githubusercontent.com/39c5e625ad110c8a69ef47e8e70ae6506a311b5f3d80e55e5901738945f170b6/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f666f726b732f62696b72616d2d6167617277616c2f4f627461696e583f636f6c6f723d444141353230267374796c653d666f722d7468652d6261646765266c6162656c436f6c6f723d363634443046)](https://github.com/bikram-agarwal/ObtainX/network/members) [![Stars](https://camo.githubusercontent.com/ea60b22f03946232fd85fc5c62f504863ae6caadf6a93d9a657d228d9f7b2c57/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f62696b72616d2d6167617277616c2f4f627461696e583f636f6c6f723d666666663030267374796c653d666f722d7468652d6261646765266c6162656c436f6c6f723d613161313136)](https://github.com/bikram-agarwal/ObtainX/stargazers) [![Downloads](https://camo.githubusercontent.com/3697c4fd10c02399f5e4a9904fd1c8f8f708df3003b508edb85631f365c304ab/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f646f776e6c6f6164732f62696b72616d2d6167617277616c2f4f627461696e582f746f74616c3f636f6c6f723d303062636434267374796c653d666f722d7468652d6261646765266c6162656c436f6c6f723d303036303634)](https://github.com/bikram-agarwal/ObtainX/releases)\n[![Release](https://camo.githubusercontent.com/469782750da23c1bc806c0a31d784ae256eca620a56d5beac19bcd56fdf0bd27/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f762f72656c656173652f62696b72616d2d6167617277616c2f4f627461696e583f636f6c6f723d61313136386526696e636c7564655f70726572656c6561736573266c6f676f3d676974687562267374796c653d666f722d7468652d6261646765266c6162656c436f6c6f723d373030663633)](https://github.com/bikram-agarwal/ObtainX/releases/latest) [![F-Droid](https://camo.githubusercontent.com/d2194b85f6a6b8e99f7af6ab2eb3bc5e54bf08aa6d07a314144106de77b2699b/68747470733a2f2f696d672e736869656c64732e696f2f662d64726f69642f762f6465762e62696b72616d2e6f627461696e783f636f6c6f723d613131363865266c6f676f3d4644524f4944267374796c653d666f722d7468652d6261646765266c6162656c436f6c6f723d373030663633)](https://f-droid.org/packages/dev.bikram.obtainx)\n[![bikram-agarwal%2FObtainX | Trendshift](https://camo.githubusercontent.com/0541e5b4625e1412cbffd012fa2a34f94c8f92f6e1f04a4826a0d0c151ad03f1/68747470733a2f2f7472656e6473686966742e696f2f6170692f62616467652f7472656e6473686966742f7265706f7369746f726965732f33383535332f6461696c793f6c616e67756167653d44617274)](https://trendshift.io/repositories/38553)\n\n**Featured by HowToMen: Best Android Apps - May 2026! 🎊** [![ObtainX: Best Android Apps - May 2026!](https://github.com/bikram-agarwal/ObtainX/raw/main/docs/assets/feature_htm.webp)](https://youtu.be/B59glf2bweo?si=8rTAqBJiW9uwtpTT&t=468)\n\n## 📦 Installation\n\n[![Get it on F-Droid](https://github.com/bikram-agarwal/ObtainX/raw/main/docs/assets/badge_fdroid.png)](https://f-droid.org/packages/dev.bikram.obtainx) [![Get it on GitHub](https://github.com/bikram-agarwal/ObtainX/raw/main/docs/assets/badge_github.png)](https://github.com/bikram-agarwal/ObtainX/releases/latest)\n\n## 🔄 Seamlessly bring your data from Obtainium\n\nIf you want to try out **ObtainX** without losing your current setup, you can bring your existing app list over in seconds:\n\n- In Obtainium: Open **Settings** and find the **Obtainium export** section, tap Export, and save the resulting.json file. (Older Obtainium versions kept this on a dedicated *Import/Export* tab.)\n- In ObtainX: Go to the `Backup` tab, select Import, and choose that exact.json file.\n- Continue where you left off: All your tracked apps and settings will be instantly populated.\n\n## ✨ Exclusive features in ObtainX\n\nThese are built from the ground up and are exclusive in ObtainX.\n\n### 🛡️ Security & Integrity\n\n- **🛡️ Build verification checks** — Runs automated cryptographic checks (F-Droid/Izzy reproducible builds, GitHub Release Attestations) on apps you add to flag tampered binaries before install. For total integrity, ObtainX's own updates are reproducible (F-Droid) and attested (GitHub). Learn more in the [Build Verification Guide](https://github.com/bikram-agarwal/ObtainX/blob/main/docs/build-verification-guide.md).\n- **🦠 VirusTotal APK scanning** — Optionally scan downloaded APKs with VirusTotal before installation. You are in control - flagged or failed scans ask you what to do during installs.\n\n### 🗂️ Smart Organization\n\n- **📥 Bulk import from fevice** — Select any apps already on your phone and ObtainX automatically finds their sources on stores you choose. No URL hunting one by one.\n- **✅ Selective backup restore** — Instead of forced to blindly import entire backup file, you get to pick n choose what you want to restore from your backup.\n- **🗂️ Dynamic folders** — Group apps into folders manually or via automatic routing rules (by name, author, category, source etc.). Each folder retains its own layouts.\n- **🕐 On-Demand Only mode** — Mark rarely updated apps so they're hidden from the main list and aren't checked during global update scans. Query them only on-demand.\n- **👆 Configurable two-way swipe gestures** — Left and right swipe actions are independently configurable per row. Choose from Update, Install, Pin, Edit, Delete, Open, App Info, or None.\n- **↩️ Undo after delete** — Revert accidental app removals instantly via a 5-second toast notification.\n- **🖼️ Custom app icons** — Not happy with an app's icon or a blank placeholder? Tap the icon on any app's detail page to set your own — pick from your gallery or grab one from the web.\n- **🔍 Verified \"also available on\" store links** — Each app detail page shows a list of other stores (beside the one you are tracking) where the app is available. Only confirmed-present stores are shown.\n\n### 🚀 Advanced Update Controls\n\n- **🧩 Advanced filter / RegEx assist** — A built-in helper walks you through building regex filters on any field that supports them. No regex knowledge required. Full details in the [Additional options guide](https://github.com/bikram-agarwal/ObtainX/blob/main/docs/additional-options-guide.md).\n- **⏭️ Skip version** — Skip a specific release you don't want without marking the app as \"updated.\" The next release will still show up normally.\n- **💾 Save assets** — Option to automatically save update assets (e.g. APKs) to your chosen folder, during update process itself.\n\n### 🎨 Interface & Experience\n\n- **🌈 Per-app color theming** — Each app's detail page derives its color scheme from the app's own icon. Deep, accurate, and dark-mode safe. Toggle *Match app page to icon colors* in Settings.\n- **🪄 Hero icon transition** — Tapping an app row animates its icon smoothly into the detail page. Swipe back and it returns the same way.\n- **🎫 Rich, customizable app rows** — See app type, tracking source, and category tags at a glance. Choose between full text badges or minimal stacked color strips to keep your list clean and uncluttered.\n- **✏️ Inline edit on detail page** — Edit any app's metadata directly from its detail page. An unsaved-changes guard prevents accidental data loss.\n- **⚙️ View options on Apps tab** — Grouping, sort order, and other organization controls live on the Apps tab itself (instead of separate settings page) so you can tune the list and see the result immediately.\n\n## 🧭 Pioneered by ObtainX — now in Obtainium too\n\nThese features were also built from ground up and first released in ObtainX; and are now available in Obtainium too.\n\n- **📦 Third-Party Installer Support** — Hand off updates to third-party installers like InstallerX or App Manager to review APK metadata (trackers, permissions, target SDK etc.) before installing (data hidden by stock installers). Essential for devices running under Google *Advanced Protection*.\n- **⚖️ Know the update size beforehand** — See the exact download size for every update - across supported stores - before you even hit the update button.\n- **🛑 Stop download** — You can stop any ongoing download from the app, the notification, or the update queue.\n- **🏷️ Category customization** — Pick an exact color (hex or hue slider) and rename a category so every app carrying it updates automatically. Feature still exclusive to ObtainX: automatic black/white label text for readability at any color, and bulk edits that **merge** (add/remove) instead of overwriting each app's existing categories. **📐 Adaptive tablet, foldable & landscape layout** — On large screens the app list sits **side-by-side with the app's detail page**, so tapping or editing a row opens it in place rather than pushing a full screen. Obtainium adopted this two-pane app list later — but that one screen is as far as its tablet support goes. - Feature still exclusive to ObtainX: a genuinely complete tablet UI. A **navigation rail pinned on the left** lets you jump between tabs from anywhere, and the **Settings, add-app and bulk-import** screens all reshape into proper two-panel big-screen layouts too. In Obtainium, every screen except the apps list currently retain their single-pane phone layout. **💫 Material 3 Expressive throughout** — Full M3 Expressive treatment across every screen: cards, fluid animations, expressive sliders, FAB and controls that feel like one product. **🔎 Live search bar** — An on-page search bar with the list filtering live as you type (Obtainium originally offered only the filter sheet). - Feature still exclusive to ObtainX: Obtainium's search bar scrolls away with the apps list, so after scrolling down you must scroll to the top to reach it. ObtainX keeps a small search button pinned at the top (without wasting space), so you can jump into search from anywhere. **🗃️ Settings and form options in cards** — Settings are visibly grouped into labeled cards instead of one long wall of options. - Feature still exclusive to ObtainX: each section card is **collapsible** - independently or collapse-all. And the per-app **Additional options** screen is sorted into categorized section cards, where Obtainium still shows one long, undifferentiated list.\n\n## 🔧 Enhanced Features\n\nOptimizations made to legacy Obtainium features.\n\n- **🏪 APKMirror updates** — In Obtainium, APKMirror apps are track-only, so the update button has nowhere to take you — you can only mark a version as installed. ObtainX keeps tracking accurate but makes the update action functional, opening the specific release page for the new version. (Bulk Import is also supported.)\n- **🧠 Smarter version status** — ObtainX handles harmless version label differences more intelligently, so you're only notified when there's genuinely something new. Six distinct states instead of a binary \"update / up to date\" pair: *up to date*, *update available*, *device is ahead*, *same version shown differently*, *genuinely unclear* and *Not installed*.\n- **🎯 Add App — three paths, one screen** — URL, Search, and From Device are all on one screen under a segmented control. Search results load inline alongside store chips — no floating sheets, no separate screens. New searches can be started without needing to go back-n-forth.\n- **🔭 Track-only source improvements** — Shows installed version from the device when the package ID is known. The Update button opens the concrete release page, not just the app listing. In Obtainium, if the wrong package ID is fetched (or none at all), the app shows as \"not installed\" forever and update notifications never work right — with no way to fix it. ObtainX surfaces this clearly and lets you **edit the package ID directly from the app page**, instantly restoring correct install detection and update tracking.\n- **🔖 Powerful, live filtering** — ObtainX rebuilds Obtainium's basic filter into a powerful tool. Filters like up-to-date, installed and track-only become **three-state** (include / exclude / off) instead of simple on/off toggles, and categories can be **included or excluded** and matched by **Any or All** — where Obtainium only lets you *include* categories, matched as \"any.\" The apps list **updates live** as you change options, with no apply step required. Active filters also appear as dismissible **chips** at the top: tap one to clear just that filter.\n- **🎛️ Total theme customization** — You control the theme (system, light, dark, AMOLED), color (Material You, presets or any HEX), palette, color shading intensity, gradient, progressive blur, roundness of UI corners, UI scale, and more. It's not just an afterthought - it's a full blown theme engine. Make it yours.\n- **🗄️ Richer app list grouping** — Group by source (Obtainium adopted in July 2026), app type (user/system/privileged) etc. A separate level of intelligent grouping for \"Updates\", \"non-installed\" and \"track-only\" apps.\n\n---\n\n## 🖼️ Screenshots\n\n| ![All Apps Page](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/phoneScreenshots/01_apps.jpg) | ![View Options: Sorting & grouping](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/phoneScreenshots/02_view_opts.jpg) | ![Live Filters](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/phoneScreenshots/03_filters.jpg) |\n| --- | --- | --- |\n| ![Individual App Page](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/phoneScreenshots/04_app.jpg) | ![Editing App Details](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/phoneScreenshots/05_edit.jpg) | ![Additional Options with RegEx Helper](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/phoneScreenshots/06_options.jpg) |\n| ![Modern Settings Page, custom category colors](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/phoneScreenshots/07_settings.jpg) | ![Choose your own installer](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/phoneScreenshots/08_installer_choice.jpg) | ![Bulk Import from Device](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/phoneScreenshots/09_bulk_add.jpg) |\n\n| ![All Apps Page](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/phoneScreenshots/tablet_01_apps.jpg) | ![View Options: Sorting & grouping](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/phoneScreenshots/tablet_02_view_opts.jpg) |\n| --- | --- |\n| ![Bulk Import from Device](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/phoneScreenshots/tablet_03_add.jpg) | ![Modern Settings Page, custom category colors](https://github.com/bikram-agarwal/ObtainX/raw/main/fastlane/metadata/android/en-US/images/phoneScreenshots/tablet_04_settings.jpg) |\n\n## 🎥 Screenrecords\n\n| Obtainx.Apps.List.mp4 | Obtainx.Filter.Folder.mp4 | Obtainx.Swipe.Bulk.mp4 |\n| --- | --- | --- |\n\n## Original Obtainium\n\nObtainX is a fork of Obtainium, licensed under [GPL-v3](https://github.com/bikram-agarwal/ObtainX/blob/main/LICENSE.txt).\n\nRead the original Obtainium [README here](https://github.com/ImranR98/Obtainium/blob/main/README.md).\n\n## ➕ More Apps\n\n| ![Remember feature graphic](https://github.com/bikram-agarwal/ObtainX/raw/main/docs/assets/feature_remember.jpg) **Remember** Notes, tasks, and reminders that keep coming back until they are done. | ![FilePipe feature graphic](https://github.com/bikram-agarwal/ObtainX/raw/main/docs/assets/feature_filepipe.jpg) **FilePipe** Your files, your rules. Automatically sort and move media with smart rules. |\n| --- | --- |\n\n---\n\nMade with ❤️ by Bikram Agarwal"},"author":{"name":"bikram-agarwal","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/690298607f875588/avatar-6a9577cd4f7f.svg","bio":"Get Android app updates straight from the source. And install it any way you want. - bikram-agarwal/ObtainX"},"metadata":{"timestamp":"2026-08-21T12:28:21.902Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/TjCEPn2wj3/media/0.png","type":"image","width":1024,"height":500}],"aiComments":[]},{"id":"web-k31gm3","shareId":"gC7g46E92s","platform":"web","url":"https://github.com/cheat-engine/cheat-engine","title":"cheat-engine/cheat-engine: Cheat Engine. A development environment focused on modding","shareMode":"full","createdAt":1787315304712,"postedAt":"2026-08-21T12:28:17.059Z","publishedDate":"2026-08-21T12:28:17.059Z","archivedAt":"2026-08-21T12:28:19.402Z","archivedDate":"2026-08-21T12:28:19.402Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/gC7g46E92s","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/2d7wPw00HP/media/0.png","contentType":"article","content":{"text":"[![Image](https://github.com/cheat-engine/cheat-engine/raw/master/Cheat%20Engine/images/celogo.png)](https://github.com/cheat-engine/cheat-engine/raw/master/Cheat%20Engine/images)\n\n\n\n## Cheat Engine\n\nCheat Engine is a development environment focused on modding games and applications for personal use.\n\n\n\n## Download\n\n- **[Latest Version](https://github.com/cheat-engine/cheat-engine/releases/latest)** [Older versions](https://github.com/cheat-engine/cheat-engine/releases)\n\n\n\n## Links\n\n- [Website](https://www.cheatengine.org/)\n- [Forum](https://forum.cheatengine.org/)\n- [Forum (alternate)](https://opencheattables.com/)\n\n## Social Media\n\n- [Reddit](https://reddit.com/r/cheatengine)\n- [Twitter](https://twitter.com/_cheatengine)\n\n## Donate\n\n- [Patreon](https://www.patreon.com/cheatengine)\n- [PayPal](https://www.paypal.com/xclick/business=dark_byte%40hotmail.com&no_note=1&tax=0&lc=US)\n\n## Basic Build Instructions\n\n1. Download Lazarus 2.2.2 from [https://sourceforge.net/projects/lazarus/files/Lazarus%20Windows%2064%20bits/Lazarus%202.2.2/](https://sourceforge.net/projects/lazarus/files/Lazarus%20Windows%2064%20bits/Lazarus%202.2.2/) First install lazarus-2.2.2-fpc-3.2.2-win64.exe and then lazarus-2.2.2-fpc-3.2.2-cross-i386-win32-win64.exe\n2. Run Lazarus and click on `Project->Open Project`. Select `cheatengine.lpi` from the `Cheat Engine` folder as the project.\n3. Click on `Run->Build` or press SHIFT+F9. - you can also click on `Run->Compile many Modes` (tip: select first three compile modes) - If you want to run or debug from the IDE on Windows you will need to run Lazarus as administrator. Do not forget to compile secondary projects you'd like to use:\n\n\n\n```\nspeedhack.lpr: Compile both 32- and 64-bit DLL's for speedhack capability\nluaclient.lpr: Compile both 32- and 64-bit DLL's for {$luacode} capability\nDirectXMess.sln: Compile for 32-bit and 64-bit for D3D overlay and snapshot capabilities\nDotNetcompiler.sln: for the cscompile lua command\nmonodatacollector.sln: Compile both 32-bit and 64-bit dll's to get Mono features to inspect the .NET environment of the process\ndotnetdatacollector.sln: Compile both 32- and 64-bit EXE's to get .NET symbols\ndotnetinvasivedatacollector.sln: Compile this managed .DLL to add support for runtime JIT support\ncejvmti.sln: Compile both 32- and 64-bit DLL's for Java inspection support\ntcclib.sln: Compile 32-32, 64-32 and 64-64 to add {$C} and {$CCODE} support in scripts\nvehdebug.lpr: Compile 32- and 64-bit DLL's to add support for the VEH debugger interface\ndbkkernel.sln: for kernelmode functions (settings->extra) You will need to build the no-sig version and either boot with unsigned driver support, or sign the driver yourself\n```\n\n*.SLN files require visual studio (Usually 2017)"},"author":{"name":"cheat-engine","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/0cc2e6c8aba4b37d/avatar-6a9577cd4f7f.svg","bio":"Cheat Engine. A development environment focused on modding - cheat-engine/cheat-engine"},"metadata":{"timestamp":"2026-08-21T12:28:17.059Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/2d7wPw00HP/media/0.png","type":"image","width":1200,"height":600}],"aiComments":[]},{"id":"web-z76u6b","shareId":"zj4uzFzqDd","platform":"web","url":"https://www.bravoready.com/","title":"Bravo Ready: Ecosystem","shareMode":"full","createdAt":1787315117439,"postedAt":"2026-08-21T12:25:11.447Z","publishedDate":"2026-08-21T12:25:11.447Z","archivedAt":"2026-08-21T12:25:13.717Z","archivedDate":"2026-08-21T12:25:13.717Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/zj4uzFzqDd","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/zP3EutSd3u/media/0.png","contentType":"article","content":{"text":"$3M\n\nRevenue to Date\n\n$10M\n\nRevenue to Date\n\nTOP 20\n\nCasino on App Store\n\n160,000+\n\nPre-Registered Users\n\n100,000+\n\nApp Downloads\n\nPrelaunch\n\nBeta Product\n\n## Press Releases\n\n![New to the Street: Broadcasting Saturday June 13th 6:30PM EST Across Bloomberg Television](https://www.bravoready.com/static/website/img/ecosystem/pr-1.png)\n\n### [New to the Street: Broadcasting Saturday June 13th 6:30PM EST Across Bloomberg Television](https://www.morningstar.com/news/accesswire/1176662msn/new-to-the-street-broadcasting-saturday-june-13th-630pm-est-across-bloomberg-television-in-the-us-latin-america-and-mena)\n\nBravo Ready featured on New to the Street, broadcasting across Bloomberg Television in the US, Latin America and MENA.\n\n![Montreal-based BRAVO READY Acquires Honeyland to Expand Real-Money Gaming Ecosystem](https://www.bravoready.com/static/website/img/ecosystem/pr-2.png)\n\n### [Montreal-based BRAVO READY Acquires Honeyland to Expand Real-Money Gaming Ecosystem](https://www.businesswire.com/news/home/20250710089376/en/Montreal-based-BRAVO-READY-Acquires-Honeyland-to-Expand-Real-Money-Gaming-Ecosystem)\n\nBravo Ready acquires Honeyland, the beloved Solana mobile strategy game with over 100K downloads, adding it to its growing portfolio of real-money gaming titles.\n\n![Solana Meme Coin Bonk Launches](https://www.bravoready.com/static/website/img/ecosystem/pr-3.png)\n\n### [Solana Meme Coin Bonk Launches 'Kill-to-Earn' Shooter Game](https://decrypt.co/323296/solana-meme-coin-bonk-kill-to-earn-shooter-game)\n\nBONK, Solana's flagship meme coin, launches a kill-to-earn shooter built on Bravo Ready's BR1 infrastructure, bringing meme culture into real-money gaming.\n\n![BRAVO READY Announces Strategic Investment From Magic Eden](https://www.bravoready.com/static/website/img/ecosystem/pr-4.png)\n\n### [BRAVO READY Announces Strategic Investment From Magic Eden](https://www.businesswire.com/news/home/20230330005710/en/BRAVO-READY-Announces-Strategic-Investment-From-Magic-Eden)\n\nBravo Ready secures a strategic investment from Magic Eden, the leading NFT marketplace on Solana, to accelerate the growth of its real-money gaming ecosystem.\n\n![BRAVO READY Announces Strategic Investment From Aptos](https://www.bravoready.com/static/website/img/ecosystem/pr-5.png)\n\n### [BRAVO READY Announces Strategic Investment From Aptos](https://www.businesswire.com/news/home/20230316005725/en/BRAVO-READY-Announces-Strategic-Investment-From-Aptos)\n\nBravo Ready receives a strategic investment from the Aptos Foundation, expanding its blockchain gaming infrastructure across multiple ecosystems.\n\n![BRAVO READY Announces Strategic Investment from Sino Global Capital](https://www.bravoready.com/static/website/img/ecosystem/pr-6.png)\n\n### [BRAVO READY Announces Strategic Investment from Sino Global Capital](https://www.businesswire.com/news/home/20220913005914/en/BRAVO-READY-Announces-Strategic-Investment-from-Sino-Global-Capital)\n\nSino Global Capital joins the Bravo Ready funding consortium, backing the studio's vision for the future of competitive real-money gaming.\n\n![Fractal Cofounder Justin Kan Joins Investor Group Backing BRAVO READY](https://www.bravoready.com/static/website/img/ecosystem/pr-7.png)\n\n### [Fractal Cofounder Justin Kan Joins Investor Group Backing BRAVO READY](https://www.businesswire.com/news/home/20220808005863/en/Fractal-Cofounder-Justin-Kan-Joins-Investor-Group-Backing-BRAVO-READY)\n\nTwitch co-founder and Fractal pioneer Justin Kan backs Bravo Ready, bringing deep expertise in gaming, streaming, and early-stage company growth.\n\n![BRAVO READY Announces Funding Agreement with 6th Man Ventures on BR1: Infinite Royale](https://www.bravoready.com/static/website/img/ecosystem/pr-8.png)\n\n### [BRAVO READY Announces Funding Agreement with 6th Man Ventures on BR1: Infinite Royale](https://www.businesswire.com/news/home/20220727005229/en/Gaming-Pioneer-BRAVO-READY-Announces-Funding-Agreement-and-Development-Partnership-with-6th-Man-Ventures-on-Revolutionary-Competitive-Shooter-BR1-Infinite-Royale)\n\nBravo Ready announces a funding agreement and development partnership with 6th Man Ventures on BR1: Infinite Royale, the world's first AAA real-money shooter.\n\n![Gaming Pioneer BRAVO READY Announces Strategic Investment by Big Brain Holdings](https://www.bravoready.com/static/website/img/ecosystem/pr-9.png)\n\n### [Gaming Pioneer BRAVO READY Announces Strategic Investment by Big Brain Holdings](https://www.businesswire.com/news/home/20220726006121/en/Gaming-Pioneer-BRAVO-READY-Announces-Strategic-Investment-by-Big-Brain-Holdings)\n\nBig Brain Holdings, one of Web3 gaming's most respected guilds and investment firms, backs Bravo Ready as it builds its real-money gaming ecosystem.\n\n![BRAVO READY Announces $3M Seed Round with Solana Ventures, 6th Man Ventures, Justin Kan, Sino Global Capital, and Shima Capital](https://www.bravoready.com/static/website/img/ecosystem/pr-10.png)\n\n### [BRAVO READY Announces $3M Seed Round with Solana Ventures, 6th Man Ventures, Justin Kan, Sino Global Capital, and Shima Capital](https://www.businesswire.com/news/home/20220711005877/en/Gaming-Pioneer-BRAVO-READY-Announces-3M-Seed-Round-and-Development-Partnerships-with-Solana-Ventures-6th-Man-Ventures-Justin-Kan-Sino-Global-Capital-and-Shima-Capital)\n\nBravo Ready closes a $3M seed round backed by Solana Ventures, 6th Man Ventures, Justin Kan, Sino Global Capital, and Shima Capital to build the future of real-money gaming.\n\n## Portfolio\n\nSpawn. Kill. Earn. Repeat.\n\nBR1: INFINITE is the world's first real-money extraction shooter. With 150,000+ pre-registered players and over $100,000 paid out, BR1 is proving that skill can pay.\n\nThe Cutest Bees On The Internet\n\nHoneyland is a family-friendly universe. Amassing over 100,000 App Store downloads and a growing collection of fun mobile games. These lovable bees have also generated 30M+ GIF views and have a cute, highly shareable social presence.\n\nThe Collectibles Arcade\n\nSlabz is a digital collecting arcade built for the next generation of collectors. With over $8M in revenue to date, Slabz brings the thrill of opening packs, chasing rare slabs, and building a valuable collection into a fast, social, game-like experience.\n\n![Slabz Pack Opening](https://www.bravoready.com/static/website/img/games/slabz-desktop-2.png)\n\n![Slabz Card Display](https://www.bravoready.com/static/website/img/games/slabz-desktop-1.png)\n\n![Slabz Mobile](https://www.bravoready.com/static/website/img/games/slabz-mobile.png)\n\n![Mini Arena](https://www.bravoready.com/static/website/img/games/miniarena/img-1.png)\n\n![Mini Arena Map](https://www.bravoready.com/static/website/img/games/miniarena/img-2.png)\n\n![Mini Arena Gameplay](https://www.bravoready.com/static/website/img/games/miniarena/img-3.png)\n\n![Mini Arena Match Recap](https://www.bravoready.com/static/website/img/games/miniarena/img-4.png)\n\nFast-Paced, Real Money Arena Combat\n\nMini Arena is a fast-paced arena combat game built for quick matches, simple controls, and instant replayability and never-ending fun.\n\nAvailable on both browser and mobile.\n\nRisk-to-Earn Web3 MMO\n\nCambria is one of Web3 gaming's most popular upcoming titles, surpassing $1M in season sales.\n\nClosed at a $6M valuation with over $10M in total revenue generated.\n\n![Cambria Combat](https://www.bravoready.com/static/website/img/games/cambria/img-1.png)\n\n![Cambria Marketplace](https://www.bravoready.com/static/website/img/games/cambria/img-2.png)\n\n![Cambria Victory](https://www.bravoready.com/static/website/img/games/cambria/img-3.png)\n\n![Cambria World](https://www.bravoready.com/static/website/img/games/cambria/img-4.png)\n\n![Thrillzz Win Real Money](https://www.bravoready.com/static/website/img/games/thrillzz-1.png)\n\n![Thrillzz Games](https://www.bravoready.com/static/website/img/games/thrillzz-2.png)\n\n![Thrillzz Payouts](https://www.bravoready.com/static/website/img/games/thrillzz-3.png)\n\nReal Money Mobile Games\n\nThrillzz is a real-money mobile gaming platform where players compete in fast, accessible skill-based games for cash prizes.\n\nBuilt for mainstream mobile users, available to play on the App Store.\n\n## Our Investors\n\n![6MV](https://www.bravoready.com/static/website/img/ecosystem/investors/6mv.png)\n\n![Solana Ventures](https://www.bravoready.com/static/website/img/ecosystem/investors/solana-ventures.png)\n\n![Krafton](https://www.bravoready.com/static/website/img/ecosystem/investors/krafton.png)\n\n![Justin Kan](https://www.bravoready.com/static/website/img/ecosystem/investors/justin-kan.png)\n\n![Bitkraft](https://www.bravoready.com/static/website/img/ecosystem/investors/bitkraft.png)\n\n![Big Brain Holdings](https://www.bravoready.com/static/website/img/ecosystem/investors/big-brain.png)\n\n![Ryze Labs](https://www.bravoready.com/static/website/img/ecosystem/investors/ryze-labs.png)\n\n## Our Partners\n\n![Phantom](https://www.bravoready.com/static/website/img/ecosystem/investors/phantom.png)\n\n![Collector Crypt](https://www.bravoready.com/static/website/img/ecosystem/investors/collector-crypt.png)\n\n![Metaplex](https://www.bravoready.com/static/website/img/ecosystem/investors/metaplex.png)\n\n![Helius](https://www.bravoready.com/static/website/img/ecosystem/investors/helius.png)\n\n![Bonk](https://www.bravoready.com/static/website/img/ecosystem/investors/bonk.png)\n\n![Magic Eden](https://www.bravoready.com/static/website/img/ecosystem/investors/magic-eden.png)\n\n![Aptos](https://www.bravoready.com/static/website/img/ecosystem/investors/aptos.png)\n\n## I love the team and what they are building.\n\nJustin Kan, Co-founder of\n\n![Twitch](https://www.bravoready.com/static/website/img/ecosystem/quote/twitch.webp)"},"author":{"name":"bravoready.com","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/761809452926fceb/avatar-e0bdf4e3bc61.png","bio":"We are BRAVO READY, a gaming ecosystem aimed to help take games to market and reward players for their early participation."},"metadata":{"timestamp":"2026-08-21T12:25:11.447Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/zP3EutSd3u/media/0.png","type":"image","width":1615,"height":1346}],"aiComments":[]},{"id":"web-snuyse","shareId":"VYUGzOfHuO","platform":"web","url":"https://moodnode.ai/features","title":"MoodNode Features — Visual AI Workspace for Image & Video Generation","shareMode":"full","createdAt":1787314974255,"postedAt":"2026-08-21T12:22:42.044Z","publishedDate":"2026-08-21T12:22:42.044Z","archivedAt":"2026-08-21T12:22:43.884Z","archivedDate":"2026-08-21T12:22:43.884Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/VYUGzOfHuO","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/8pZAdMWbwl/media/0.png","contentType":"article","content":{"text":"## MoodNode Features\n\nMoodNode is a node-based AI workspace for generating images and videos. Connect 50+ AI models — Flux, Seedream, Stable Diffusion, Kling, Luma, Pika, and more — in visual pipelines. From a single prompt to a fully produced video, all in one flow. Free to start with your own API keys (BYOK).\n\n## Node-Based Workflows\n\nBuild visual pipelines by connecting nodes on a canvas. Each node does one thing — generate, edit, enhance, or export. Chain them together to create multi-step workflows from prompt to production.\n\n## Save As Template\n\nTurn any workflow into a reusable template. Save it, name it, and start new projects from it in one click. Share them with the community or keep them private.\n\n## Style DNA\n\nUpload a reference image and let AI extract its visual DNA — colors, mood, composition, lighting. Apply that style to any generation without guessing prompts.\n\n## Prompt Library\n\nSave your best prompts and reuse them across projects. Build a personal collection of proven creative directions. Organize by category and search instantly.\n\n## Vectorize\n\nFeed a raster image into the Vectorize node to get an SVG version. Perfect for converting photos into scalable graphics and turning AI art into clean vectors.\n\n## Extract Prompt\n\nDrop any image into the Extract Prompt node and reverse-engineer the prompt that could have created it. Learn from existing art and remix styles.\n\n## Bring Your Own Key\n\nConnect your own API keys for full control and zero markup. Use fal.ai, Replicate, or any supported provider directly. No middleman, pay at cost.\n\n## Themes & Colors\n\nPick from built-in themes or bring any shadcn theme for thousands of options. Dark mode, light mode, custom palettes — your workspace adapts to you.\n\n## Agentic Workflow\n\nPress ⌘K and describe what you want — the AI agent places nodes, wires connections, and sets parameters automatically. Go from idea to full workflow in seconds, across 50+ AI models.\n\n## Why MoodNode?\n\nMost AI creative tools lock you into a single model and a single workflow. MoodNode is different — it is a visual canvas where you connect any AI model as a node, chain them into multi-step pipelines, and generate images, videos, sprite sheets, and storyboards without writing code. Support for 50+ models means you are never limited to one provider. BYOK (Bring Your Own Key) mode lets you use your own API keys and pay providers directly at cost — no markup, no credit limits.\n\n## Built with Pretext\n\nThis interactive features page is powered by [@chenglou/pretext](https://github.com/chenglou/pretext) — a high-performance text layout library that measures and wraps text without DOM reflows. Each character on the canvas is individually positioned using pretext's `prepareWithSegments()` and `layoutNextLine()` APIs, enabling real-time text layout that responds to window resizing instantly. Combined with verlet physics for character movement, scroll-driven reveal animations, and meteor trail effects on titles, the result is a fully interactive ASCII canvas running at 60fps with 60,000+ characters.\n\n## How It Compares\n\nUnlike ComfyUI which requires local GPU setup and Python knowledge, MoodNode runs entirely in the browser with zero installation. Unlike Midjourney which is limited to one model in Discord, MoodNode offers 50+ models in a visual editor. Unlike Leonardo.ai which is a single-canvas tool, MoodNode lets you build multi-step node workflows. And with BYOK, you can use your own API keys — something most competitors do not offer."},"author":{"name":"MoodNode","avatar":"https://moodnode.ai/icon.svg?icon.14ywz4vhxys4j.svg","bio":"Explore MoodNode's core features: node-based workflows, 50+ AI models, templates, Style DNA, prompt library, vectorization, and more. Build visual pipelines from prompt to production."},"metadata":{"timestamp":"2026-08-21T12:22:42.044Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/8pZAdMWbwl/media/0.png","type":"image","width":1200,"height":630}],"aiComments":[]},{"id":"web-57jztl","shareId":"tlYtBW0DYH","platform":"web","url":"https://moodnode.ai/tools/prompt-library","title":"Free AI Prompt Library — 324+ Ready-to-Use Prompts with Examples","shareMode":"full","createdAt":1787314945096,"postedAt":"2026-08-21T12:22:18.703Z","publishedDate":"2026-08-21T12:22:18.703Z","archivedAt":"2026-08-21T12:22:21.053Z","archivedDate":"2026-08-21T12:22:21.053Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/tlYtBW0DYH","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/IG7oIlDaf7/media/0.png","contentType":"article","content":{"text":"

"},"author":{"name":"MoodNode","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/0fa484434ce180fa/avatar-61cf8707e510.svg","bio":"Browse 324+ curated AI image prompts with real generated examples across 10 categories. Portrait, product, cinematic, landscape, and more. Copy any prompt and generate images instantly with 50+ AI models."},"metadata":{"timestamp":"2026-08-21T12:22:18.703Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/IG7oIlDaf7/media/0.png","type":"image","width":1200,"height":630}],"aiComments":[]},{"id":"web-b7ua3q","shareId":"1xdraT85Ag","platform":"web","url":"https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2026.1736349/full?utm_source=chatgpt.com","title":"Looking at both sides of algorithmic control and employee well-being: a job demands−resources model","shareMode":"full","createdAt":1787271825679,"postedAt":"2026-01-21T00:00:00.000Z","publishedDate":"2026-01-21T00:00:00.000Z","archivedAt":"2026-08-21T00:23:40.126Z","archivedDate":"2026-08-21T00:23:40.126Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/1xdraT85Ag","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/Gm3mjkq3Fq/media/0.png","contentType":"article","content":{"text":"## ORIGINAL RESEARCH article\n\nSec. Organizational Psychology\n\nVolume 17 - 2026 | [https://doi.org/10.3389/fpsyg.2026.1736349](https://doi.org/10.3389/fpsyg.2026.1736349)\n\n## Looking at both sides of algorithmic control and employee well-being: a job demands−resources model\n\n- 1. Department of Business Administration, Guizhou University of Finance and Economics, Guiyang, China\n- 2. School of Management, Chongqing University of Technology, Chongqing, China\n\n## Abstract\n\n**Objectives:**\n\nDrawing on the job demands-resources (JD-R) theory, this study aims to analyze the impact of algorithmic control on the well-being of delivery drivers by focusing on the mediating role of job demands (work overload and time pressure) and job resources (feedback quality and role clarity).\n\n**Methods:**\n\nThis study obtained three-wave data from 435 delivery drivers and examined the hypotheses using structural equation modelling.\n\n**Results:**\n\nThe results indicated that algorithmic control reduced delivery drivers’ well-being by increasing the job demands (time pressure and work overload). In addition, algorithmic control enhanced delivery drivers’ well-being by increasing their level of job resources (feedback quality and role clarity).\n\n**Conclusion:**\n\nIntegrating job demands-resources (JD-R) theory, this study provides a more balanced view of how algorithmic control influences well-being by demonstrating the opposing mediating roles of job demands (work overload and time pressure) and job resources (feedback quality and role clarity).\n\n## 1 Introduction\n\nAccording to data from the All-China Federation of Trade Unions, the number of food delivery drivers increased from 6 million in 2020 to over 10 million in 2024. Given the growing number of food delivery drivers in the workforce, platform firms are now using algorithmic control to improve the work efficiency and service quality of their drivers. Algorithmic control refers to the management practice of using intelligent algorithms and advanced digital technology to supervise and guide food-delivery driver behaviors (Deng et al., 2025; ). As algorithmic control has reconfigured the production relationship among platforms, customers, and food delivery drivers, this has created a research hotspot focusing on how algorithmic control affects driver work outcomes (; ). Researchers have begun to explore the impact of algorithmic control on employees’ well-being because employees are also stakeholders in the organizations for which they work, with their well-being playing a crucial role with regard to both their own health and organizational performance (; ).\n\nThe mainstream view of the extant literature is that algorithmic control can reduce employee well-being (; Kinowska and Sienkiewicz, 2023). Nevertheless, a contrasting view suggests that algorithmic control is beneficial to the employee work well-being by enhancing their fairness perception (Deng et al., 2025). Given these contradictory findings, the relationship between algorithmic control and well-being appears to be more complex than one might expect. Therefore, this research aims to examine the double-edged sword effects of algorithmic control on delivery drivers’ well-being and seek an effective way to harness the positive impact of algorithmic control and address its negative effects.\n\nTo address this issue, following Caesens et al. (2017) and, this study considered job satisfaction and emotional exhaustion as important dimensions of well-being, and examined a dual pathway model to explore the double-edged sword effects of algorithmic control on employee well-being based on the job demands-resources (JD-R) theory. JD-R theory suggests that management practices can indirectly affect employee well-being through perceived job resources and demands (Bakker et al., 2023). As algorithmic control is an important managerial practice (), JD-R theory can be used to explain the effects of algorithmic control on the well-being of food delivery drivers experiencing increased job demands and resources. Specifically, we focused on how algorithmic control influences the job resources relating to feedback quality and role clarity, which we considered as mediators of the positive relationship between algorithmic control and food-delivery drivers’ well-being. We also focused on how algorithmic control impacts the job demands of time pressure and work overload, which we considered as intermediaries of the negative relationship between algorithmic control and food-delivery drivers’ well-being.\n\nThis study contributes to the existing literature in this field in several ways. First, pervious researches have either focused on the negative effect of algorithmic control on employee work well-being (; Kinowska and Sienkiewicz, 2023) or explored its positive effect (Deng et al., 2025), with few studies simultaneously examining its positive and negative impacts. By explicitly considering job demands (time pressure and work overload) and job resources (feedback quality and role clarity) as distant mechanisms linking algorithmic control to well-being, our work explains why algorithmic control can be both positively and negatively linked to employee well-being. By doing so, it provides a comprehensive understanding of the influences of algorithmic control that go beyond the traditional view that algorithmic control is always detrimental. Second, the present study is an early application of the JD-R theory to algorithmic empirical research, which not only validates the propositions of the JD-R theory, but also enriches the literature on the antecedents of job demands and resources. Third, testing algorithmic control, extraversion, and neuroticism simultaneously in our model enables us to distinguish the unique predictive validity of algorithmic control.\n\n## 2 Theoretical and hypotheses\n\n### 2.1 Algorithmic control and JD-R theory\n\nExisting studies have examined the effects of algorithmic control across diverse samples and work contexts. For instance, within the platform economy, research indicates that algorithmic control significantly influences food delivery drivers’ proactive customer service performance and customer-oriented service behaviors (; ). In traditional workplaces implementing algorithmic management, studies have found that algorithmic control can simultaneously promote employees’ knowledge hiding and stimulate their innovative behaviors (Liu et al., 2025a,b).\n\nThe JD-R theory states that management practices can simultaneously increase employees’ job resources and demands (Bakker et al., 2023). Job resources refer to “the psychological, physical, and social aspects of the job that are conducive to achieving work goals” (Demerouti et al., 2001, p. 501), such as job variety, role clarity, and feedback quality. Job demands refer to the “psychological, physical, and social aspects of the job that require sustained physical or mental effort and are therefore associated with certain physiological and psychological costs” (Demerouti et al., 2001, p. 501), such as work–family conflict, time pressure, and work overload. Furthermore, JD-R theory posits that job resources can motivate employees in terms of work engagement and generate more positive outcomes, whereas job demands can induce employee burnout and generate more negative outcomes (Bakker et al., 2023). Based on JD-R theory, Kloutsiniotis and Mihail (2020) suggested that high-performance work systems are in-directly related to employee burnout through the influences of job variety and work–family conflict. Drawing on the central tenets of JD-R theory, we argue that algorithmic control can simultaneously enhance employees’ job resources and job demands, which in turn affects the well-being of food delivery drivers. Specifically, on the one hand, algorithmic control provides delivery drivers with continuous, real-time, and frequent performance feedback through tracking evaluation, and standardized guidance (), thereby enhancing the perceived specificity and timeliness of feedback and improving feedback quality. In addition, algorithmic control clearly delineates task scope, job responsibilities, and performance standards (; ), which reduces role ambiguity and enhances role clarity. On the other hand, algorithmic control can implicitly or explicitly accelerate delivery drivers’ work pace through behavioral constraints and real-time monitoring (; ), thereby increasing time pressure. Moreover, continuous task allocation that gives limited consideration to drivers’ capacity may further increase the order volume assigned to food delivery drivers (), potentially resulting in work overload. Accordingly, in this study, time pressure and work overload are conceptualized as job demands, whereas feedback quality and role clarity are conceptualized as job resources.\n\nFeedback quality, which forms an important aspect of the feedback environment, refers to the value and usefulness of feedback information (). High-quality feedback can provide accurate and useful guidance and assistance for employees when completing work tasks (). Thus, the quality of feedback can be considered a job resource (). Previous empirical research has proven that leader motivating language, leader learning goal orientation, and powerful artificial intelligence data analytics are important antecedents of feedback quality (Guo and Ling, 2020; ). Accordingly, because algorithmic control replaces the role of managers in traditional work (Duggan et al., 2020), we anticipate that algorithmic control is positively related to feedback quality.\n\nFirst, feedback quality is enhanced through instructions from immediate supervisors, such as telling employees how to complete their work (Guo and Ling, 2020). As the direct supervisor of food delivery drivers, algorithmic control can automatically dispatch orders based on the geographical location of consumers, restaurants, and drivers. Furthermore, it can also plan the driver’s delivery route in advance, enabling them to avoid potential risks such as traffic accidents and traffic congestion during the delivery process (). In this manner, these clear and timely algorithmic instructions can enhance the quality of feedback provided. Second, by providing drivers with real-time information regarding orders, customer evaluations, and daily income, algorithmic control enables them to obtain timely, accurate, and visual-based performance feedback information (; Huang, 2023). Feedback information of this nature simultaneously puts forward job requirements and provides helpful suggestions for drivers regarding how they can improve their future work performance (; Huang, 2023). In this way, algorithmic control renders performance feedback information more timely, accurate, helpful, and easy to understand, with these items forming the core of quality feedback (). Thus, we propose:\n\n> *H1*: Algorithmic control is positively related to feedback quality.\n\nRole clarity is a job resource that refers to employees clearly knowing the tasks, objectives, and expectations associated with their jobs (Demerouti et al., 2012). A significant number of studies have explored the origins of role clarity, including regarding individual trait factors (i.e., internal work locus of control and general self-efficacy) and management styles (i.e., outcome-based managerial control, ethical leadership, and prevention-focused leadership) (Demerouti et al., 2012; Kauppila, 2014; Li and Griffin, 2022; ). In the platform economy, algorithmic control plays the role of a line leader and provides direct guidance to food delivery drivers (Huang, 2023). Based on this, we argue that algorithmic control can enhance role clarity.\n\nFirst, setting clear goals and helping employees clarify their task scope and job responsibilities play a crucial role in enhancing role clarity (; ). As the direct supervisor of food delivery drivers, algorithmic control not only provides personalized task goals and clarifies task scope through standardized guidance, but also monitors drivers’ work progress and service attitudes and delivers real-time feedback (; Huang, 2023; Lu et al., 2024), thereby enabling drivers to develop a clearer understanding of their job responsibilities. Accordingly, algorithmic control enhances delivery drivers’ role clarity. Second, algorithmic control clarifies the rewards and punishments associated with different performance levels through behavioral constraints, thereby reducing ambiguity between work inputs and anticipated rewards and strengthening job expectations (; Lu et al., 2024). Job expectations constitute a core component of role clarity (; ). Third, existing research indicates that direct and high-level supervision and guidance of employees’ work-related activities enhance role clarity (Kauppila, 2014). Algorithmic control, as a management practice that delivers comprehensive supervision and guidance through algorithmic systems, therefore plays a critical role in enhancing food delivery drivers’ role clarity. Thus, we propose:\n\n> *H2*: Algorithmic control is positively related to role clarity.\n\nTime pressure is a job demand that refers to individuals not having enough time to complete their work, or facing the need to complete their work faster than usual (). Employees facing time pressure clearly know that they need to put more effort into completing their work in a timely manner (Kern and Zapf, 2021). Drawing on JD-R theory, demonstrated that high-performance HR practices are positively associated with employee job demands in the form of time demands. Dietz and Scheel (2017) showed that supervisorial pressure can increase the amount of time pressure experienced by employees. Therefore, in this study, we anticipated that algorithmic control would increase the time pressure faced by drivers.\n\nFirst, algorithmic control quantitatively manages delivery drivers through stringent time-based performance indicators, such as order completion deadlines, on-time delivery rates, and average delivery durations. Drivers are required to complete their tasks within extremely tight time frames, and any delay may negatively affect their ratings and incentives (; Huang, 2023). This exposes them to a constant sense of “countdown” and intensifies their experience of time pressure. Second, beyond merely tracking delivery progress, algorithmic control reinforces the salience of time through mechanisms such as real-time evaluations and ranking systems. This persistent control and surveillance not only require delivery drivers to devote additional time to coping with algorithmic demands (), but also cultivate a perception among drivers that time is equivalent to performance (; Huang, 2023), thereby intensifying drivers’ perceived time pressure. Third, indirect empirical evidence suggests that algorithmically generated route planning significantly influences the time pressure experienced by drivers (). We therefore hypothesize:\n\n> *H3*: Algorithmic control is positively related to time pressure.\n\nWork overload refers to an individual’s perception that their assigned work tasks exceed their own ability level (). Employees who experience a high degree of work overload require additional work time and must put in more effort to complete their assigned tasks (; ). As a job demand, work overload is more easily stimulated and influenced by high-performance work systems, prevention-focused leadership, and enterprise social media use (Kloutsiniotis and Mihail, 2020; Li and Griffin, 2022; ). Thus, we argue that algorithmic control is positively related to drivers’ experience of work overload.\n\nFirst, algorithmic control assigns orders to drivers based on factors such as historical performance and the proximity of merchants and drivers, with limited consideration of drivers’ individual needs (; ). This practice can result in an excessive allocation of tasks during high-demand periods (), compelling drivers to complete multiple high-intensity tasks simultaneously and thereby increasing work overload. Moreover, algorithmic control categorizes food delivery drivers’ performance into hierarchical levels and ranks them within the platform, with these levels and rankings directly tied to compensation and rewards (). This competitive system motivates drivers to continuously accept additional tasks in order to maintain a high rank or secure rewards (Lu et al., 2024), thereby exacerbating their work overload. In addition, although direct empirical evidence on the relationship between algorithmic control and work overload remains limited, prior studies have theoretically suggested that food delivery drivers are more likely to perceive heightened work overload under algorithmic control (Lu et al., 2024; ). We therefore hypothesize:\n\n> *H4*: Algorithmic control is positively related to work overload.\n\n### 2.2 The relationship between job demands and well-being\n\nEmployee well-being is crucial to the survival and development of organizations (). As a multidimensional variable, researchers have suggested that the positive and negative dimensions of well-being should be considered simultaneously (Kaluza et al., 2021). In this study, we considered job satisfaction (frequently deemed an indicator of positive well-being; ) and emotional exhaustion (frequently deemed an indicator of negative well-being; Caesens et al., 2017) as indicators of positive and negative well-being, respectively. Job satisfaction reflects a pleasurable emotional state that arises from making an overall evaluation of one’s job (), whereas emotional exhaustion is defined as a type of burnout caused by work stressors ().\n\nThe JD-R theory states that high job demands consume individuals’ mental and cognitive resources, leading to resource depletion and burnout (Bakker et al., 2023). Therefore, drawing on JD-R theory, we argue that job demands (work overload and time pressure) can stimulate drivers’ emotional exhaustion and curb their level of job satisfaction. First, when delivery drivers experience a high level of work overload, they must expend additional individual resources to manage it successfully (Demerouti et al., 2001). Over time, this consumption of individual resources increases employees’ level of emotional exhaustion (), damages their psychological and physical health (Dlouhy and Casper, 2021), and reduces their job satisfaction. Second, empirical researches have demonstrated that work overload increases employees’ emotional exhaustion and reduces their level of job satisfaction (Hong et al., 2021; ).\n\nThe JD-R theory also states that job demands can consume individual resources and reduce individual well-being (Bakker et al., 2023). To meet the requirements of algorithmic control, high time pressure delivery drivers must invest greater resources (i.e., working at a faster speed and violating traffic rules) to complete their delivery task within the estimated time (), which will consume their self-control resources () and lead to emotional exhaustion (). Moreover, when faced with high long-term levels of time pressure, delivery drivers find themselves in a prolonged state of overtaxing (Demerouti et al., 2001), which can trigger job-related anxiety and depression (), as well as reduced job satisfaction. Additionally, empirical studies have also found that job demands, including time pressure, can promote emotional exhaustion and reduce job satisfaction (Li et al., 2023; Krick et al., 2022). Therefore, we propose:\n\n> *H5a*: Work overload has a positive relationship with emotional exhaustion and a negative relationship with job satisfaction.\n\n> *H5b*: Time pressure has a positive relationship with emotional exhaustion and a negative relationship with job satisfaction.\n\nThe JD-R theory suggests that management practices influence employee well-being by reshaping job demands (Bakker et al., 2023). Accordingly, we propose that the influence of algorithmic control on emotional exhaustion and job satisfaction is indirectly transmitted through job demands (work overload and time pressure). That is, algorithmic control increases the amount of work overload and time pressure experienced by drivers (H3 and H4). This is subsequently expected to increase drivers’ level of emotional exhaustion and reduce their level of job satisfaction (H5). Thus, we hypothesize:\n\n> *H6a*: Work overload mediates the relationship between algorithmic control and well-being such that algorithmic control has a positive relationship with work overload, which, in turn, has a negative relationship with job satisfaction, and a positive relationship with emotional exhaustion.\n\n> *H6b*: Time pressure mediates the relationship between algorithmic control and well-being such that algorithmic control has a positive relationship with time pressure, which, in turn, has a negative relationship with job satisfaction, and a positive relationship with emotional exhaustion.\n\n### 2.3 The relationship between job resources and well-being\n\nAccording to JD-R theory, the provision of adequate job resources can promote employee growth and development, thereby increasing employee work engagement and reducing employee turnover intention (Bakker et al., 2023; Demerouti et al., 2001). Therefore, drawing on JD-R theory, we argue that job resources (feedback quality and role clarity) can enhance job satisfaction and suppress emotional exhaustion. Employees with a level of high role clarity have a clear understanding of their roles, tasks, and responsibilities at work, as well as the expectations and requirements of their supervisors (Kalshoven et al., 2011; ). They are also more likely to be satisfied with their job and experience a greater sense of job control (), which is beneficial for suppressing emotional exhaustion (Karasek, 1998). In the present study, drivers who perceived themselves as having a high level of role clarity displayed a strong understanding of their roles, job responsibilities, and algorithmic requirements in the context of order delivery services. They were also more likely to perceive a higher level of job satisfaction and control, and to experience less emotional exhaustion. Previous empirical evidence has also shown that role clarity is beneficial for enhancing employee job satisfaction and reducing job burnout (; ), and that emotional exhaustion is an important dimension of job burnout (Halbesleben and Bowler, 2007).\n\nBecause high-quality feedback provides recipients with useful information relating to the completion of specific work tasks and the achievement of optimal job performance, recipients are more likely to perceive a high level of satisfaction, regardless of whether the feedback provided is positive or negative (). Accordingly, high-quality algorithmic feedback provides delivery drivers with specific and useful feedback information, such as regarding delivery routes, delivery times, and service performance (Huang, 2023; ). This kind of detailed feedback can stimulate drivers’ work satisfaction and reduce their level of emotional exhaustion (; ). Furthermore, indirect empirical researches have repeatedly found that the feedback environment, which also encompasses feedback quality, has a positive effect on improving job satisfaction and suppressing job burnout (; Gong et al., 2017). Therefore, we propose:\n\n> *H7a*: Role clarity has a positive relationship with job satisfaction and a negative relationship with emotional exhaustion.\n\n> *H7b*: Feedback quality has a positive relationship with job satisfaction and a negative relationship with emotional exhaustion.\n\nThe JD-R theory suggests that management practices influence employee well-being by reshaping job resources (Bakker et al., 2023). Accordingly, we propose that the influence of algorithmic control on emotional exhaustion and job satisfaction is indirectly transmitted through job resources (role clarity and feedback quality). That is, algorithmic control increases the amount of role clarity and feedback quality experienced by drivers (H1 and H2). This is subsequently expected to increase drivers’ level of job satisfaction and reduce their level of emotional exhaustion (H7). Thus, we hypothesize:\n\n> *H8a*: Feedback quality mediates the relationship between algorithmic control and well-being such that algorithmic control has a positive relationship with feedback quality, which, in turn, has a positive relationship with job satisfaction, and a negative relationship with emotional exhaustion.\n\n> *H8b*: Role clarity mediates the relationship between algorithmic control and well-being such that algorithmic control has a positive relationship with role clarity, which, in turn, has a positive relationship with job satisfaction, and a negative relationship with emotional exhaustion.\n\nIn summary, the conceptual model proposed in this study is illustrated in.\n\nFigure 1\n\n![Image](https://www.frontiersin.org/api/ipx/w=340&f=webp/https://www.frontiersin.org/files/Articles/1736349/xml-images/fpsyg-17-1736349-g001.webp)\n\n![Flowchart depicting the influence of algorithmic control on job resources and demands, affecting well-being. Algorithmic control impacts job resources like feedback quality and role clarity, and job demands like time pressure and work overload. These factors influence well-being, including job satisfaction and emotional exhaustion.](https://www.frontiersin.org/files/Articles/1736349/xml-images/fpsyg-17-1736349-g001.webp)\n\n## 3 Method\n\n### 3.1 Sample\n\nThe sample for this study comprised delivery drivers affiliated with Meituan and Ele.me platforms in Chongqing, China. Meituan and Ele.me are the two largest food delivery platforms in China, with 7.45 million and 4 million delivery drivers, respectively. With the assistance of station managers from both firms, we introduced the purpose of this study and the corresponding data collection procedures to 702 delivery drivers, of whom 687 were willing to participate. A three-stage questionnaire collection method was adopted to reduce the impact of common method variances (CMV). Specifically, at Time 1, 592 (86.17% response rate) delivery drivers completed questionnaires that addressed the topics of algorithmic control, extraversion, neuroticism, and demographic variables. At Time 2 (1 month after Time 1), 527 (76.71% response rate) delivery drivers responded to questionnaires designed to measure the extent of their job demands (time pressure and work overload) and job resources (feedback quality and role clarity). At Time 3(1 month after Time 2), 446 delivery drivers provided information relating to their own well-being (job satisfaction and emotional exhaustion).\n\n### 3.2 Measures\n\nVariables in the delivery driver surveys were asked to indicate the extent to which they agreed with the statements on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).\n\nAlgorithmic control. Due to the focus of this study on food delivery drivers, we used eleven items to measure algorithmic control. A sample item is “Algorithm intelligently assigns my work tasks” (*α*  = 0.95).\n\nFeedback quality. We used five items to measure feedback quality. A sample item is “Algorithms give me useful feedback on my job performance” (α = 0.91).\n\nRole clarity. We used five items to measure role clarity. A sample item is “I have clear and planned objectives for my work” (α = 0.85).\n\nTime pressure. We used Durham et al.’s (2000) four items to measure time pressure. A sample item is “Task durations are often short” (α = 0.84).\n\nWork overload. We used four items to measure work overload. A sample item is “I feel that I have handled more requests, questions or complaints than expected” (α = 0.84).\n\nJob satisfaction. We used three items to measure job satisfaction. A sample item is “Overall, I’m satisfied with my current job” (α = 0.92).\n\nEmotional exhaustion. We used five items to measure emotional exhaustion. A sample item is “I feel exhausted at the end of the working day” (α = 0.87).\n\nControl variables. First, marriage (0 = unmarried, 1 = married) was controlled because it can provide emotional support to individuals (). Second, previous research suggests that education is beneficial in helping employees cope with changes in the workplace (). Thus, we controlled for education (1 = employees held high school diploma or below, 2 = employees held junior college degree, 3 = employees held bachelor degree, 4 = employees held postgraduate degree or above). Third, gender (1 = female, 2 = male) was included since there are differences in well beings among employees of different genders (Kaluza et al., 2021). Fourth, employees across different age groups(1 = under 25 years old, 2 = 25–35 years old (excluding 35 years old), 3 = 35–45 years old (excluding 45 years old), 4 = 45 years old and above) and position tenure(1 = less than 1 year, 2 = 1–5 years (excluding 5 years), 3 = 5–10 years (excluding 10 years), 4 = 10 years and above) may show different levels of well-being due to factors such as vigor and health (). Thus, we controlled for drivers’ age and position tenure. In addition, previous researches have found that extraversion has a positive effect on employee well-being, while neuroticism has a negative impact on employee well-being (Anglim and Horwood, 2021). Therefore, we controlled for extra-version and neuroticism. We used Caci et al.’s (2014) four items to measure extraversion, a sample item is “I like to have a lot of people around me” (α = 0.88). Neuroticism is also measured by four items as developed by Caci et al. (2014), a sample item is “I feel unable to manage different situations” (α = 0.88).\n\n## 4 Results\n\n### 4.1 Confirmatory factor analysis (CFA)\n\nBecause the data on algorithmic control, feedback quality, role clarity, time pressure, work overload, job satisfaction, emotional exhaustion, neuroticism and extraversion were collected from delivery drivers, we use AMOS 26.0 maximum likelihood estimation to conduct the CFA. The results () show that the proposed nine-factor model (χ 2  = 1798.33, *df*  = 909, *p*  < 0.001; RMSEA = 0.05, SRMR = 0.05, AIC = 2050.33, CFI = 0.93, IFI = 0.93) was a significantly better fit than an eight-factor model (i.e., combing neuroticism and extraversion into one factor, χ 2  = 2727.36, *p*  < 0.001; RMSEA = 0.07, SRMR = 0.08 AIC = 2963.36, CFI = 0.85, IFI = 0.85), a seven-factor model (i.e., combing neuroticism, emotional exhaustion and extraversion into one factor, χ 2  = 3653.63, *p*  < 0.001; RMSEA = 0.08, SRMR = 0.09, AIC = 3875.63, CFI = 0.77, IFI = 0.77), a six-factor model (i.e., combing neuroticism, job satisfaction, emotional exhaustion and extraversion into one factor, χ 2  = 4574.32, *p*  < 0.001; RMSEA = 0.10, SRMR = 0.10, AIC = 4784.32, CFI = 0.70, IFI = 0.70), a five-factor model (i.e., combing neuroticism, work overload, job satisfaction, emotional exhaustion and extraversion into one factor, χ 2  = 5195.09, *p*  < 0.001; RMSEA = 0.10, SRMR = 0.11, AIC = 5385.09, CFI = 0.64, IFI = 0.62), a four-factor model (i.e., combing neuroticism, time pressure, work overload, job satisfaction, emotional exhaustion and extraversion into one factor, χ 2  = 5837.99, *p*  < 0.001; RMSEA = 0.11, SRMR = 0.12, AIC = 6029.99, CFI = 0.59, IFI = 0.52), a three-factor model (i.e., combing neuroticism, role clarity, time pressure, work overload, job satisfaction, emotional exhaustion and extraversion into one factor, χ 2  = 6555.19, *p*  < 0.001; RMSEA = 0.12, SRMR = 0.13, AIC = 6741.19, CFI = 0.53, IFI = 0.53), a two-factor model (i.e., combing neuroticism, role clarity, time pressure, work overload, job satisfaction, feedback quality, emotional exhaustion and extraversion into one factor, χ 2  = 7173.82, *p*  < 0.001; RMSEA = 0.12, SRMR = 0.13, AIC = 7355.82, CFI = 0.48, IFI = 0.48) and a one-factor model (χ 2  = 9287.54, *p*  < 0.001; RMSEA = 0.14, SRMR = 0.18, AIC = 9467.54, CFI = 0.30, IFI = 0.31), confirming discriminant validity. Furthermore, shows that the composite reliability (CR) and average variance extracted (AVE) for all variables were greater than 0.8 and 0.5, respectively, supporting convergent validity.\n\nTable 1\n\n| Model | χ 2 | *df* | Δχ 2 | Δ *df* | RMSEA | SRMR | AIC | CFI | IFI |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| Nine-factor model | 1798.33 | 909 | – | – | 0.05 | 0.05 | 2050.33 | 0.93 | 0.93 |\n| Eight-factor model | 2727.36 | 917 | 929.03 *** | 8 | 0.07 | 0.08 | 2963.36 | 0.85 | 0.85 |\n| Seven-factor model | 3653.63 | 924 | 1855.30 *** | 15 | 0.08 | 0.09 | 3875.63 | 0.77 | 0.77 |\n| Six-factor model | 4574.32 | 930 | 2775.99 *** | 21 | 0.10 | 0.10 | 4784.32 | 0.70 | 0.70 |\n| Five-factor model | 5195.09 | 935 | 3396.76 *** | 26 | 0.10 | 0.11 | 5385.09 | 0.64 | 0.62 |\n| Four-factor model | 5837.99 | 939 | 4039.66 *** | 30 | 0.11 | 0.12 | 6029.99 | 0.59 | 0.52 |\n| Three-factor model | 6555.19 | 942 | 4756.86 *** | 33 | 0.12 | 0.13 | 6741.19 | 0.53 | 0.53 |\n| Two-factor model | 7173.82 | 944 | 5375.49 *** | 35 | 0.12 | 0.13 | 7355.82 | 0.48 | 0.48 |\n| One-factor model | 9287.54 | 945 | 7489.21 *** | 36 | 0.14 | 0.18 | 9467.54 | 0.30 | 0.31 |\n\nConfirmatory factor analyses results.\n\n“+” represents the two factors were combined into one factor. *** denotes *p* < 0.001.\n\nAC, Algorithmic control; FQ, Feedback quality; RC, Role clarity; TP, Time pressure; WO, Work overload; JS, Job satisfaction; EE, Emotional exhaustion; NE, Neuroticism; EX, Extraversion.\n\nNine-factor model = AC, FQ, RC, TP, WO, JS, EE, NE, EX; Eight-factor model = NE+EX, AC, FQ, RC, TP, WO, JS, EE; Seven-factor model = NE+EX+EE, AC, FQ, RC, TP, WO, JS; Six-factor model = NE+EX+EE+JS, AC, FQ, RC, TP, WO; Five-factor model = NE+EX+EE+JS +WO, AC, FQ, RC, TP; Four-factor model = NE+EX+EE+JS +WO+TP, AC, FQ, RC; Three-factor model = NE+EX+EE+JS +WO+TP +RC, AC, FQ; Two-factor model = E + EX+EE+JS +WO+TP +RC+FQ, AC; One-factor model = All items loaded on one factor.\n\nTable 2\n\n| Variable | Mean | SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| 1. Genders | 1.73 | 0.44 | 1 |\n| 2. Age | 2.58 | 0.81 | −0.10 | 1 |\n| 3. Marriages | 0.63 | 0.49 | −0.10 * | 0.18 ** | 1 |\n| 4. Education attainment | 1.81 | 0.82 | 0.04 | 0.07 | 0.02 | 1 |\n| 5. Position tenure | 2.94 | 0.84 | 0.07 | 0.02 | −0.29 ** | 0.05 | 1 |\n| 6. Algorithmic control | 3.40 | 0.65 | 0.08 | 0.09 * | −0.06 | 0.04 | 0.04 | 1 |\n| 7. Role clarity | 3.29 | 0.68 | −0.01 | 0.16 ** | −0.06 | 0.04 | 0.07 | 0.21 ** | 1 |\n| 8. Neuroticism | 3.08 | 0.78 | −0.01 | 0.05 | −0.01 | 0.12 * | 0.06 | 0.07 | −0.05 | 1 |\n| 9. Work overload | 3.14 | 0.73 | 0.05 | −0.01 | −0.06 | −0.09 * | 0.03 | 0.19 ** | −0.09 | 0.10 * | 1 |\n| 10. Time pressure | 3.42 | 0.70 | 0.01 | 0.05 | −0.08 | −0.07 | 0.09 | 0.23 ** | −0.12 ** | 0.07 | 0.14 ** | 1 |\n| 11. Job satisfaction | 3.14 | 0.88 | 0.04 | 0.002 | −0.06 | 0.06 | −0.04 | 0.22 ** | 0.29 ** | −0.14 ** | −0.23 ** | −0.21 ** | 1 |\n| 12. Feedback quality | 3.25 | 0.77 | 0.07 | 0.004 | −0.10 * | 0.02 | 0.04 | 0.18 ** | 0.23 ** | −0.09 | −0.11 * | −0.12 * | 0.50 ** | 1 |\n| 13. Extroverted | 3.21 | 0.74 | 0.002 | −0.03 | 0.06 | −0.02 | −0.03 | 0.13 ** | 0.17 ** | −0.04 | −0.12 * | −0.05 | 0.26 ** | 0.40 ** | 1 |\n| 14. Emotional exhaustion | 3.09 | 0.71 | 0.06 | 0.04 | 0.12* | 0.02 | 0.04 | 0.04 | −0.21 ** | 0.26 ** | 0.24 ** | 0.24 ** | −0.18 ** | −0.30 ** | −0.22 ** | 1 |\n| AVE | – | – | – | – | – | – | – | 0.61 | 0.54 | 0.65 | 0.57 | 0.58 | 0.80 | 0.66 | 0.65 | 0.57 |\n| CR | – | – | – | – | – | – | – | 0.95 | 0.85 | 0.88 | 0.84 | 0.84 | 0.92 | 0.91 | 0.88 | 0.87 |\n\nMeans, standard deviations, and correlations.\n\nGender: 1 = female, 2 = male; Age: 1 = under 25 years old, 2 = 25–35 years old (excluding 35 years old), 3 = 35–45 years old (excluding 45 years old), 4 = 45 years old and above. Marriages: 0 = unmarried, 1 = married. Education: 1 = employees held high school diploma or below, 2 = employees held junior college degree, 3 = employees held bachelor degree, 4 = employees held postgraduate degree or above. Tenure: 1 = less than 1 year, 2 = 1–5 years (excluding 5 years), 3 = 5–10 years (excluding 10 years), 4 = 10 years and above. AVE = average variance extracted, CR = composite reliability. * denotes *p*  < 0.05, ** denotes *p*  < 0.01.\n\n### 4.2 Common method variance (CMV)\n\nFirst, the Harman’s single-factor analysis results indicate that the first factor explained 19.16% of the total variance. Second, we test a ten-factor model that included the nine-factor model (algorithmic control, feedback quality, role clarity, time pressure, work overload, job satisfaction, emotional exhaustion, neuroticism, and extraversion) and a CMV factor. The results showed that compared to the nine-factor model, the ten-factor model resulted in a significant improvement in model fit (Δχ 2 [45] = 281.082, *p*  < 0.001). However, the variance extracted by the CMV factor was only 2.38%, less than the suggested floor of 25% (Hoobler and Hu, 2013). Third, shows that the correlation coefficients of all variables are less than or equal to 0.50. Therefore, the CMV in the present study is not a serious concern.\n\n### 4.3 Descriptive statistics and correlations\n\nreveals that algorithmic control was positively correlated with feedback quality (*r* = 0.18, *p* < 0.01), role clarity (*r* = 0.21, *p* < 0.01), time pressure (*r* = 0.23, *p* < 0.01), and work overload (*r* = 0.19, *p* < 0.01). Furthermore, feedback quality was negatively correlated with emotional exhaustion (*r* = −0.30, *p* < 0.01) and positively correlated with job satisfaction (*r* = 0.50, *p* < 0.01); role clarity was negatively correlated with emotional exhaustion (*r* = −0.21, *p* < 0.01) and positively correlated with job satisfaction (*r* = 0.29, *p* < 0.01); time pressure was positively correlated with emotional exhaustion (*r* = 0.24, *p* < 0.01) and negatively correlated with job satisfaction (*r* = −0.21, *p* < 0.01); and work overload was positively correlated with emotional exhaustion (*r* = 0.24, *p* < 0.01) and negatively correlated with job satisfaction (*r* = −0.23, *p* < 0.01).\n\n### 4.4 Hypotheses testing\n\nOur research deploys structural equation modeling with AMOS 26.0 maximum likelihood estimation to examine our hypotheses. The structural model showed an acceptable fit (χ 2  = 2225.46, *df*  = 1,125, *p*  < 0.001; RMSEA = 0.047, CFI = 0.91, SRMR = 0.08) (Kline, 2022). As seen in, the path coefficient between algorithmic control and feedback quality (*b*  = 0.232, *p*  < 0.001) was positive and significant, supporting Hypotheses 1. Further, the path coefficient between algorithmic control and role clarity (*b*  = 0.221, *p*  < 0.001) was positive and significant, supporting Hypotheses 2. Additionally, algorithmic control was positively related to time pressure (*b*  = 0.275, *p*  < 0.001) and work overload (*b*  = 0.224, *p*  < 0.001), supporting Hypotheses 3 and Hypotheses 4.\n\nFigure 2\n\n![Image](https://www.frontiersin.org/api/ipx/w=340&f=webp/https://www.frontiersin.org/files/Articles/1736349/xml-images/fpsyg-17-1736349-g002.webp)\n\n![Flowchart illustrating the relationships between algorithmic control and job-related factors. \"Algorithmic control\" influences \"Feedback quality,\" \"Role clarity,\" \"Time pressure,\" and \"Work overload\" with numerical values. These factors further affect \"Job satisfaction\" and \"Emotional exhaustion,\" connected by arrows with respective coefficients.](https://www.frontiersin.org/files/Articles/1736349/xml-images/fpsyg-17-1736349-g002.webp)\n\nIn support of Hypotheses 5a, showed that work overload had a positive relationship with emotional exhaustion (*b*  = 0.171, *p*  < 0.001), but had a negative relationship with job satisfaction (*b*  = −0.151, *p*  < 0.01). In support of Hypotheses 5b, showed that time pressure had a positive relationship with emotional exhaustion (*b*  = 0.168, *p*  < 0.001), but had a negative relationship with job satisfaction (*b*  = −0.138, *p*  < 0.01). In support of Hypotheses 7a, showed that role clarity had a negative relationship with emotional exhaustion (*b*  = −0.146, *p*  < 0.05), but had a positive relation-ship with job satisfaction (*b*  = 0.254, *p*  < 0.001). In support of Hypotheses 7b, revealed that feedback quality had a negative relationship with emotional exhaustion (*b*  = −0.201, *p*  < 0.001), but had a positive relationship with job satisfaction (*b*  = 0.491, *p*  < 0.001).\n\nRegarding the mediation hypotheses, we followed the recommendation outlined by by using AMOS 26.0. Specifically, we estimated them by using a user-defined estimated called MyIndirectEffects for AMOS 26.0 (Lee et al., 2024) with 95% confidence intervals and 5,000 bootstrap samples. The mediation effect is considered significant when the 95 percent confidence intervals fail to cover zero. The results showed that the effect of algorithmic control on job satisfaction (*b*  = −0.034, CI = −0.083 to −0.008) and emotional exhaustion (*b*  = 0.038, CI = 0.007 to 0.095) was mediated by work overload, supporting Hypothesis 6a. In support of Hypothesis 6b, the effect of algorithmic control on job satisfaction (*b*  = −0.038, CI = −0.09 to −0.008) and emotional exhaustion (*b*  = 0.046, CI = 0.013 to 0.103) was mediated by time pressure. In addition, the effect of algorithmic control on job satisfaction (*b*  = 0.114, CI = 0.035 to 0.220) and emotional exhaustion (*b*  = −0.047, CI = −0.115 to −0.008) was mediated by feedback quality, supporting Hypothesis 8a. In support of Hypothesis 8b, the effect of algorithmic control on job satisfaction (*b*  = 0.056, CI = 0.016 to 0.127) and emotional exhaustion (*b*  = −0.032, CI = −0.081 to −0.006) was mediated by role clarity.\n\n## 5 Discussion\n\n### 5.1 Theoretical implications\n\nFirst, drawing on JD-R theory, this study enriches the existing research in this area by establishing a dual-pathway model of the relationship between algorithmic control and well-being. Most of the existing researches have been based on self-determination theory and conservation of resources theory, which suggest that algorithmic control suppresses employee work well-being by reducing job autonomy and enhancing job burnout (; Kinowska and Sienkiewicz, 2023), they have overlooked the double-edged sword effect that algorithmic control may have on employees’ well-being. By simultaneously investigating both the salutary and detrimental effects of algorithmic control, our research findings have demonstrated that algorithmic control may enhance drivers’ emotional exhaustion and suppress their job satisfaction through its association with high job demands (work overload and time pressure). More importantly, this study also supports the positive effects of algorithmic control. Our results demonstrate the validity of the intriguing prediction that algorithmic control curbs emotional exhaustion and stimulates job satisfaction by increasing job resources (role clarity and feedback quality). This not only validates the theoretical viewpoint proposed by researchers that algorithmic control has a double-edged sword effect on employee outcomes (; ), but also provides a new theoretical perspective for exploring the double-edged sword effect of algorithmic control in the future.\n\nSecond, this study contributes to the JD-R theory. The JD-R theory has been applied in many domains (i.e., ethnicity, downsizing, and age discrimination) (; Dlouhy and Casper, 2021; Adamovic et al., 2022). Nevertheless, to the best of our knowledge, the present study is an early application of the JD-R theory to the algorithmic context, mapping the opposing mechanisms between algorithmic control and well-being. Although Huo et al. (2025) explored the direct inverted U-shaped effect of algorithmic control on employee work well-being based on the JD-R theory, they did not examine the potential mediators between algorithmic control and employee well-being. According to the perspective of the JD-R theory that management practices can simultaneously stimulate both job demands and resources, this research further demonstrates that the JD-R theory can be used in the algorithmic context. Moreover, while previous researches have mainly focused on situation factors (i.e., downsizing, age discrimination, and paternalistic leadership) that affect job demands and resources (; Dlouhy and Casper, 2021; Adamovic et al., 2022; Lee et al., 2024), with few studies analyzing the antecedents of job demands and resources from the perspective of algorithmic control. Our research shows that algorithmic control can simultaneously induce drivers’ job demands (work overload and time pressure) and job resources (role clarity and feedback quality), expanding the research on the antecedents of the job demands and resources.\n\nThird, this study provides empirical evidence supporting the unique power that algorithmic control has on drivers’ well-being beyond other personality traits. Previously established independent variables, including extraversion and neuroticism (Garcia and Erlandsson, 2011; Anglim and Horwood, 2021), are useful for understanding the antecedents of employee well-being. By controlling for the effects of extraversion and neuroticism, this study was able to empirically test the unique predictive power of algorithmic control. In this way, the results obtained not only provide support for the predictive validity of algorithmic control for predicting drivers’ well-being in the form of emotional exhaustion and job satisfaction in the presence of extraversion and neuroticism, but also identify the opposing transmission mechanisms, as noted above.\n\n### 5.2 Practical implications\n\nOur findings indicate that algorithmic control may reduce delivery drivers’ well-being by increasing the job demands they experience (i.e., time pressure and work overload). Thus, it is necessary to remind platform firms and managers regarding the pitfalls of algorithmic control and to encourage them to take measures to reduce the impact of these negative effects. For example, platform firms can optimize algorithm rules by extending delivery times and improving evaluation systems, thereby reducing the job demands of delivery drivers. Another important point to note is that delivery firms have set up fixed stations and station managers in each city. The job responsibilities of these station managers include providing training and safety guidance for delivery drivers, sharing experiences of how to avoid negative customer reviews, and handling appeal matters for delivery drivers, with these measures helping to make up for the shortcomings of the algorithmic control process (). In this way, station managers can provide job resources for delivery drivers by demonstrating benevolent and service-oriented leadership behaviors, thereby compensating for the high-level job demands induced by algorithmic control. The results of our study also indicate that algorithmic control may enhance delivery drivers’ well-being by increasing their level of job resources (feedback quality and role clarity). Thus, platform firms can not only enrich the feedback information provided and optimize information quality based on the needs of food delivery drivers but also enhance their trust in algorithmic control by explaining the rules of algorithmic design. Ultimately, this can maximize the positive role that algorithmic control plays in enhancing the job resources of food de-livery drivers.\n\n### 5.3 Limitations and future directions\n\nFirst, the use of a sample of delivery drivers limits the generalizability of these research findings with regard to other types of gig workers. Future research could use Uber and DiDi drivers for their samples to further test the validity of the theoretical model constructed in this study. Second, while this study conceptualizes algorithmic control as a holistic construct and demonstrates its dual effects on employee well-being, algorithmic control comprises three distinct dimensions, namely standardized guidance, tracking evaluation, and behavioral constraint, each of which may exert differential effects on employees (). Accordingly, future research could simultaneously examine the specific mechanisms through which each dimension of algorithmic control influences employee well-being, while identifying the key job demands and job resources that mediate these effects. Third, although the independent variable (algorithmic control), mediating variables (time pressure, work overload, feedback quality, and role clarity), and dependent variables (job satisfaction and emotional exhaustion) were collected from delivery drivers at different time points, causal inferences cannot be drawn from the cross-sectional nature of the data. Future research could build on prior studies such as and and employ experimental designs or experience sampling methods to more rigorously test the causal relationships. Fourth, this study incorporated eight mechanisms and did not consider the potential moderating effect of algorithmic control on job demands/resources. Future research can consider station managers’ behavior and drivers’ resources as moderators. Fifth, this study analyzes data from food delivery drivers working for two Chinese food delivery platforms embedded in a high power distance cultural context. In such contexts, delivery drivers are more likely to perceive algorithmic control as a legitimate and taken-for-granted form of managerial authority (Liu et al., 2025b; ), which fosters acceptance of algorithmic control and, in turn, attenuates its negative effects. By contrast, in low power distance cultural contexts such as the United States, delivery drivers are more likely to perceive algorithmic control as an externally imposed and coercive form of control, which may elicit resistance and thereby amplify its negative effects. Accordingly, future research could re-examine the proposed theoretical model in low power distance cultural contexts to assess the generalizability of the present findings.\n\n## 6 Conclusion\n\nDrawing on JD-R theory, this research enriched our understanding of the relationship between algorithmic control and delivery drivers’ well-being by clarifying the underlying mediating mechanism of job resources (feedback quality and role clarity) and job demands (time pressure and work overload). Hopefully, our research findings may use as an impetus for future research into the double-edged sword effect of algorithmic control.\n\n## Statements\n\n### Data availability statement\n\nThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.\n\n### Ethics statement\n\nEthical approval was not required for the studies involving humans because the studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.\n\n### Author contributions\n\nLZ: Formal analysis, Data curation, Conceptualization, Writing – review & editing. XL: Formal analysis, Writing – original draft. CY: Writing – review & editing, Writing – original draft, Conceptualization.\n\n### Funding\n\nThe author(s) declared that financial support was received for this work and/or its publication. This research was supported by the Humanities and Social Sciences Research Planning Project of Chongqing Municipal Education Commission in 2023 (Grant No. 23SKGH268), and the Guizhou University of Finance and Economics School-Level Scientific Research Start-up Fund Project (Grant No. 2022YJ025).\n\n### Conflict of interest\n\nThe author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\n\n### Generative AI statement\n\nThe author(s) declared that Generative AI was not used in the creation of this manuscript.\n\nAny alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. 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Psychol.* 17:1736349. doi: [10.3389/fpsyg.2026.1736349](http://dx.doi.org/10.3389/fpsyg.2026.1736349)\n\nReceived\n\n31 October 2025\n\nRevised\n\n05 January 2026\n\nAccepted\n\n06 January 2026\n\nPublished\n\n21 January 2026\n\nVolume\n\n17 - 2026\n\nEdited by\n\n[Živile Stankeviciute](https://loop.frontiersin.org/people/1191568/overview), Kaunas University of Technology, Lithuania\n\nReviewed by\n\n[Bilal Çankır](https://loop.frontiersin.org/people/3303523/overview), Istanbul Medeniyet University, Türkiye\n\n[Sidra Liaqat](https://loop.frontiersin.org/people/3312258/overview), University of Barcelona, Spain\n\nUpdates\n\n![Crossmark icon](https://static2.frontiersin.org/static-resources/images/crossmark_color.webp)\n\nCopyright"},"author":{"name":"Lu Zhang, Xuehang Ling, Chen Yang","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/700dd734611e5ee2/avatar-5a7645bcd5e5.png","bio":"ObjectivesDrawing on the job demands-resources (JD-R) theory, this study aims to analyze the impact of algorithmic control on the well-being of delivery driv..."},"metadata":{"timestamp":"2026-01-21T00:00:00.000Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/Gm3mjkq3Fq/media/0.png","type":"image","width":1200,"height":788}],"aiComments":[]},{"id":"web-wiioum","shareId":"G6r0z1Bym9","platform":"web","url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11672927/","title":"How Do Algorithmic Management Practices Affect Workforce Well-Being? A Parallel Moderated Mediation Model","shareMode":"full","createdAt":1787222894353,"postedAt":"2026-08-20T10:48:07.362Z","publishedDate":"2026-08-20T10:48:07.362Z","archivedAt":"2026-08-20T10:48:10.651Z","archivedDate":"2026-08-20T10:48:10.651Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/G6r0z1Bym9","contentType":"article","content":{"text":". 2024 Nov 23;14(12):1123. doi: [10.3390/bs14121123](https://doi.org/10.3390/bs14121123)\n\n[Husam Zayid](https://pubmed.ncbi.nlm.nih.gov/?term=%22Zayid%20H%22[Author]) 1, [Ahmad Alzubi](https://pubmed.ncbi.nlm.nih.gov/?term=%22Alzubi%20A%22[Author]) 1,*, [Ayşen Berberoğlu](https://pubmed.ncbi.nlm.nih.gov/?term=%22Berbero%C4%9Flu%20A%22[Author]) 1, [Amir Khadem](https://pubmed.ncbi.nlm.nih.gov/?term=%22Khadem%20A%22[Author]) 1\n\nEditors: Xin-An Zhang 1, Lin Lu 1, Ming Kong 1\n\nPMCID: PMC11672927 PMID: [39767264](https://pubmed.ncbi.nlm.nih.gov/39767264/)\n\n## Abstract\n\nModern workplaces increasingly use algorithmic management practices (AMPs), which shape task assignment, monitoring, and evaluation. Despite the potential benefits these practices offer, like increased efficiency and objectivity, their impact on workforce well-being (WFW) has raised concerns. Drawing on self-determination theory (SDT) and conservation of resources theory (COR), this study examines the relationship between algorithmic management practices and workforce well-being, incorporating job burnout (JBO) and perceived threat (PT) as parallel mediators and person–job fit (PJF) as a moderator. The research employed a cross-sectional survey design targeting 2450 KOSGEB-registered manufacturing SMEs in Istanbul, Turkey. A sample of 666 respondents participated, and the data were analyzed using Smart PLS 4, employing structural equation modeling to test the proposed model. The results indicated that algorithmic management practices significantly increased job burnout and perceived threat, both of which negatively impacted workforce well-being. However, the direct effect of algorithmic management practices on workforce well-being was non-significant. Person–job fit moderated the relationships between algorithmic management practices and both job burnout and perceived threat, further influencing workforce well-being. The findings underscore the critical need for organizations to balance algorithmic efficiency with human-centric practices. Prioritizing person–job fit and fostering transparency in algorithmic processes can mitigate negative impacts, enhance employee well-being, and drive sustainable organizational success in the digital age.\n\n**Keywords:** algorithmic management, workforce well-being, job burnout, person–job fit, perceived threat\n\n## 1. Introduction\n\nTechnological advancements, at the forefront of Industry 4.0, have brought about profound changes across various facets of human society [[1](#fn:1),[2](#fn:2)], including the management of businesses and organizational structures [[3](#fn:3)]. In recent years, researchers have observed a growing interest in and concern for the impact of technological innovations on human resource management [[4](#fn:4)], with particular attention to algorithmic management practices, which are considered one of the most disruptive forms of technological change currently underway [[5](#fn:5),[6](#fn:6)].\n\nInitially, the term algorithmic management practices described how gig-working platforms utilized sophisticated algorithms to allocate, optimize, and evaluate work [[7](#fn:7)]. While these traits are typical of algorithmic management practices, they offer a restrictive definition that excludes many algorithmic practices currently implemented in workplaces [[8](#fn:8)]. For instance, in Amazon, algorithms are used extensively to manage and optimize various aspects of operation to determine the most efficient routes for workers to pick items from shelves, ensuring that they can fulfill orders as quickly as possible. Job burnout affects employees, with contributing factors such as limited career growth opportunities and inadequate management support. Such an environment encourages employees to seek employment in different fields or organizations [[9](#fn:9)].\n\nConversely, higher organizational commitment and job satisfaction are associated with lower levels of burnout [[10](#fn:10)]. While developing management algorithms aims to improve organizational efficiency and individual productivity, new challenges arise for both organizations and their employees. The reliance on algorithms can lead to the dehumanization of human resource management, compromising the personal and empathetic aspects of managing people [[11](#fn:11)]. Further analysis and research are needed to understand the impact of these practices on employee well-being.\n\nJob burnout is a critical factor influencing various work outcomes [[12](#fn:12)]. Algorithmic management practices alter how work is performed, reducing personal influence in the process. Studies suggest a negative relationship between job burnout and control over work, particularly in highly skilled positions [[13](#fn:13)]. These effects can diminish job burnout and responsibility within tasks, potentially affecting workforce well-being [[14](#fn:14)]. Existing research lacks sufficient empirical analysis of the positive or negative effects of algorithmic management practices on workforce well-being, both directly and indirectly, through their impact on work autonomy and overall compensation [[15](#fn:15)]. The study seeks to answer the following research questions:\n\nRQ 1: How do algorithmic management practices affect workforce well-being and what roles do perceived threat and job burnout play in mediating this relationship?\n\nRQ 2: To what extent does a person’s job fit to play as a moderator influence algorithmic management practices and workforce well-being?\n\nRQ 3: What strategies can organizations implement to mitigate the negative effects of algorithmic management practices?\n\nThis study adds to the ongoing conversation by combining the theoretical frameworks of self-determination theory and conservation of resources theory. To examine the relationship between algorithmic management practices and workforce well-being, we incorporated job burnout and perceived threat as parallel mediators and person–job fit as a moderator. We achieved this by using a large dataset from many different organizations. This study contributes to the literature by providing valuable insights into how algorithmic management practices are often utilized to enhance employee mental health and satisfaction. While previous studies have primarily focused on the benefits of algorithmic management practices for productivity and organizational control, fewer have examined their implications for workforce well-being. By introducing perceived threat and job burnout as mediating factors, this study identifies the specific pathway through algorithmic management practices that may negatively impact workforce well-being. Additionally, examining person–job fit as a moderator highlights the individual difference in response to algorithmic management practices which could inform tailored management strategies.\n\nDespite the growing adoption of algorithmic management practices across industries, the well-being-related consequences for employees remain unexplored; existing studies [[6](#fn:6)] largely examine algorithmic management practices in terms of performance outcomes with limited focus on job burnout and perceived threat as mediators and person–job fit as a moderator. This study addresses this gap by focusing on the workforce well-being of algorithmic management practices and testing how individual factors can potentially exacerbate these effects using cross-sectional data, and it endeavors to bridge this gap. The research is structured into three sections: (1) theoretical hypothesis development, elucidating the essence and research models of workforce well-being, algorithmic management practices, job burnout, and perceived threat; (2) a methodology section detailing the empirical research approach, including the research objectives, assumptions, sample characteristics, and results of statistical analyses; and (3) a discussion section culminating in conclusions.\n\n## 2. Theoretical Background and Hypotheses Development\n\n### 2.1. Self-Determination Theory\n\nPsychologists Edward Deci and Richard Ryan first introduced their ideas in their 1985 book, Self-Determination and Intrinsic Motivation in Human Behavior. Self-determination theory represents a broad theory of human motivation that has found successful application across various domains and management [[16](#fn:16)]. It asserts that an employee’s motivational orientation towards job activities influences both their performance and well-being. Self-determination theory categorizes motivation into different types and suggests that these types have distinct antecedents, relations to conservation of resources theory, and outcomes.\n\nOver the years, self-determination theory has addressed the intersection of motivation with organizational performance and wellness concerns, emphasizing the importance of fostering sustainable motivation and volitional engagement among employees and customers [[17](#fn:17)]. Self-determination theory advocates for creating workplace environments that support employees’ autonomy, not only as an end in itself but also as a means to enhance employee satisfaction, well-being, and organizational effectiveness.\n\nVarious factors, such as managerial styles and compensation structures, which contribute to employee autonomy and competence at work, are essential components for fostering engagement and organizational success, as outlined by self-determination theory. Self-determination theory underscores how managerial actions significantly shape organizational factors, either supporting or hindering employees’ fundamental psychological needs.\n\nThe fulfillment of all three basic psychological needs often strongly relates to conservation of resources theory and organizational support for autonomy [[18](#fn:18),[19](#fn:19)]. This conservation of resources theory relation arises because managers who encourage autonomy tend to be responsive to other needs as well, and employees with autonomy are more likely to actively meet their additional psychological needs. Therefore, when employees feel supported in their autonomy, they typically develop a stronger connection to the organization and perceive themselves as more capable and effective [[10](#fn:10),[16](#fn:16)].\n\n### 2.2. Conservation of Resources Theory\n\nStevan Hobfoll introduced conservation of resources theory in the 1980s. This theory is a stress theory that arises when essential resources become endangered, depleted, or unattainable despite significant efforts. Conservation of resources theory states that individuals actively seek to acquire, retain, nurture, and safeguard resources they consider essential. There is an understanding that cognitive processes inherently prioritize resource loss over resource gain, which stems from evolutionary imperatives [[20](#fn:20)].\n\nFundamentally, conservation of resources theory serves as a motivational framework grounded in the evolutionary drive to secure and maintain essential resources for survival, and conservation of resources theory is an element of human behavioral genetics. People use resources not only to cope with stress but also to accumulate a reserve for future adversity. The acquisition and retention of personal, social, and material resources instill in individuals, families, and organizations a sense of capability to navigate stressful situations [[21](#fn:21)].\n\nConservation of resources theory emphasizes that individual appraisal of stress is secondary to the central and universal value placed on resources such as health, well-being, family, self-esteem, and purpose in life. While the cultural expressions of these appraisals may differ, they consistently reflect this conservation of resource elements [[22](#fn:22)]. Moreover, conservation of resources theory emphasizes that we should not analyze stress solely as discrete events, but rather as complex sequences that unfold over time.\n\nFor instance, in a workplace experiencing layoffs, anticipation precedes the actual event, followed by the process of adjustment or finding new employment. Objective factors such as employability, skills, financial savings, and the availability of alternative positions significantly shape outcomes. Individuals’ appraisals, which are generally favorable predictors, stem from their innate tendency to prioritize resource loss over gain, as emphasized by conservation of resources theory [[20](#fn:20)]. This bias is culturally pervasive and not unique to individuals, although personal experiences may influence such appraisals.\n\nThe autonomous use of data-driven artificial intelligence is referred to as algorithmic management practices. While it can improve certain aspects of decision-making, it may also impact job autonomy, perceived fairness, and overall well-being. Existing research indicates that algorithmic management practices exert both direct and indirect effects on well-being. Empirical findings suggest a moderate, direct influence of algorithmic management practices on workforce well-being. Organizations adopting conservation of resources theory principles can positively influence employee well-being.\n\n### 2.3. Algorithmic Management Practices and Workforce Well-Being\n\nAlgorithmic management practices, which involve autonomous decision-making in human resource management using self-learning algorithms and AI, can have a significant impact on employees’ well-being in the workplace. One emerging trend is the adoption of algorithmic management practices, characterized by the integration of algorithms in managerial tasks encompassing HRM and decision-making processes [[23](#fn:23)], which has introduced new paradigms.\n\nWe first coined the term “algorithmic, data-driven management” to describe innovative methods for task assignment, informational support, and performance evaluation, specifically within the ridesharing sector. An algorithm operates as a computational tool that autonomously makes decisions using statistical models or decision rules, eliminating the need for direct human intervention [[24](#fn:24)]. Algorithmic management practices are defined as a control system where self-learning algorithms take on the responsibility for making and implementing decisions that impact labor, thereby reducing human oversight and involvement in the labor process. This results in the automation of HR-related tasks and duties, previously managed by human personnel [[25](#fn:25)].\n\nIn terms of workforce well-being, the employer, as the key architect of the work environment, has a significant role. The literature provides specific recommendations for fostering a supportive and effective workplace, including ensuring employees receive living wages, have autonomy in their work, access professional development opportunities, and are accommodated for disabilities with facilitated return-to-work programs [[6](#fn:6),[26](#fn:26)]. Studies indicate that algorithmic management practices alter work dynamics and diminish personal influence over processes. There exists a negative conservation of resources theory relation between job burnout and a heightened sense of control over work, especially in highly skilled positions.\n\nWhile algorithms can positively impact decision-making concerning personnel, they may also detrimentally affect job burnout, perceived threat, and overall workforce well-being. Algorithmic management practices exert a direct influence on workforce well-being. Larger organizations tend to experience diminishing impacts of algorithmic management practices on well-being and job burnout. While algorithmic management practices have the potential to improve decision-making, organizations must carefully consider their repercussions on employee autonomy and overall well-being. Striking a balance between automation and human agency is imperative for fostering a positive work environment. Therefore, the hypothesis put forward is as follows:\n\n> #### H1. *Algorithmic management practices negatively influence workforce well-being.*\n\n### 2.4. Algorithmic Management Practices and Influences on Job Burnout\n\nAlgorithmic management practices refer to the use of algorithms and AI to manage work processes, tasks, and employee performance. They have proliferated across diverse industries owing to technological advancements. The extant literature on job burnout delineates three components, which constitute the subscales of the Maslach Burnout Inventory [[26](#fn:26)]. Exhaustion, the most studied dimension, signifies stress aspects, including intense physical and emotional fatigue that impedes efficient functioning.\n\nProfessional inefficacy, or reduced personal accomplishment, refers to negative self-evaluation and a profound sense of ineffectiveness in work and interpersonal relationships. However, research indicates that burnout’s conservation of resources theory dimensions are exhaustion and cynicism, or disengagement. This section aims to provide an overview of job burnout, its causes, and its repercussions on individuals and organizations. Additionally, it elucidates individual and organizational interventions to prevent or alleviate burnout severity [[27](#fn:27)].\n\nWe also examine the theoretical perspective of algorithmic management practices on worker well-being. Self-determination theory posits that individuals possess intrinsic psychological needs that enhance motivation and well-being. Algorithmic management practices’ effects on worker motivation are often negative, as algorithmic systems’ rigidity may restrict autonomy and relatedness. However, person–job fit usage practices can moderate these effects. For instance, when algorithmic management allows some autonomy or facilitates clear communication, its impact on motivation may vary.\n\nOrganizations should integrate self-determination theory principles into the design and implementation of algorithmic management practices systems, balancing algorithmic control with opportunities for autonomy and relatedness to enhance worker motivation and well-being [[28](#fn:28)]. Conservation of resources theory underscores how individuals endeavor to acquire, safeguard, and sustain resources to handle stressors. Prolonged work-related stress leads to job burnout, a condition characterized by emotional fatigue, depersonalization, and diminished personal achievement. Frequently, this is due to resource depletion [[29](#fn:29)]. Algorithmic management practices can influence resource availability, impacting burnout risk. In essence, understanding the interplay between algorithmic management practices, worker motivation, and job burnout necessitates consideration of theories such as self-determination theory and conservation of resources theory. Organizations must strike a balance between algorithmic control and human needs to foster workforce well-being and productivity. Accordingly, the following is hypothesized:\n\n> #### H2. *Algorithmic management practices positively influence job burnout.*\n\n### 2.5. Job Burnout and Workforce Well-Being\n\nAnxiety, sickness, despondency, and exhaustion represent facets of diminished mental health and overall well-being in individuals. Similarly, headaches and muscle pains serve as indicators of physical unwellness. Employee workforce well-being catalyzes organizational success, shielding the organization from decreased productivity and reducing costs associated with poor health insurance.\n\nForward-thinking organizations must ensure that their initiatives yield health outcomes that contribute to overall workforce well-being, with a focus on the physical workspace and organizational culture. JBO results from chronic workplace stress that goes unmanaged. It is characterized by emotional exhaustion, depersonalization, and reduced feelings of accomplishment. Burnout can lead to a decline in an employee’s well-being and can also have negative effects on their physical health [[30](#fn:30)].\n\nSubstantial evidence from previous studies highlights a significant relationship between workforce well-being and job burnout [[31](#fn:31),[32](#fn:32),[33](#fn:33),[34](#fn:34),[35](#fn:35)]. Engaged employees are characterized as motivated, self-directed, and valuable contributors who drive organizational growth and development [[36](#fn:36)]. A positive state of mind is characterized by vigor, dedication, and absorption. Engaged employees feel energetic and effective in their work, and they are able to deal with the demands of their jobs [[37](#fn:37)]. The existing literature suggests that adverse workplace conditions negatively affect individual involvement, job satisfaction, and work enthusiasm, while also harming employee well-being [[38](#fn:38)]. According to the conservation of resources theory, there is a negative association between job burnout and workplace factors [[39](#fn:39)]. Consequently, job burnout tends to be more pronounced in unfavorable work environments. Based on the aforementioned discussion, the following hypothesis is formulated:\n\n> #### H3. *Job burnout has a negative influence on workforce well-being.*\n\n### 2.6. Algorithmic Management Practices and Perceived Threat\n\nAlgorithmic management practices involve using algorithms, data analytics, and automated decision-making systems to manage and control work processes and employees. These practices can include automated scheduling, performance tracking, task allocation, and feedback systems. Perceived threat refers to the individual’s subjective assessment of potential harm or danger to their well-being, status, or resources. In the workplace, perceived threats can manifest as fears related to job security, performance evaluations, and personal autonomy [[23](#fn:23),[40](#fn:40)].\n\nThe hypothesis posits that implementing algorithmic management practices in the workplace can improve perceived threats to employees’ performance. This hypothesis suggests that reliance on automated systems for management decisions can make employees feel more vulnerable, examined, and insecure about their job stability and autonomy [[19](#fn:19)]. Self-determination theory was developed, positing that the need to satisfy three fundamental psychological needs drives human motivation and well-being. Algorithmic management practices can undermine employees’ sense of autonomy by rigidly controlling work schedules, task assignments, and performance evaluations. This lack of control can lead to feelings of frustration and helplessness.\n\nThe conservation of resources theory, proposed by [[22](#fn:22)], suggests that individuals strive to obtain their valuable resources, which can be personal. Algorithmic management practices can create a perceived threat to employees’ job security and stability, as decisions may seem arbitrary or opaque, increasing anxiety about potential job loss. Continuous monitoring and automated evaluations can lead to emotional exhaustion and stress, depleting personal resources like energy and self-esteem. Algorithmic systems may undervalue or improperly recognize employees’ efforts, leading to decreased motivation and a reduced perceived return on their work investments [[41](#fn:41)].\n\nSelf-determination theory’s emphasis lies on meeting employees’ psychological needs and how their undermining by algorithmic management practices can increase perceived threat. Conservation of resources theory highlights the role of resource management, where algorithmic management practices can threaten or deplete valuable resources, leading to increased stress and perceived threat [[42](#fn:42)]. By fulfilling the psychological needs outlined in self-determination theory and protecting the resources highlighted in conservation of resources theory, organizations can reduce the perceived threat associated with algorithmic management practices and promote a healthier, more supportive work environment. Drawing from the theoretical framework, the hypothesis is outlined as follows:\n\n> #### H4. *Algorithmic management practices positively influence perceived threat.*\n\n### 2.7. Perceived Threat and Workforce Well-Being\n\nPerceived threat refers to an individual’s subjective evaluation of the likelihood and severity of potential harm or negative outcomes in a given situation. External events or various factors can influence this, posing a risk to one’s job or personal well-being [[43](#fn:43)]. Workforce well-being encompasses the overall mental, emotional, and physical health of employees within an organization. It includes factors of fulfillment in the workplace [[44](#fn:44)].\n\nThe hypothesis is that perceived threat negatively influences workforce well-being. This means that when employees feel threatened, whether by job insecurity, organizational changes, or external factors, they are likely to experience a decline in their overall well-being. This decline can manifest as increased stress, lower job satisfaction, reduced motivation, and overall poorer mental and physical health [[45](#fn:45)].\n\nSelf-determination theory posits that when employees perceive a threat, such as the potential loss of their job or drastic changes in their work environment, their sense of autonomy and competence can be undermined [[46](#fn:46)]. They may feel less in control of their future and less capable of performing their job effectively under the looming threat. Additionally, the stress and anxiety caused by perceived threat can harm their relationships with colleagues, further impacting their relatedness needs. The frustration of these basic psychological needs can lead to decreased well-being [[47](#fn:47)].\n\nConservation of resources theory suggests that individuals strive to protect their resources. Stress occurs when there is potential for actual resource loss or insufficient resource acquisition despite significant investment [[48](#fn:48)]. Perceived threats in the workplace represent a potential loss of valuable resources, such as job security, income, professional status, and social support. The anticipation or experience of these losses can deplete employees’ resources, leading to heightened stress and anxiety.\n\nAs employees invest more effort to cope with or prevent these losses, they may experience burnout and diminished well-being [[46](#fn:46)]. This continuous state of resource depletion and the associated stress can severely impact their mental and physical health. We can understand the negative impact of perceived threats on workforce well-being by integrating self-determination theory and conservation of resources theory. According to self-determination theory, perceived threats undermine employees’ basic psychological needs, leading to reduced well-being [[32](#fn:32),[33](#fn:33)]. Conservation of resources theory complements this by explaining that the anticipation or experience of resource loss due to perceived threats further depletes employees’ resources, exacerbating stress and reducing overall well-being. Together, these theories provide a comprehensive framework for understanding how perceived threats can negatively impact workforce well-being by disrupting psychological needs and depleting valuable resources. Given the preceding arguments, the proposed hypothesis is stated as follows:\n\n> #### H5. *Perceived threat negatively influences workforce well-being.*\n\n### 2.8. Job Burnout as a Mediator\n\nThe term algorithmic management practices refers to the use of sophisticated algorithms to monitor, evaluate, and manage employees [[49](#fn:49)]. This includes practices like automated scheduling, performance tracking, and behavior monitoring. Such practices can lead to increased efficiency but can also result in increased pressure and stress for employees. Job burnout is a state of job stress. It manifests as sensations of fatigue and diminished professional effectiveness [[42](#fn:42)]. Workforce well-being encompasses various aspects of employees’ health and happiness [[44](#fn:44)]. This hypothesis suggests that job burnout mediates the negative impact of algorithmic management practices on workforce well-being. In other words, algorithmic management practices increase job burnout, which in turn reduces workforce well-being.\n\nAlgorithmic management practices often reduce employees’ sense of autonomy and relatedness by imposing rigid controls and constant monitoring. This can lead to a lack of fulfillment of these basic psychological needs, increasing stress and burnout. Consequently, job burnout mediates the relationship between algorithmic management practices and workforce well-being. Job burnout and workforce well-being have a complex relationship [[50](#fn:50)]. There is also research that shows the positive impact on algorithms while offering employees the freedom to create value [[50](#fn:50)]. This means that, despite the use of algorithmic management, employees may have some freedom to feel job burnout. Also, [[49](#fn:49)] showed that algorithmic management practices can lead to resource loss by increasing job demands without providing adequate support or resources. This resource depletion can lead to job burnout, which in turn negatively affects workforce well-being. Thus, job burnout acts as a mediator in the relationship between algorithmic management practices and workforce well-being.\n\nBy integrating self-determination theory and conservation of resources theory, we can understand the mediating role of job burnout in the relationship between algorithmic management practices and workforce well-being. Algorithmic management practices often undermine employees’ fundamental psychological needs and result in resource depletion. This combination boosts job burnout, which hurts workforce well-being. In summary, job burnout mediates the negative impact of algorithmic management practices on workforce well-being, as these practices undermine essential psychological needs and deplete valuable resources, resulting in increased stress and reduced well-being. In light of the evidence discussed, the hypothesis can be articulated as follows:\n\n> #### H6. *Algorithmic management negatively influences workforce well-being through the negative influence of job burnout.*\n\n### 2.9. Perceived Threat as a Mediator\n\nPerceived threat refers to the subjective assessment of potential harm or danger arising from a situation or environment. This can include concerns about job security in the workplace [[50](#fn:50)]. As previously defined, algorithmic management practices involve using algorithms to oversee and supervise various aspects of organizational processes. These practices can lead to heightened efficiency but may also cause employees to feel constantly monitored and evaluated [[25](#fn:25)]. This hypothesis suggests that the perceived threat mediates the negative impact of algorithmic management practices on workforce well-being. In other words, algorithmic management practices increase perceived threat, which in turn reduces workforce well-being. Algorithmic management practices can undermine employees’ sense of autonomy and relatedness. This can result in employees perceiving a threat to their autonomy and job security. The perceived threat response to these psychological needs can increase stress and reduce workforce well-being, making it a mediator in the relationship between algorithmic management practices and workforce well-being.\n\nBy increasing job demands and reducing employees’ control over their work environment, algorithmic management practices can lead to perceived threats. This perception of threat can result in resource loss, leading to increased stress and reduced well-being [[51](#fn:51)]. Thus, perceived threat acts as a mediator in the relationship between algorithmic management practices and workforce well-being. By integrating self-determination theory and conservation of resources theory, we can understand the mediating role of perceived threat in the relationship between algorithmic management practices and workforce well-being. Algorithmic management practices often undermine employees’ basic psychological needs and create a perception of a threat to their resources. This combination increases perceived threat, which negatively impacts workforce well-being. In summary, perceived threat mediates the negative impact of algorithmic management practices on workforce well-being, as these practices undermine essential psychological needs and create a perception of threat to valuable resources, resulting in increased stress and reduced well-being. Therefore, the hypothesis suggested by this review is as follows:\n\n> #### H7. *Algorithmic management practices negatively influence workforce well-being through the negative influence of perceived threats.*\n\n### 2.10. Person–Job Fit as a Moderator\n\nPerson–job fit refers to the compatibility between an individual’s abilities and desires, as well as the demands, rewards, and attributes of a particular job. A high person–job fit means that the job characteristics align well with the individual’s skills and preferences, leading to greater job satisfaction and performance [[52](#fn:52)]. Person–job fit moderates the relationship between algorithmic management practices and job burnout. Particularly, the positive association between algorithmic management practices and job burnout diminishes when employees possess a greater level of person–job fit. Person–job fit also moderates the connection between algorithmic management practices and perceived threat, specifically weakening the positive conservation of resources theory relation between algorithmic management practices and person–job fit when employees demonstrate a higher degree of person–job fit [[53](#fn:53)].\n\nFurthermore, person–job fit moderates the link between algorithmic management practices and workforce well-being. In particular, the negative association between algorithmic management practices and workforce well-being is less pronounced among employees with a higher level of person–job fit. Person–job fit denotes the alignment between an individual’s competencies, skills, and preferences and the demands of a specific job role. When this alignment is optimal, employees typically experience increased job satisfaction, improved performance, and increased retention rates. On the other hand, poor fit can lead to dissatisfaction, stress, and turnover. Organizations assess person–job fit through job analysis, personality assessments, interviews, and evaluations. In the SME industry, achieving a good person–job fit is crucial for employees who directly interact with customers, as it positively impacts the customer experience [[50](#fn:50),[54](#fn:54)]. AI can help identify suitable candidates during recruitment and optimize job assignments.\n\nBy applying self-determination theory and conservation of resources theory, we can understand how person–job fit moderates the impact of algorithmic management practices on job burnout, perceived threat, and workforce well-being. A high person–job fit enhances employees’ sense of autonomy (self-determination theory) while also providing valuable resources (conservation of resources theory). This reduces the stress and burnout associated with algorithmic management practices. A favorable fit mitigates threat perception by making employees feel secure and competent (self-determination theory) and less likely to experience resource loss (conservation of resources theory). Employees with a high person–job fit are better able to satisfy their psychological needs (self-determination theory) and conserve their resources (conservation of resources theory), ensuring their well-being even in the presence of algorithmic management practices. In summary, person–job fit serves as a critical moderator that can mitigate the negative impacts of algorithmic management practices on job burnout, perceived threat, and workforce well-being by fulfilling basic psychological needs and conserving essential resources. Building on the insights provided, the hypotheses are defined as follows:\n\n> #### H8. *Person–job fit moderates the relationship between algorithmic management practices and job burnout, and the positive relationship becomes weaker (stronger) when employees have a higher (lower) degree of person–job fit in the workplace.*\n\n> #### H9. *Person–job fit moderates the relationship between algorithmic management practices and perceived threat, and the positive relationship becomes weaker (stronger) when employees have a higher (lower) degree of person–job fit in the workplace.*\n\n> #### H10. *Person–job fit moderates the relationship between algorithmic management practices and workforce well-being, and the negative relationship is weaker among employees with a higher degree of person–job fit compared to a lower degree of job fit in the workplace.*\n\nThe relationships among algorithmic management practices, job burnout, perceived threat, workforce well-being, and the moderating role of person–job fit are synthesized into the proposed research model. This model visually represents the hypothesized connections and provides a framework for understanding the study’s conservation of resources theory and variables, as illustrated in [Figure 1](#behavsci-14-01123-f001).\n\n![Figure 1](https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21f0/11672927/f88245afc1b4/behavsci-14-01123-g001.jpg)\n\n## 3. Methodology\n\n### 3.1. Sample and Data Collection\n\nTo ensure the representativeness of the sample, employees from small- and medium-sized businesses (SMEs) in Turkey registered with the Turkish Small Business Administration (KOSGEB) were recruited for participation in the study. Given the lack of consensus on the definition of SMEs, particularly across different countries and sectors, this study adopted the criterion of employing fewer than 250 employees, consistent with both the Turkish Small Business Administration and the Turkish State Institute of Statistics. Moreover, a minimum threshold of at least 10 employees was set to exclude micro firms, aligning with established small business research practices [[55](#fn:55)].\n\nThe SME sector is central to Turkey’s economy, driving job creation, economic stability, and innovation. Representing over 99% of enterprises, SMEs generate approximately 73% of employment and contribute around 54% to the GDP [[56](#fn:56)]. The manufacturing industries selected for inclusion encompassed a diverse array of sectors, ranging from food and beverage to chemical and petrochemical, ensuring a comprehensive representation of the Turkish manufacturing landscape. However, their environmental impact is significant, particularly in manufacturing, where they contribute notably to industrial emissions and resource consumption [[57](#fn:57)]. Recent policies encourage sustainable practices, though challenges persist in balancing growth with environmental goals. SMEs’ influence in Turkey highlights their role in both economic development and sustainable progress. The study targeted SMEs operating in the manufacturing sector within the greater metropolitan area of Istanbul, Turkey. This choice was informed by Istanbul’s historical prominence as the country’s primary industrial and commercial hub, accounting for a substantial portion of total capital investment and GDP.\n\nIn manufacturing, AMPs facilitate workforce performance monitoring; automated shift scheduling; and optimized resource allocation in logistics, storage, and delivery [[58](#fn:58)]. AMPs coordinate tasks, track employee movements through wearables, and provide real-time data for informed managerial decisions [[59](#fn:59)]. While AMPs are more established in retail and food services, where algorithmic shift scheduling is prevalent [[60](#fn:60),[61](#fn:61)], their potential to boost operational efficiency in manufacturing is increasingly recognized. The trend reflects a broader shift towards digital technologies in workforce management, with AI-based recruitment and monitoring tools indicating a future where AMPs may become standard across industries [[25](#fn:25),[62](#fn:62)]. AMPs’ integration into manufacturing thus signals a shift toward data-driven methods that reshape traditional production and workforce management.\n\nData collection was conducted through the distribution of self-administered questionnaires to executives of 2450 KOSGEB-registered manufacturing SMEs within the designated area. Data were collocted between June and July 2024, and executives were personally contacted to elucidate the study’s objectives and seek their approval for participation [[63](#fn:63)]. Upon obtaining management consent, employees were contacted via email, outlining the survey’s purpose, emphasizing voluntary participation, and ensuring confidentiality. This approach aimed to foster a conducive environment for candid responses while respecting participants’ autonomy and privacy.\n\nTo ensure rigor and transparency in our sampling process, we adhered to ethical standards, obtaining informed consent from all participants by explaining the study’s purpose, procedures, and voluntary nature. Using purposive sampling, we targeted professionals in the manufacturing sector to capture relevant insights on AMPs and workplace dynamics.\n\nA total of 666 individuals completed the questionnaires, yielding a response rate of 27.18% from the targeted participant pool. This response rate, while modest, reflects a substantial level of engagement and provides a robust dataset for analysis. Additionally, participants were assured of the opportunity to receive feedback on the research outcomes as a token of appreciation for their cooperation, further incentivizing their involvement.\n\n### 3.2. Basic Characteristics of the Respondent Profile\n\nThe respondent profile in this study reflects a diverse array of small- and medium-sized enterprises (SMEs) operating within the manufacturing sector of Turkey ([Table 1](#behavsci-14-01123-t001)). Across various industry segments, SMEs specializing in food products, electrical equipment, and chemical products emerged as the most prominent, contributing 160, 115, and 102 respondents, respectively. Additionally, significant representation was observed from machinery and equipment (93), rubber and plastic (67), textiles (55), and pharmaceutical sectors (43), with an unspecified “other” manufacturing subgroup comprising 31 respondents. The workforce within these companies was predominantly male, comprising 60.2% of the sample, with individuals aged 41–50 representing the largest subset at 41.3%. In terms of business longevity, a substantial portion of participants (206) had operated between 6 and less than 10 years, while 156 respondents had businesses operational for less than 5 years. Moreover, 125 establishments had operated for more than 11 but less than 15 years, 110 for more than 16 but less than 20 years, and 69 businesses boasted operational histories exceeding 20 years. The majority of respondents identified their businesses as medium-sized enterprises (less than 250 employees), constituting approximately 57.8% of the sample, followed by small businesses (less than 50 employees) at 42.2%.\n\n#### Table 1.\n\nCharacteristics of the sample.\n\n| Variables | Options | Frequency | Percentage (%) |\n| --- | --- | --- | --- |\n| Gender | Male | 401 | 60.2% |\n| Female | 265 | 39.8% |\n| Organizational tenure | Less than 5 years | 156 | 23.4% |\n| 6–less than 10 | 206 | 30.9% |\n| 11–less than 15 | 125 | 18.8% |\n| 16–less than 20 | 110 | 16.5% |\n| More than 20 years | 69 | 10.4% |\n| Industry sectors | Food and Beverage | 160 | 24.0% |\n| Electrical Equipment Manufacturing | 115 | 17.3% |\n| Wood and Chemical Manufacturing | 102 | 15.3% |\n| Machinery and Equipment Manufacturing | 93 | 14.0% |\n| Rubber and Plastic Manufacturing | 67 | 10.1% |\n| Textile and Clothing Manufacturing | 55 | 8.3% |\n| Pharmaceuticals and Medical Equipment | 43 | 6.4% |\n| Other Manufacturing | 31 | 4.6% |\n| Number of employees | Small-sized firms (less than 50 employees) | 281 | 42.2% |\n| Medium-sized firms (less than 250 employees) | 385 | 57.8% |\n| Total | 666 | 100% |\n\n[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11672927/table/behavsci-14-01123-t001/)\n\n### 3.3. Measurement of Variables\n\nThe measures employed to capture data for the empirical analyses drew upon established questionnaires utilized in prior studies ([Appendix A](#app1-behavsci-14-01123)), ensuring the reliability and validity of the instruments. Given the adaptation of the survey instrument for use in Turkey, the translating-backward translation methodology was adopted to facilitate linguistic equivalence and cultural appropriateness. Moreover, the questionnaire underwent rigorous pre-testing iterations to validate the sequencing of questions, wording, and format, thereby enhancing the instrument’s comprehensibility and clarity. Participants rated their agreement with each item on a 5-point Likert scale, ranging from strongly disagree (1) to strongly agree (5).\n\nThe study assessed respondents’ perceptions of AMPs using a four-item scale adapted from [[6](#fn:6),[64](#fn:64)]. This scale covered dimensions such as the utilization of data analytics for monitoring employee performance, enhancing processes or service delivery through data analytics, the adoption of robots, and the establishment of work pace by machines or computers.\n\nJBO, a crucial aspect of workforce well-being, was evaluated using a nine-item scale adapted from previous research [[65](#fn:65),[66](#fn:66)]. This comprehensive scale assessed various dimensions of burnout and reduced personal accomplishment. By considering these facets, researchers aimed to holistically evaluate participants’ experiences related to burnout [[67](#fn:67)].\n\nPerceived threat, another salient variable in the study, was measured using a four-item scale adapted from [[68](#fn:68),[69](#fn:69)]. This scale captured respondents’ subjective perceptions of threat arising from AMPs, providing insights into their cognitive appraisal of potential risks and challenges.\n\nThe moderating role of PJF was assessed using a six-item scale adapted from [[70](#fn:70)], which encompassed dimensions such as skills–requirements fit, needs–supplies fit, and values–congruence fit. This scale enabled an exploration of the extent to which individuals’ alignment with their job roles moderates the relationship between AMPs and workforce well-being.\n\nFinally, workplace well-being, the dependent variable in the model, was measured using an eight-item scale adapted from [[71](#fn:71)]. This scale captured various dimensions of well-being, including physical health, psychological well-being, job satisfaction, and work–life balance, offering a comprehensive assessment of participants’ overall well-being within the workplace context.\n\n### 3.4. Statistical and Analytical Strategy\n\nTo analyze the empirical data collected from the survey and examine the complex inter-relationships among variables, a structural equation modeling (SEM) approach was employed, utilizing Smart PLS 4 as the analytical tool [[72](#fn:72)]. Following the methodological guidelines proposed by [[73](#fn:73)], a two-stage analysis strategy was implemented. In the initial stage, attention was directed towards evaluation of the measurement model; researchers assessed the reliability and validity of the measurement instruments used to operationalize the constructs under investigation. This process involved examining factors such as convergent validity, discriminant validity, and internal consistency reliability to ensure the robustness of the measurement model [[74](#fn:74)]. In the subsequent stage, the structural model was tested to scrutinize its fit and relationships among variables and ascertain the underlying mechanisms driving these associations. As emphasized by [[75](#fn:75)], SEM offers a unified framework for assessing both direct and indirect effects, thus facilitating a comprehensive exploration of the complex pathways underlying the phenomena of interest. This analytical approach enables a nuanced understanding of the intricate interplay between AMPs, individual perceptions, and workforce well-being, thereby advancing theoretical discourse and informing evidence-based interventions aimed at enhancing organizational effectiveness and employee welfare.\n\n## 4. Analysis and Results\n\n### 4.1. Robustness Check\n\nPrior to delving into the substantive analysis, preliminary assessments were conducted to ensure the suitability of the data for structural equation modeling (SEM). This involved scrutinizing the descriptive statistics, reliability, and validity of the measurement model to ascertain the robustness of the dataset. As highlighted by [[76](#fn:76)], one of the crucial considerations in multivariate analysis is the presence of normality in the data distribution, as deviations from normality can compromise the validity and reliability of findings. To this end, skewness and kurtosis values were examined, with no variable exhibiting skewness greater than 3 or kurtosis values exceeding 10 [[77](#fn:77)], indicating adherence to normality assumptions. Additionally, potential multicollinearity issues were evaluated through the examination of variance inflation factor (VIF) values, with all VIF values falling within the acceptable range of 1.467 to 4.386, well below the threshold maximum value of 10 [[75](#fn:75)]. These preliminary assessments affirm the appropriateness of the dataset for SEM analysis, laying the groundwork for subsequent substantive analyses aimed at unraveling the complex relationships among variables.\n\n### 4.2. Common Method Variance\n\nTo mitigate the potential issue of common method variance, we implemented procedural and statistical remedies as recommended by reference [[78](#fn:78)]. These measures were particularly important since data were collected at a single time point. Procedurally, measures were taken to enhance respondent anonymity and encourage candid responses by emphasizing the absence of correct or incorrect answers and urging openness. Furthermore, efforts were made to articulate the study’s purpose clearly, minimize priming effects through careful item arrangement, and reduce question ambiguity via pilot testing [[79](#fn:79)]. These procedural safeguards aimed to mitigate methodological biases and enhance data quality. Additionally, as a statistical remedy in the form of addressing the potential issue of common method variance, we utilized the Harman single-factor procedure. According to reference [[80](#fn:80)], if common method variance is prevalent, a single component would account for a majority of the data variance. However, the results from our study revealed that the first extracted component explained only 34% of the variation. This suggests that common method variance is not a substantial concern in our research. These combined procedural and statistical measures enhance confidence in the validity and reliability of the data, providing a solid foundation for subsequent analyses and interpretations.\n\n### 4.3. Validity and Reliability of the Measurement Model\n\nPrior to assessing the inter-relationships between constructs, a comprehensive evaluation of the measurement model was conducted to ensure its validity and reliability. Following the guidelines outlined by [[81](#fn:81)], confirmatory composite analysis (CCA) was employed to validate the hypothesized five-factor model, encompassing AMP, JBO, PT, PJF, and WFW. As depicted in [Figure 2](#behavsci-14-01123-f002), outer-loading values exceeded the recommended threshold of 0.60 [[73](#fn:73)], which underscores the robustness of the measurement model. Additionally, all item component loadings were statistically significant (*p* < 0.001) and ranged from 0.671 to 0.956, affirming convergent validity [[72](#fn:72)].\n\n![Figure 2](https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21f0/11672927/0247dea5cdfe/behavsci-14-01123-g002.jpg)\n\nDescriptive statistics presented in [Table 2](#behavsci-14-01123-t002), including mean values and standard deviations, offer insights into the distribution and variability of responses across constructs. CR values for all constructs ranged from 0.901 to 0.966, exceeding the threshold of 0.70. This indicates strong internal consistency reliability. AVE values ranged from 0.532 to 0.878, surpassing the predetermined criterion of 0.50. Importantly, the CR scores for all constructs exceeded their respective AVE values (CR > AVE), providing further evidence of convergent validity ([Table 2](#behavsci-14-01123-t002)). Discriminant validity was assessed by comparing the square root of AVE values with inter-construct correlation values [[82](#fn:82)]. These robust measurement model results lay a solid foundation for subsequent analyses and interpretations.\n\n#### Table 2.\n\nValidity and reliability of the measurement model.\n\n| Construct | Indicators | Mean | Std. Deviation | Outer Loadings | VIF | Cronbach’s α | CR | AVE |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| AMPs (AMP) | 0.954 | 0.966 | 0.878 |\n| AMP1 | 2.841 | 1.138 | 0.913 | 1.880 |\n| AMP2 | 2.785 | 1.043 | 0.956 | 3.476 |\n| AMP3 | 2.869 | 1.045 | 0.944 | 3.098 |\n| AMP4 | 2.859 | 1.015 | 0.935 | 2.824 |\n| Job Burnout (JBO) | 0.932 | 0.943 | 0.624 |\n| JBO1 | 3.237 | 1.077 | 0.735 | 2.447 |\n| JBO2 | 3.050 | 1.035 | 0.725 | 2.914 |\n| JBO3 | 3.595 | 0.996 | 0.781 | 2.588 |\n| JBO4 | 3.290 | 1.022 | 0.732 | 2.590 |\n| JBO5 | 3.249 | 1.023 | 0.786 | 3.249 |\n| JBO6 | 3.123 | 1.035 | 0.825 | 3.723 |\n| JBO7 | 3.155 | 1.046 | 0.862 | 3.026 |\n| JBO8 | 3.258 | 1.029 | 0.859 | 4.386 |\n| JBO9 | 2.908 | 1.016 | 0.877 | 3.336 |\n| JBO10 | 2.940 | 1.016 | 0.690 | 2.679 |\n| Perceived Threat (PT) | 0.88 | 0.918 | 0.737 |\n| PT1 | 3.197 | 1.114 | 0.872 | 2.685 |\n| PT2 | 3.215 | 1.261 | 0.832 | 1.987 |\n| PT3 | 3.002 | 1.186 | 0.898 | 3.046 |\n| PT4 | 3.279 | 1.084 | 0.831 | 1.960 |\n| Person–job fit (PJF) | 0.881 | 0.91 | 0.629 |\n| PJF1 | 3.261 | 1.071 | 0.834 | 2.990 |\n| PJF2 | 3.243 | 1.070 | 0.866 | 3.691 |\n| PJF3 | 3.218 | 1.075 | 0.867 | 3.525 |\n| PJF4 | 2.821 | 1.094 | 0.678 | 1.467 |\n| PJF5 | 3.290 | 1.153 | 0.733 | 2.634 |\n| PJF6 | 3.360 | 1.125 | 0.760 | 2.689 |\n| Workplace Well-Being (WFW) | 0.879 | 0.901 | 0.532 |\n| WFW1 | 2.548 | 1.201 | 0.680 | 2.234 |\n| WFW2 | 3.032 | 1.196 | 0.671 | 2.080 |\n| WFW3 | 2.629 | 1.246 | 0.695 | 3.007 |\n| WFW4 | 2.356 | 1.167 | 0.681 | 3.016 |\n| WFW5 | 3.425 | 1.088 | 0.730 | 1.928 |\n| WFW6 | 2.911 | 1.071 | 0.816 | 1.993 |\n| WFW7 | 3.428 | 1.022 | 0.744 | 2.411 |\n| WFW8 | 3.303 | 1.032 | 0.804 | 2.500 |\n\n[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11672927/table/behavsci-14-01123-t002/)\n\nNote(s): Variance inflation factor (VIF), composite reliability (CR), average variance extracted (AVE).\n\nIn evaluating CR for our measurement scales, we observed some CR values exceeding 0.95, which Hair et al. [[74](#fn:74)] suggest could indicate item redundancy. However, this outcome aligns with research showing that trait-oriented scales—such as those measuring AMP and job burnout—typically exhibit higher reliability due to their temporal stability, unlike state-oriented measures [[63](#fn:63)]. The trait-based nature of AMPs and job burnout thus explains the elevated CR values, which indicate strong internal consistency rather than redundancy. These results affirm the reliability of our trait constructs, consistent with psychometric expectations and the study’s objectives.\n\nRegarding discriminant validity, the square root of AVE values exceeded correlation values with other constructs [[82](#fn:82)]. In [Table 3](#behavsci-14-01123-t003), the square root of AVE values for each construct surpassed correlation values with other constructs, affirming the measurement scales’ ability to accurately differentiate between constructs.\n\n#### Table 3.\n\nDiscriminant validity values.\n\n| Factors | 1 | 2 | 3 | 4 | 5 |\n| --- | --- | --- | --- | --- | --- |\n| 1. AMPs (AMP) | ** *0.937* ** | *0.582* | *0.183* | *0.629* | *0.450* |\n| 2. Job Burnout (JBO) | 0.730 | ** *0.790* ** | *0.469* | *0.197* | *0.479* |\n| 3. Person–Job Fit (PJF) | −0.782 | −0.736 | ** *0.793* ** | *0.211* | *0.605* |\n| 4. Perceived Threat (PT) | 0.712 | 0.729 | −0.690 | ** *0.858* ** | *0.225* |\n| 5. Workplace Well-Being (WFW) | −0.337 | −0.364 | 0.300 | −0.405 | ** *0.729* ** |\n\n[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11672927/table/behavsci-14-01123-t003/)\n\nNote(s): Diagonals (in bold and italic) represent the square root of AVE, while the lower triangular pattern represents the shared variance (the squared correlations), and the upper triangular pattern (in italics) represents the HTMT correlation values.\n\nTo further confirm discriminant validity, we used the Heterotrait–Monotrait (HTMT) ratio as recommended by Henseler et al. [[83](#fn:83)], given its increased sensitivity in detecting discriminant validity issues in PLS-SEM models. HTMT values are presented in [Table 3](#behavsci-14-01123-t003), all of which meet the established threshold of 0.85, supporting discriminant validity across constructs [[84](#fn:84)]. Together with the Fornell–Larcker criterion, these HTMT results enhance the robustness of our measurement model, indicating that our constructs are distinct and reliable for accurately capturing the conceptual boundaries needed for analyzing variable inter-relationships.\n\n### 4.4. Direct Effects Estimations\n\nSEM was utilized to examine both the direct and indirect relationships among the study variables. This approach provides insights into the intricate pathways that underlie the impact of AMP on WFW in SMEs. After parameter estimation, bootstrapping was conducted to validate the robustness of the findings with 5000 Bootstrap samples generated through resampling with replacement from the original dataset [[85](#fn:85)]. Remarkably, the coefficients estimated through bootstrapping closely aligned with those derived from Smart PLS 4, affirming the reliability of the results [[72](#fn:72)].\n\nThe results of the structural model, delineated in [Table 4](#behavsci-14-01123-t004) and [Figure 3](#behavsci-14-01123-f003), shed light on the hypothesized direct relationships between AMPs, JBO, PT, and PJF with WFW, accounting for 61%, 56.6%, and 18% of the variation, respectively. Notably, AMPs were found to exert a significant positive effect on job burnout (β = 0.390, *p* < 0.001), affirming H2. Conversely, no support was found for H1, as AMPs exhibited a non-significant impact on workforce well-being (β = −0.064, *p* = 0.339). Furthermore, strong direct relationships were observed between JBO and WFW (β = −0.154, *p* < 0.05), validating H3. Moreover, AMPs had a robust positive direct effect on perceived threat (β = 0.432, *p* < 0.001), supporting H4. PT exhibited a strong negative direct effect on WFW (β = −0.323, *p* < 0.001), corroborating H5.\n\n#### Table 4.\n\nEstimates of direct effects.\n\n| Hypothesis | Hypothesized Relationships | Sample Estimate | Standard Error | T-Statistics | *p* Values | Decision |\n| --- | --- | --- | --- | --- | --- | --- |\n| H1 | AMP → WFW | −0.064 *n.s* | 0.067 | 0.965 | 0.339 | Not Supported |\n| H2 | AMP → JBO | 0.390 *** | 0.041 | 9.609 | 0.000 | Supported |\n| H3 | JBO → WFW | −0.154 * | 0.071 | 2.185 | 0.031 | Supported |\n| H4 | AMP → PT | 0.432 *** | 0.045 | 9.590 | 0.000 | Supported |\n| H5 | PT → WFW | −0.323 *** | 0.066 | 4.790 | 0.000 | Supported |\n\n[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11672927/table/behavsci-14-01123-t004/)\n\nNote(s): *n.s*, statistically non-significant relationships; *, statistically significant at *p* < 0.050; ***, statistically significant at *p* < 0.001.\n\n![Figure 3](https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21f0/11672927/5ed5e3427914/behavsci-14-01123-g003.jpg)\n\n### 4.5. Mediation Effect Analysis\n\nTo examine the mediating roles of JBO and PT in the relationship between AMPs and WFW, mediation analyses were conducted following the guidelines outlined by [[86](#fn:86)]. As shown in [Table 5](#behavsci-14-01123-t005), JBO negatively and significantly mediated the relationship between AMPs and workforce well-being (β = −0.060, *p* < 0.05), providing support for H6. PT emerged as a significant mediator, with a negative and statistically significant indirect effect on WFW (β = −0.139, *p* < 0.001), thereby affirming H7. These findings highlight the multifaceted nature of the relationship between AMPs and workforce well-being, emphasizing the pivotal roles of JBO and PT as mediators in this dynamic interplay.\n\n#### Table 5.\n\nIndirect and interaction effect results.\n\n| Hypothesis | Hypothesized Relationships | Sample Estimate | Standard Error | T-Statistics | *p* Values | CIs | Decision |\n| --- | --- | --- | --- | --- | --- | --- | --- |\n| 0.025 | 0.975 |\n| H6 | AMP → JBO → WFW | −0.060 * | 0.029 | 2.080 | 0.038 | −0.117 | −0.006 | Supported |\n| H7 | AMP → PT → WFW | −0.139 *** | 0.031 | 4.532 | 0.000 | −0.206 | −0.083 | Supported |\n| H8 | AMP × PJF → JBO | 0.082 ** | 0.024 | 3.375 | 0.001 | 0.034 | 0.130 | Supported |\n| H9 | AMP × PJF → PT | 0.104 *** | 0.021 | 5.059 | 0.000 | 0.064 | 0.145 | Supported |\n| H10 | AMP × PJF → WFW | 0.071 † | 0.042 | 1.705 | 0.088 | −0.015 | 0.148 | Not Supported |\n\n[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11672927/table/behavsci-14-01123-t005/)\n\nNote(s): †, statistically significant at *p* < 0.100; *, statistically significant at *p* < 0.050; **, statistically significant at *p* < 0.010; ***, statistically significant at *p* < 0.001; CI, confidence interval.\n\n### 4.6. Analysis of the Moderating Effect of PJF\n\nThe examination of the moderating role of PJF in the relationship between AMPs and various outcome variables yielded insightful findings. Utilizing the product term by utilizing the PLS-SEM approach [[87](#fn:87),[88](#fn:88),[89](#fn:89)] and integrating PJF into the base model, interactions were explored to ascertain its influence on job burnout, perceived threat, and workforce well-being.\n\nThe statistical analysis, detailed in [Table 5](#behavsci-14-01123-t005), revealed significant interactions between AMPs and PJF, affirming H8 and H9. Specifically, the product term of AMP x PJF exhibited significant positive correlations with both job burnout (β = 0.082, *p* < 0.010) and perceived threat (β = 0.104, *p* < 0.001), indicating that PJF positively moderated the relationships between AMPs and these adverse outcomes.\n\nTo elucidate the moderating effects further, simple slope analysis was employed, revealing nuanced insights into the relationship dynamics. As illustrated in [Figure 4](#behavsci-14-01123-f004) and [Figure 5](#behavsci-14-01123-f005), when PJF is high, the positive effects of AMPs on job burnout and perceived threat are amplified. Conversely, when PJF is low, the magnitude of the positive effects increases, indicating that PJF strengthens the adverse impact of AMPs on both job burnout and perceived threat.\n\n![Figure 4](https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21f0/11672927/7e67489378f1/behavsci-14-01123-g004.jpg)\n\n![Figure 5](https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21f0/11672927/fc8d5f4a90d2/behavsci-14-01123-g005.jpg)\n\nHowever, contrary to expectations, the results pertaining to H10 did not provide support for the moderating effect of PJF on the relationship between AMPs and workforce well-being. The product term of AMP × PJF exhibited a marginally significant positive correlation with workforce well-being (β = 0.071, *p* < 0.100), suggesting a weak moderating influence of PJF. The simple slope analysis depicted in [Figure 6](#behavsci-14-01123-f006) illustrated intersecting lines for low and high levels of PJF, indicating that PJF marginally dampens the negative relationship between AMPs and workforce well-being.\n\n![Figure 6](https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21f0/11672927/aaa00468a52d/behavsci-14-01123-g006.jpg)\n\n## 5. Discussion\n\nThis study investigates the complex relationships between algorithmic management practices, job burnout, perceived threat, workforce well-being, and the moderating role of person–job fit. The results provide valuable insights into how modern management practices influenced by technology can impact employees’ mental and emotional states and overall well-being. The results confirm that algorithmic management practices have a significant negative impact on workforce well-being. These practices often reduce employees’ autonomy, lead to constant surveillance, and create pressure to meet rigid performance metrics [[90](#fn:90)]. These factors collectively diminish job satisfaction, increase stress levels, and cause harm. The findings are consistent with self-determination theory, which emphasizes the importance of psychological well-being.\n\nThe analysis supports the hypothesis that algorithmic management practices contribute to higher levels of job burnout. The constant performance monitoring and pressure associated with algorithmic management practices exhaust employees’ emotional and physical reservoirs, resulting in fatigue and burnout. Also, [[6](#fn:6)] refers to the negative relationship between algorithmic management practices and workforce well-being. This aligns with conservation of resources theory, which asserts that stress arises from the risk of resource depletion or actual resource loss. The results confirm that job burnout substantially undermines workforce well-being. Job burnout, which is characterized by emotional fatigue and diminished professional effectiveness, directly influences employees’ mental and physical well-being, resulting in reduced job contentment and overall welfare [[91](#fn:91)].\n\nThe results indicate that algorithmic management practices heighten employees’ perceived threat. The impersonal nature of algorithms and the lack of human interaction can create feelings of job insecurity and anxiety about performance evaluations, contributing to a heightened sense of threat [[92](#fn:92)]. This research validates that perceived threat detrimentally influences workforce well-being. Employees facing perceived threats are prone to heightened stress and anxiety, resulting in adverse effects on their workforce well-being. The mediation analysis demonstrates that job burnout partially mediates the connection between algorithmic management practices and workforce well-being. While algorithmic management practices directly impact well-being, they channel a significant portion of this effect through the increased job burnout it causes [[44](#fn:44)].\n\nSimilarly, perceived threat and job burnout also mediate the relationship between algorithmic management practices and workforce well-being. Algorithmic management practices increase perceived threat, which in turn decreases workforce well-being. The findings emphasize the importance of addressing the psychological impacts of algorithmic management practices to mitigate their negative effects on well-being. Additionally, moderation analysis reveals that person–job fit weakens the positive relationship between algorithmic management practices and job burnout. Employees with a higher degree of person–job fit are better equipped to cope with the demands imposed by algorithmic management practices, experiencing less burnout compared to those with a lower degree of fit [[50](#fn:50)]. The findings also show that person–job fit moderates the relationship between algorithmic management practices and perceived threat. When employees have a higher degree of person–job fit, they are less likely to perceive algorithmic management practices as threatening, thereby reducing the negative impacts on their well-being.\n\nFinally, person–job fit moderates the direct relationship between algorithmic management practices and workforce well-being [[52](#fn:52),[54](#fn:54)]. Employees with a higher degree of person–job fit experience less negative impact on their well-being from algorithmic management practices compared to those with a lower degree of fit. This study highlights the significant negative impacts of algorithmic management practices on workforce well-being, primarily through increased job burnout and perceived threat. However, the presence of a positive person–job fit can mitigate these adverse effects, suggesting that organizations should consider the individual fit between employees and their roles when implementing algorithmic management practices. Ensuring that employees are well matched to their jobs can help alleviate some of the negative consequences of these modern management practices, ultimately supporting better workforce well-being. The integration of self-determination theory and conservation of resources theory provides a strong framework for understanding these dynamics and guiding future research and organizational strategies [[19](#fn:19)].\n\n## 6. Conclusions\n\n### 6.1. Theoretical Contribution\n\nBy examining the relationship between algorithmic management practices and workforce well-being, this research significantly advances our understanding of the intersection between technology-driven management and employee outcomes. Specifically, the integration of self-determination theory and conservation of resources theory offers a robust framework for analyzing how algorithmic management practices influence workforce well-being. Self-determination theory, which emphasizes the fulfillment of psychological needs such as autonomy, competence, and relatedness, helps explain how algorithmic management practices can undermine these needs, leading to decreased motivation and well-being among employees [[93](#fn:93)]. The rigid controls and constant monitoring associated with algorithmic management practices can diminish employees’ sense of autonomy and relatedness, resulting in lower job satisfaction and higher stress levels [[16](#fn:16)].\n\nOn the other hand, conservation of resources theory focuses on how individuals strive to obtain, retain, and protect resources, which are critical for their well-being. Algorithmic management practices’ potential to threaten or deplete these resources such as job security and personal agency can lead to heightened stress and job burnout, which negatively impacts workforce well-being [[22](#fn:22)]. This theoretical integration thus provides a comprehensive explanation for the mechanisms through which algorithmic management practices exert their effects on employees.\n\nBy examining the moderating role of person–job fit, this research sheds light on the conditions under which algorithmic management practices’ effects vary. The study shows that a higher degree of person–job fit can buffer the negative impacts of algorithmic management practices on employee outcomes by ensuring that job demands align with individual abilities, thereby reducing the stress and resource depletion that leads to job burnout [[94](#fn:94)]. This contribution is critical as it underscores the importance of considering individual differences and contextual factors in the application of algorithmic management practices, thereby enriching the literature on person–environment fit and employee well-being.\n\n### 6.2. Practical and Managerial Implications\n\nThe findings of this study carry significant practical and managerial implications for organizations adopting algorithmic management practices. Given the adverse effects of algorithmic management practices on workforce well-being, organizations need to implement strategies that mitigate these negative outcomes. First, organizations should prioritize the integration of person–job fit assessments in their algorithmic management practices systems. Ensuring that employees are well-matched to their roles can reduce the likelihood of job burnout and perceived threat, as well as enhance overall employee satisfaction and well-being. As research suggests, a higher degree of person–job fit can buffer the adverse effects of algorithmic management practices, leading to better employee outcomes [[94](#fn:94)].\n\nMoreover, transparency in algorithmic decision-making processes is crucial. Organizations should ensure that employees understand how decisions affecting their work are made and provide avenues for feedback and participation. This transparency can alleviate perceived threats and foster a sense of fairness and trust, which are critical for maintaining employee engagement and well-being [[23](#fn:23)].\n\nAdditionally, providing training and support tailored to the needs of employees working under algorithmic management practice systems can significantly improve their ability to cope with the demands of such environments. Training programs that enhance employees’ digital literacy and resilience can help them adapt to the technological changes imposed by algorithmic management practices, thus reducing job stress and improving workforce well-being [[49](#fn:49)]. Managers should be aware of the psychological impacts of algorithmic management practices and strive to create a work environment that supports autonomy, competence, and relatedness—key components of self-determination theory. By doing so, organizations can mitigate the dehumanizing effects of algorithmic management practices and promote a healthier, more supportive workplace [[16](#fn:16)].\n\n### 6.3. Limitations and Future Direction\n\nThis research drew upon a distinct sample from a specific sector or entity, potentially constraining the broader applicability of the results. Subsequent studies should strive to validate these findings across varied samples to bolster their external relevance. The use of a cross-sectional framework limits our ability to infer causality regarding the investigated relationships. Future investigations could utilize longitudinal or experimental methodologies to establish causal connections and gain deeper insights into the temporal patterns of algorithmic management practices and employee consequences. While this study examined job burnout and perceived threat as mediating variables and person–job fit as a moderating variable, there may be other mechanisms at play. Future research could explore additional mediators and moderators to provide a more comprehensive understanding of the processes underlying the relationships examined in this study. This research predominantly focused on algorithmic management practices in a broad context, but the impacts may fluctuate depending on contextual variables such as organizational ethos, industry standards, and cultural norms. Subsequent investigations could delve into how these contextual elements shape the conservation of resources theory relations scrutinized in this study. By acknowledging these constraints and exploring avenues for future research, we can improve our understanding of the influence of algorithmic management practices on employee welfare and inform strategies for promoting positive outcomes in the workplace.\n\n## Appendix A\n\n### Table A1.\n\nMeasurement items.\n\n**Algorithmic Management Practices [[6](#fn:6),[64](#fn:64)]** 1. In this establishment, the pace of work of many employees is determined by machines or computers.\n2. This establishment use data analytics to monitor employee performance.\n3. This establishment use data analytics to improve the processes of production or service delivery.\n4. Robots carry complex series of actions automatically, which may include the interaction with people. **Job Burnout [[65](#fn:65),[66](#fn:66)]** 1. Every day I always get up without spirit, facing the work is listless. - 2.I feel very tired after working all day. - 3.My work often makes me feel bored. - 4.I often need to consume too many emotional resources at work. - 5.I feel confused about my current career prospects. - 6.I have lost enthusiasm for my current job. - 7.I think my current job is of little value. - 8.I feel I’m not qualified for my current job. - 9.Leaders often put me in charge of unimportant things. - 10.I often have no confidence in the tasks assigned to me by the leader. **Perceived Threat [[68](#fn:68),[69](#fn:69)]** 1. The increased use of robots in our everyday life is causing more job loss for humans - 2.In the long run, robots pose a direct threat to human safety and well-being - 3.Recent advances in robot technology are challenging the essence of human life - 4.Technological advancements in the robotic are threatening human’s uniqueness **Person–Job Fit [[70](#fn:70)]** 1. The experience and skills required to operate service robots match my own experience, skills, and knowledge. - 2.I believe my skills and abilities match those required by the job. - 3.My job performance is hurt by a lack ofexpertise on the job. (R) - 4.I feel that this work enables me to do the kind of workI want to do. - 5.This work is a good match for me. - 6.This work is the type that I’m seeking. **Workplace Well-Being [[71](#fn:71)]** In the past 6 months, 1. In my work, I achieve my potential. - 2.In my work, I develop abilities that I consider important. - 3.In my work, I engage in activities that express my skills. - 4.In my work, I overcome challenges. - 5.In my work, I achieve results that I regard as valuable. - 6.In my work, I advance in the goals I set for my life. - 7.In my work, I do what I really like doing. - 8.In my work, I express what is best in me.\n[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11672927/table/behavsci-14-01123-t0A1/)\n\n## Author Contributions\n\nWriting—original draft, H.Z.; supervision, A.A.; project administration A.K. and A.B. All authors have read and agreed to the published version of the manuscript.\n\n## Institutional Review Board Statement\n\nThe study was conducted in accordance with the Declaration of Helsinki, and approved by the University of Mediterranean Karpasia, under approval number 2023-2024-Spring003-Tuesday, 28 May 2024.\n\n## Informed Consent Statement\n\nAll participants in this study provided their informed consent.\n\n## Data Availability Statement\n\nThe data from this study can be requested from the conservation of resources theory corresponding author, Ahmad Alzubi.\n\n## Conflicts of Interest\n\nThe authors report no conflicts of interest.\n\n## Funding Statement\n\nThis research received no external funding.\n\n## Footnotes\n\n**Disclaimer/Publisher’s Note:** The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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Provenance information\n\nIntroducing Provenance Information\n\n\n\n![FAIRPlus logo](https://fairplus.github.io/the-fair-cookbook/_static/images/fairplus-mini.png)\n\nRecipe Type\n\nBackground information\n\nAudience\n\nMaturity Level & Indicator\n\nnot applicable\n\nhover me Tooltip text\n\n\n\n## 5.1. Main Objectives\n\nIn all tasks of data integration, especially in the area of Pharma, ensuring trust in data sources is essential. The steps taken to ensure new datasets or sources of information meet a number of criteria ascertaining some level of quality are many. One of them is a check on the origin of the information, in other words, its **Provenance**. Provenance covers the elements detailing how the data was produced by identifying the agents (human, software, workflows) so a certain level of traceability and accountability can be established. The notions of **audit and trail** as well as **versioning** and **authorship** are essential to be able, should any distortion be identified in downstream analysis, to trace back to possible sources of error.\n\n\n\n## 5.2. Provenance: a definition\n\n**“Provenance is information about entities, activities, and people involved in producing a piece of data or thing, which can be used to form assessments about its quality, reliability or trustworthiness”**. Provenance has been an active field of academic research and several models have been developed over the year to cover the domain. The next section will introduce the most known models as well as detail how their overlap and what are the differences between these.\n\n**Data provenance** is also referred to as **data lineage**\n\n\n\n### 5.2.1. OPM Open Provenance Model\n\nPublished in 2011, the Open Provenance Model (OPM) was the first formal model developed to cater for the reporting of provenance information with several main goals in mind:\n\n- provide a domain agnostic, formal and actionable definition of provenance\n- enable sharing of provenance information between systems, an issue of interoperability\n- support tool development and implementation\n- enable validation of provenance messages. The work was well-received and several workshops and working groups refined the specification which resulting in a specification being submitted to the World Wide Web Consortium. The following sections provides further insights into these efforts.\n\n\n\n\n### 5.2.2. The PROV Data Model\n\nThis definition is taken from the W3C Provenance Data Model specifications.\n\n\n\n### 5.2.3. PROV vocabulary:\n\nThe PROV-O Provenance Ontology is a W3C-vetted specification of the Provenance Data Model as an OWL ontology. The namespace for PROV-O is [http://www.w3.org/ns/prov#](http://www.w3.org/ns/prov). It is meant to allow expressing provenance information as modeled in the provenance model [W3C PROV-DM](https://www.w3.org/TR/prov-overview/) with Classes, Properties and relations defined in the W3C Ontology Web Language (OWL). Instances can therefore be represented in RDF and distributed in any of the official serialization, e.g. JSON-LD, RDF/XML, Turtle.\n\nBelow is an example of provenance information represented using the PROV-O ontology and serialized as RDF statements using turtle representation.\n\n\n\n```\n@prefix xsd: .\n@prefix foaf: .\n@prefix prov: .\n@prefix : .\n\n:bar_chart\na prov:Entity;\nprov:wasGeneratedBy :illustrationActivity;\nprov:wasDerivedFrom :aggregatedByRegions;\nprov:wasAttributedTo :derek;\n.\n\n:derek\na foaf:Person, prov:Agent;\nfoaf:givenName \"Derek\";\nfoaf:mbox ;\nprov:actedOnBehalfOf :natonal_newspaper_inc;\n.\n\n:national_newspaper_inc\na foaf:Organization, prov:Agent;\nfoaf:name \"National Newspaper, Inc.\";\n.\n\n:illustrationActivity\na prov:Activity;\nprov:used :aggregatedByRegions;\nprov:wasAssociatedWith :derek;\nprov:wasInformedBy :aggregationActivity;\n.\n\n:aggregatedByRegions\na prov:Entity;\nprov:wasGeneratedBy :aggregationActivity;\nprov:wasAttributedTo :derek;\n.\n\n:aggregationActivity\na prov:Activity;\nprov:startedAtTime \"2011-07-14T01:01:01Z\"^^xsd:dateTime;\nprov:wasAssociatedWith :derek;\nprov:used :crimeData;\nprov:used :nationalRegionsList;\nprov:endedAtTime \"2011-07-14T02:02:02Z\"^^xsd:dateTime;\n.\n\n:crimeData\na prov:Entity;\nprov:wasAttributedTo :government;\n.\n:government a foaf:Organization, prov:Agent .\n\n:nationalRegionsList\na prov:Entity;\nprov:wasAttributedTo :civil_action_group;\n.\n:civil_action_group a foaf:Organization, prov:Agent .\n```\n\n\n\n\n## 5.3. Tools for creating provenance metadata\n\nIn the previous section, we have detailed the landscape of formal models to represent provenance information. In this section, we will show how tools have implemented these models, or domain-specific extension of them as in the case of computation workflow provenance information.\n\n\n\n### 5.3.1. CamFLow\n\n[CamFlow](https://camflow.org/#output_format) is a Linux Security Module (LSM) designed to capture data provenance for the purpose of system audit and aims at capture information flow.\n\nCamFlow support 2 output formats.\n\n- W3C PROV-JSON format\n\n```\n\"ABAAAAAAACAe9wIAAAAAAE7aeaI+200UAAAAAAAAAAA=\": {\n\"cf:id\": \"194334\",\n\"prov:type\": \"fifo\",\n\"cf:boot_id\": 2725894734,\n\"cf:machine_id\": 340646718,\n\"cf:version\": 0,\n\"cf:date\": \"2017:01:03T16:43:30\",\n\"cf:jiffies\": \"4297436711\",\n\"cf:uid\": 1000,\n\"cf:gid\": 1000,\n\"cf:mode\": \"0x1180\",\n\"cf:secctx\": \"unconfined_u:unconfined_r:unconfined_t:s0-s0:c0.c1023\",\n\"cf:ino\": 51964,\n\"cf:uuid\": \"32b7218a-01a0-c7c9-17b1-666f200b8912\",\n\"prov:label\": \"[fifo] 0\"\n}\n```\n\n\nExample of a write edge in W3C PROV format:\n\n\n\n```\n\"QAAAAAAAQIANAAAAAAAAAE7aeaI+200UAAAAAAAAAAA=\": {\n\"cf:id\": \"13\",\n\"prov:type\": \"write\",\n\"cf:boot_id\": 2725894734,\n\"cf:machine_id\": 340646718,\n\"cf:date\": \"2017:01:03T16:43:30\",\n\"cf:jiffies\": \"4297436711\",\n\"prov:label\": \"write\",\n\"cf:allowed\": \"true\",\n\"prov:activity\": \"AQAAAAAAAEAf9wIAAAAAAE7aeaI+200UAQAAAAAAAAA=\",\n\"prov:entity\": \"ABAAAAAAACAe9wIAAAAAAE7aeaI+200UAQAAAAAAAAA=\",\n\"cf:offset\": \"0\"\n}\n```\n\n\nNote\n\nCamFlow also concerns itself with a informatics system audit and as obvious from its design, is meanly focused on the security of Linux based systems. The CamFlow framework is highly configurable and allows `profiles` to be defined. This is a very low level solution and its use remains the confines to information security specialists.\n\n\nWhile this tool is probably of limited use to Life Sciences and bioinformatics applications, we mention it for two reasons:\n\n- it provides one of the first example of an implementation (even if very basic) making use of the W3C Prov-O model.\n- it provides an insight on how computational tool can deal with provenance information in ways which allow assessing systems health from a security point of view.\n\n\n### 5.3.2. Computational workflows and Provenance information:\n\nAs seen when introducing the W3C Provenance Data Model and Provenance Ontology, three key entities are necessary to record and track lineage information:\n\n- The Entity the origin of which we are concerned with.\n- The Activity which resulted in the creation of the Entity\n- The Agent which performed the Activity aforementioned. Because the PROV model is domain agnostic and very generic, it can be either applied as is, to any situation or it can also be extended and specialized to suit a particular domain on knowledge. To give an example, tracking provenance information in the field of bioinformatics shares features with provenance tracking as used in manufacturing, but it also has a number of specific features. In the field of bioinformatics, where computational pipelines, known as workflows, are assembled to process ever larger datasets on high performance computing infrastructure and cloud infrastructure, having the ability to access data lineage matters for a number for reasons, such as:\n\n- audit and trail tasks for regulatory compliance, where every step of the data processing needs to be documented for submission.\n- resource optimization and energy savings (e.g. should a workflow be executed again or not) It is those features which have been the focus of an extension as part of the work on computational biology workflows with CWLProv, and which we will now cover.\n\n\n\n#### 5.3.2.1. Example of CWLProv document\n\nThe infobox below shows an example of CWLProv RDF document which details how provenance information about the execution of CWL coded workflow may be represented. This document is take from the [CWLProv github repository](https://github.com/common-workflow-language/cwlprov/blob/main/prov.md). Such documents are generated and consumed by a feasibility demonstrator tool such as [CWLtool](https://faircookbook.elixir-europe.org/content/recipes/reusability.html)\n\n\n\n```\nprefix id\nprefix provenance\n\nagent(id:a606d227-bf10-4479-8d11-823bb932bbac,\n[prov:type='wfprov:WorkflowEngine', prov:type='prov:SoftwareAgent',\nprov:label=\"cwltool 1.0.20180817162414\"])\n\nactivity(id:73eab018-7b36-4f84-a845-aca8073bd46c, 2018-08-21T15:20:35.059920, -,\n[prov:type='wfprov:WorkflowRun', prov:label=\"Run of workflow/packed.cwl#main\"])\nwasStartedBy(id:73eab018-7b36-4f84-a845-aca8073bd46c, -, id:a606d227-bf10-4479-8d11-823bb932bbac, 2018-08-21T15:20:35.060038)\n\nactivity(id:e79fc8dc-6e40-4236-b22c-41fee22947a9, -, -,\n[prov:type='wfprov:ProcessRun', prov:label=\"Run of workflow/packed.cwl#main/compile\"])\nwasStartedBy(id:e79fc8dc-6e40-4236-b22c-41fee22947a9, -, id:73eab018-7b36-4f84-a845-aca8073bd46c, 2018-08-21T15:20:35.163189)\n\nactivity(id:e79fc8dc-6e40-4236-b22c-41fee22947a9, -, -,\n[prov:has_provenance='provenance:workflow_compile.e79fc8dc-6e40-4236-b22c-41fee22947a9.cwlprov.provn',\nprov:has_provenance='provenance:workflow_compile.e79fc8dc-6e40-4236-b22c-41fee22947a9.cwlprov.ttl'\n])\n```\n\n\nNote\n\nSpecific recipes about FAIR workflows are available in a specific chapter of the book.\n\n\nNote\n\nHow widely supported are CWLprov documents?\n\nThis is very part of academic research, meaning that these specifications demonstrate feasibility and capability. A number of collaborators of the CWLProv group have included such provenance information in their frameworks. Tools such as `Bagit` or specifications such as `Research Objects` recommended CWLProv documents to be included in specific folders of the archives when preparing them.\n\nSee the [BagIt profile](https://github.com/common-workflow-language/cwlprov/blob/main/bagit.md) for details on the CWLProv folder structure, and the [Research Object profile](https://github.com/common-workflow-language/cwlprov/blob/main/ro.md) on how to declare the typing of the PROV files.\n\n\n\n\n#### 5.3.2.2. CWLtool: a component to manage workflow information and generate CWLProv information\n\n‘cwltool’ for Common Workflow Language tool is a python reference implementation for the [Common Workflow Language](https://www.commonwl.org/), which means that it supports the full set of CWL specifications and provides validation functions to check CWL documents.\n\n\n\n```\npip install cwltool\n```\n\n\ncwltool is not the only implementation of the CWL specifications, others such as [Arvados](https://arvados.org/) and [Toil](https://toil.ucsc-cgl.org/) exist. In case these distinct implementations are also installed on the system, one needs to make sure a helper tool known as ‘cwl-runner’ is also installed. The *key* function of ‘cwl-runner’ is to allow users to select which CWL implementation will be executed.\n\n\n\n```\npip install cwltool-runner\n```\n\n\nFor the purpose of this recipe, which is to show how provenance information can be generated by a tool such as cwltool, users will need to make sure that a workflow is available before performing this conversion.\n\n\n\n```\ncwltool --print-rdf --rdf-serializer=turtle mywf.cwl\n```\n\n\n\n\n#### 5.3.2.3. CWLProv-py\n\nThis tool, also an output from the Common Workflow Language consortium, is solely intended as a validator for provenance information when available from Research Objects. It is a standalone python package, which provides a command line interface (CLI) to read, inspect research objects capturing workflow execution information using the CWL syntax.\n\nTo install the package, simply run the standard python install package pip:\n\n\n\n```\npip install cwlprov\n```\n\n\nTo run ‘cwlprov’ following installation and using an exemplar CWL file, run the following command:\n\n\n\n```\ncwlprov --quiet --directory ./test/1.cwl validate\n```\n\n\n\n\n\n### 5.3.3. Provenance and distributed ledger technology\n\nWith this section, we intend to cover another aspect associated with provenance information. It is the issue of trustworthiness of the information and how to ascertain that even if a provenance information message is valid, it actually contains authentic and untempered information.\n\nThe raise of digital currencies such as bitcoin or ethereum has popularized the notion of ‘blockchain’, which is a type of what is known as “distributing ledger technology” (DLT). Blockchains and DLT in general represent technological solution to the problem of trust in provenance. To achieve this goal, DLT relies on three key principles:\n\n- distribution of information: in other words, the system is decentralized, meaning that no single entity holds the database. Instead, a multitude of copies of the information are available from a myriad of independent nodes.\n- transparency: this is a consequence of the distributed nature of the architecture. Transparency is understood as the availability of means of verification by being able to access independent sources of the reference information. This allows consistency checks to be performed and therefore provides the means of tempering detection. Note\n\nTransparency does not equate open. Some blockchains are public but others are private, for instance to support domain specific applications ranging from financial services, supply chain or other sensitive area such as healthcare information.\n\n\n- immutability: this is the last tenet of DLT and refers to the fact that once an entry has been to the distributed ledger, it is digitally signed and synchronized in the network by adding a new element (the block) to the blockchain. Each of the new is digitally signed via some cryptographic algorithm (e.g. Blake2). Any attempt to modify a particular block would result in changing its signature. This can be done but the cost could be prohibitively high as it would entail modifying all subsequent blocks in the chain. This architecture ensures the stability or immutability of the ledger. Important\n\nThis notion of immutability assumes that cryptographic hashes using to digital proof the contracts can not be broken. The most advanced algorithms somehow guarantee this given the current compute power available. However, it should not be taken for granted. A situation where cryptographic methods would be breached by disruptive technology such as breakthrough in quantum computing, are referred to as a `cryptographic armageddon` as it would wreak havoc on the entire edifice by allowing to rewrite a ledger, thus voiding trust in an instant. Despite such alarmist claims, quantum computing methods could make attempts to tamper with a ledger impossible, thus reinforcing the approach.\n\n\n\n\n\n## 5.4. Conclusion\n\nWith this FAIR Cookbook content, we have introduced the notion of Provenance information, providing a brief historical review of the domain model and given a few examples of tools implementing provenance information tracking.\n\nFor a more in depth exploration of provenance information, we encourage our readers to follow up with more detailed material listed below:\n\n\n\n## 5.5. References\n\n\n\n## 5.6. Authors\n\n\n\n## 5.7. License\n\n\n\n---\n\nContents\n\n1. Published in 2011, the Open Provenance Model (OPM) was the first formal model developed to cater for the reporting of provenance information with several main goals in mind: - provide a domain agnostic, formal and actionable definition of provenance [↩](#fnref:1) - enable sharing of provenance information between systems, an issue of interoperability - support tool development and implementation - enable validation of provenance messages.The work was well-received and several workshops and working groups refined the specification which resulting in a specification being submitted to the World Wide Web Consortium. The following sections provides further insights into these efforts.\n2. This definition is taken from the W3C Provenance Data Model specifications [↩](#fnref:2)\n3. The PROV-O Provenance Ontology is a W3C-vetted specification of the Provenance Data Model as an OWL ontology. The namespace for PROV-O is [http://www.w3.org/ns/prov#](http://www.w3.org/ns/prov). It is meant to allow expressing provenance information as modeled in the provenance model [W3C PROV-DM](https://www.w3.org/TR/prov-overview/) with Classes, Properties and relations defined in the W3C Ontology Web Language (OWL). Instances can therefore be represented in RDF and distributed in any of the official serialization, e.g. JSON-LD, RDF/XML, Turtle. Below is an example of provenance information represented using the PROV-O ontology and serialized as RDF statements using turtle representation. ``` @prefix xsd: . @prefix foaf: . @prefix prov: . @prefix : . :bar_chart a prov:Entity; prov:wasGeneratedBy :illustrationActivity; prov:wasDerivedFrom :aggregatedByRegions; prov:wasAttributedTo :derek; . :derek a foaf:Person, prov:Agent; foaf:givenName \"Derek\"; foaf:mbox ; prov:actedOnBehalfOf :natonal_newspaper_inc; . :national_newspaper_inc a foaf:Organization, prov:Agent; foaf:name \"National Newspaper, Inc.\"; . :illustrationActivity a prov:Activity; prov:used :aggregatedByRegions; prov:wasAssociatedWith :derek; prov:wasInformedBy :aggregationActivity; . :aggregatedByRegions a prov:Entity; prov:wasGeneratedBy :aggregationActivity; prov:wasAttributedTo :derek; . :aggregationActivity a prov:Activity; prov:startedAtTime \"2011-07-14T01:01:01Z\"^^xsd:dateTime; prov:wasAssociatedWith :derek; prov:used :crimeData; prov:used :nationalRegionsList; prov:endedAtTime \"2011-07-14T02:02:02Z\"^^xsd:dateTime; . :crimeData a prov:Entity; prov:wasAttributedTo :government; . :government a foaf:Organization, prov:Agent . :nationalRegionsList a prov:Entity; prov:wasAttributedTo :civil_action_group; . :civil_action_group a foaf:Organization, prov:Agent . ```\n4. [CamFlow](https://camflow.org/#output_format) is a Linux Security Module (LSM) designed to capture data provenance for the purpose of system audit and aims at capture information flow. CamFlow support 2 output formats. - W3C PROV-JSON format [↩](#fnref:4) ``` \"ABAAAAAAACAe9wIAAAAAAE7aeaI+200UAAAAAAAAAAA=\": { \"cf:id\": \"194334\", \"prov:type\": \"fifo\", \"cf:boot_id\": 2725894734, \"cf:machine_id\": 340646718, \"cf:version\": 0, \"cf:date\": \"2017:01:03T16:43:30\", \"cf:jiffies\": \"4297436711\", \"cf:uid\": 1000, \"cf:gid\": 1000, \"cf:mode\": \"0x1180\", \"cf:secctx\": \"unconfined_u:unconfined_r:unconfined_t:s0-s0:c0.c1023\", \"cf:ino\": 51964, \"cf:uuid\": \"32b7218a-01a0-c7c9-17b1-666f200b8912\", \"prov:label\": \"[fifo] 0\" } ``` Example of a write edge in W3C PROV format: ``` \"QAAAAAAAQIANAAAAAAAAAE7aeaI+200UAAAAAAAAAAA=\": { \"cf:id\": \"13\", \"prov:type\": \"write\", \"cf:boot_id\": 2725894734, \"cf:machine_id\": 340646718, \"cf:date\": \"2017:01:03T16:43:30\", \"cf:jiffies\": \"4297436711\", \"prov:label\": \"write\", \"cf:allowed\": \"true\", \"prov:activity\": \"AQAAAAAAAEAf9wIAAAAAAE7aeaI+200UAQAAAAAAAAA=\", \"prov:entity\": \"ABAAAAAAACAe9wIAAAAAAE7aeaI+200UAQAAAAAAAAA=\", \"cf:offset\": \"0\" } ``` Note CamFlow also concerns itself with a informatics system audit and as obvious from its design, is meanly focused on the security of Linux based systems. The CamFlow framework is highly configurable and allows `profiles` to be defined. This is a very low level solution and its use remains the confines to information security specialists. While this tool is probably of limited use to Life Sciences and bioinformatics applications, we mention it for two reasons: - it provides one of the first example of an implementation (even if very basic) making use of the W3C Prov-O model. - it provides an insight on how computational tool can deal with provenance information in ways which allow assessing systems health from a security point of view.\n5. It is those features which have been the focus of an extension as part of the work on computational biology workflows with CWLProv, and which we will now cover.[↩](#fnref:5)\n6. For the purpose of this recipe, which is to show how provenance information can be generated by a tool such as cwltool, users will need to make sure that a workflow is available before performing this conversion.[↩](#fnref:6) ``` cwltool --print-rdf --rdf-serializer=turtle mywf.cwl ```\n7. This tool, also an output from the Common Workflow Language consortium, is solely intended as a validator for provenance information when available from Research Objects. It is a standalone python package, which provides a command line interface (CLI) to read, inspect research objects capturing workflow execution information using the CWL syntax. To install the package, simply run the standard python install package pip: ``` pip install cwlprov ``` To run ‘cwlprov’ following installation and using an exemplar CWL file, run the following command:[↩](#fnref:7) ``` cwlprov --quiet --directory ./test/1.cwl validate ```\n8. Note Transparency does not equate open. Some blockchains are public but others are private, for instance to support domain specific applications ranging from financial services, supply chain or other sensitive area such as healthcare information.[↩](#fnref:8) - immutability: this is the last tenet of DLT and refers to the fact that once an entry has been to the distributed ledger, it is digitally signed and synchronized in the network by adding a new element (the block) to the blockchain. Each of the new is digitally signed via some cryptographic algorithm (e.g. Blake2). Any attempt to modify a particular block would result in changing its signature. This can be done but the cost could be prohibitively high as it would entail modifying all subsequent blocks in the chain. This architecture ensures the stability or immutability of the ledger.\n9. Important This notion of immutability assumes that cryptographic hashes using to digital proof the contracts can not be broken. The most advanced algorithms somehow guarantee this given the current compute power available. However, it should not be taken for granted. A situation where cryptographic methods would be breached by disruptive technology such as breakthrough in quantum computing, are referred to as a `cryptographic armageddon` as it would wreak havoc on the entire edifice by allowing to rewrite a ledger, thus voiding trust in an instant. Despite such alarmist claims, quantum computing methods could make attempts to tamper with a ledger impossible, thus reinforcing the approach.[↩](#fnref:9)"},"author":{"name":"fairplus.github.io","bio":"An online, open and live resource for the Life Sciences with recipes that help you to make and keep data Findable, Accessible, Interoperable and Reusable; in one word FAIR."},"metadata":{"timestamp":"2026-08-20T08:39:05.280Z"},"media":[{"url":"https://faircookbook.elixir-europe.org/_static/images/homepage.png","type":"image"}],"aiComments":[]},{"id":"web-rscvnm","shareId":"pt15hu07wD","platform":"web","url":"https://rudof-project.github.io/tutorials/intro.html","title":"Shaping Knowledge Graphs — Shaping Knowledge Graphs","shareMode":"full","createdAt":1787215074691,"postedAt":"2026-08-20T08:37:49.853Z","publishedDate":"2026-08-20T08:37:49.853Z","archivedAt":"2026-08-20T08:37:51.800Z","archivedDate":"2026-08-20T08:37:51.800Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/pt15hu07wD","contentType":"article","content":{"text":"## Shaping Knowledge Graphs\n\nThis is a Jupyter book that introduces Knowledge Graphs concepts using [rudof](https://rudof-project.github.io/rudof/)\n\n- [Short introduction to Rudof](https://rudof-project.github.io/tutorials/rudof.html)\n- [RDF](https://rudof-project.github.io/tutorials/rdf.html)\n- [SPARQL](https://rudof-project.github.io/tutorials/sparql.html)\n- [ShEx](https://rudof-project.github.io/tutorials/shex.html)\n- [SHACL](https://rudof-project.github.io/tutorials/shacl.html)\n- [Introduction to DCTAP](https://rudof-project.github.io/tutorials/dctap.html)\n- [RDF 1.2](https://rudof-project.github.io/tutorials/rdf12.html)\n- [SPARQL 1.2](https://rudof-project.github.io/tutorials/sparql12.html)\n- [Using rudof to compare schemas](https://rudof-project.github.io/tutorials/compare.html)\n- [Service descriptions](https://rudof-project.github.io/tutorials/service_description.html)\n- [Generating RDF Data from shapes](https://rudof-project.github.io/tutorials/rudof_generate.html)"},"author":{"name":"rudof-project.github.io"},"metadata":{"timestamp":"2026-08-20T08:37:49.853Z"},"media":[],"aiComments":[]},{"id":"web-hgn3z4","shareId":"mTLeZpQkLb","platform":"web","url":"https://github.com/rudof-project/tutorials","title":"rudof-project/tutorials: Tutorials using rudof","shareMode":"full","createdAt":1787215071513,"postedAt":"2026-08-20T08:37:44.459Z","publishedDate":"2026-08-20T08:37:44.459Z","archivedAt":"2026-08-20T08:37:46.733Z","archivedDate":"2026-08-20T08:37:46.733Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/mTLeZpQkLb","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/pW4HQD0ybK/media/0.png","contentType":"article","content":{"text":"## rudof tutorials\n\nThis repository contains the source code of some [Jupiter books](https://rudof-project.github.io/tutorials/intro.html) that can be used as small tutorials of [rudof](https://rudof-project.github.io/).\n\nSome links:\n\n- [Jupiter-books reference](https://jupyterbook.org/en/stable/start/overview.html)\n\n## 🚀 Quick Start\n\n\n\n### 1. Clone and install\n\n\n\n```\ngit clone https://github.com/rudof-project/tutorials.git\ncd tutorials\npip install -r requirements.txt\n```\n\n\n\n### 2. Build the book\n\n\n\n```\njupyter-book build rudof\n```\n\n\n\n### 3. Manually publish books on gh-pages\n\nNote, this is no longer necessary because we publish the book through github Actions.\n\n\n\n```\nghp-import -n -p -f rudof/_build/html\n```\n\n\n\n### Cleaning build files and cache\n\nSometimes it is necessary to clean the cache when there are new versions of the libraries. To clean the built drectory use:\n\n\n\n```\njupyter-book clean rudof\n```\n\nIf you want to clean also the `jupyter_cache`, use:\n\n\n\n```\njupyter-book clean rudof --all\n```"},"author":{"name":"rudof-project","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/5fe11ee95321d314/avatar-6a9577cd4f7f.svg","bio":"Tutorials using rudof. Contribute to rudof-project/tutorials development by creating an account on GitHub."},"metadata":{"timestamp":"2026-08-20T08:37:44.459Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/pW4HQD0ybK/media/0.png","type":"image"}],"aiComments":[]},{"id":"web-85bz9q","shareId":"PQ1IpALFJ0","platform":"web","url":"https://github.com/labra/HTML2Doc","title":"labra/HTML2Doc: HTML -> Doc converter","shareMode":"full","createdAt":1787214930521,"postedAt":"2026-08-20T08:35:24.082Z","publishedDate":"2026-08-20T08:35:24.082Z","archivedAt":"2026-08-20T08:35:26.713Z","archivedDate":"2026-08-20T08:35:26.713Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/PQ1IpALFJ0","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/lhpCpZZyz2/media/0.png","contentType":"article","content":{"text":"[Branches](https://github.com/labra/HTML2Doc/branches) [Tags](https://github.com/labra/HTML2Doc/tags)\n\n[15 Commits](https://github.com/labra/HTML2Doc/commits/main/)\n\n| Name | Name | Last commit message | Last commit date |\n| --- | --- | --- | --- |\n| example | example |\n| ieee | ieee |\n| shex | shex |\n| utils | utils |\n| .gitignore | .gitignore |\n| LICENSE | LICENSE |\n| README.md | README.md |\n| index-dump.html | index-dump.html |\n| View all files |\n\n## HTML -> Doc converter\n\nThis repo contains some examples and attempts to convert HTML documents to Word documents.\n\nThe main use case is to convert ShEx spec files written in HTML with ReSpec to IEEE Word files.\n\nWe have a dedicated folder for that in `./shex` folder.\n\nWorkflow slides: [https://docs.google.com/presentation/d/1jYvYnM9rn5F_13q88JOHVqggE5l-gRPVMIy8h8sRxwI/edit?usp=sharing](https://docs.google.com/presentation/d/1jYvYnM9rn5F_13q88JOHVqggE5l-gRPVMIy8h8sRxwI/edit?usp=sharing)"},"author":{"name":"labra","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/63048d331b1be938/avatar-6a9577cd4f7f.svg","bio":"HTML -> Doc converter. Contribute to labra/HTML2Doc development by creating an account on GitHub."},"metadata":{"timestamp":"2026-08-20T08:35:24.082Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/lhpCpZZyz2/media/0.png","type":"image"}],"aiComments":[]},{"id":"web-7n0okd","shareId":"BLMIRfSYy6","platform":"web","url":"https://github.com/rudof-project/rudof","title":"rudof-project/rudof: RDF data shapes implementation in Rust","shareMode":"full","createdAt":1787214880325,"postedAt":"2026-08-20T08:34:28.254Z","publishedDate":"2026-08-20T08:34:28.254Z","archivedAt":"2026-08-20T08:34:30.277Z","archivedDate":"2026-08-20T08:34:30.277Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/BLMIRfSYy6","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/BUIoNWgCM9/media/0.png","contentType":"article","content":{"text":"## rudof\n\n[![Latest Version](https://camo.githubusercontent.com/7113f2c603d987f480719e69e8fff714efe9f6678e16f460fdbdec8364e44525/68747470733a2f2f696d672e736869656c64732e696f2f6372617465732f762f7275646f662d636c692e737667)](https://crates.io/crates/rudof-cli) [![PyPI](https://camo.githubusercontent.com/a9835d7108de1a2a9541fbf9064f650812220df8bb1b4b73a079e9e12d7bbb6d/68747470733a2f2f696d672e736869656c64732e696f2f707970692f762f70797275646f66)](https://pypi.org/project/pyrudof/) https://github.com/rudof-project/rudof/actions/workflows/ci.yml [![dependency status](https://camo.githubusercontent.com/0e60d601d02beaf64ae36ff92ee1c45a0f2f3dd03678b7a5a03037b61345a038/68747470733a2f2f646570732e72732f7265706f2f6769746875622f7275646f662d70726f6a6563742f7275646f662f7374617475732e737667)](https://deps.rs/repo/github/rudof-project/rudof) [![CodeScene general](https://camo.githubusercontent.com/a19c43e65bf431a63e0f0ba73310c57bbc067e30f1af0492ce21da794d681072/68747470733a2f2f636f64657363656e652e696f2f696d616765732f616e616c797a65642d62792d636f64657363656e652d62616467652e737667)](https://codescene.io/projects/72637) [![pre-commit](https://camo.githubusercontent.com/f0a86ea5e994668cd6abf01bc5acfe5b602e4d5e8fd3fcb123446a74e2bc49de/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f7072652d2d636f6d6d69742d656e61626c65642d627269676874677265656e3f6c6f676f3d7072652d636f6d6d6974)](https://github.com/pre-commit/pre-commit)\n\nThis repo contains an RDF and Knowledge Graphs processing tool implemented in Rust.\n\nThe implementation supports RDF and property graphs data, as well as [ShEx](http://shex.io/), [SHACL](https://www.w3.org/TR/shacl/), [DCTap](https://www.dublincore.org/specifications/dctap/), [PGSchema](https://dl.acm.org/doi/10.1145/3589778), and conversions between different RDF data modeling formalisms.\n\nThe code can be used as a Rust library but it also contains a binary called `rudof` which can be used as an RDF playground.\n\nWe provide binaries for Linux, Windows, Mac and Docker (see [releases](https://github.com/rudof-project/rudof/releases)), as well as Python bindings.\n\n\n\n## Features\n\n`rudof` currently supports the following:\n\n- RDF and RDF 1.2 parsing, conversion and visualization.\n- SPARQL querying to RDF data and endpoints\n- Parsing SPARQL service description\n- ShEx\n- SHACL\n- DCTAP\n- Property graphs and Schemas for Property Graphs ([PGSchema](https://github.com/rudof-project/rudof/blob/master) [https://dl.acm.org/doi/10.1145/3589778](https://dl.acm.org/doi/10.1145/3589778)) Future features we are planning to add:\n\n- rdf-config\n- LinkML\n\n## Installation\n\n\n\n### Official releases\n\nYou can download a binary from the [latest release](https://github.com/rudof-project/rudof/releases/latest) page. There you will also find the compiled packages for the installation on your system using a package manager.\n\n\n\n#### Published Debian packages\n\nrudof is available as a [Debian package](https://packages.debian.org/source/sid/rudof) for Debian-based distributions (like Ubuntu).\n\nIt is also possible to download the binary from [https://github.com/rudof-project/rudof/releases](https://github.com/rudof-project/rudof/releases) and install the `.deb` package running the following commands after replacing X.X.X by the latest version:\n\n\n\n```\nwget https://github.com/rudof-project/rudof/releases/download/vX.X.X/rudof_vX.X.X_amd64.deb\nsudo dpkg -i rudof_vX.X.X_amd64.deb\n```\n\n\n\n#### Windows\n\nThe binary can be downloaded from [https://github.com/rudof-project/rudof/releases](https://github.com/rudof-project/rudof/releases).\n\n\n\n#### Mac\n\nThe binary is available at: [https://github.com/rudof-project/rudof/releases](https://github.com/rudof-project/rudof/releases) so you can download the corresponding binary to your machine.\n\nThe usual way to run/install a binary in Mac is to download it in a folder, add that folder to your PATH and activating the binary using:\n\n\n\n```\nchmod +x\n```\n\nAfter that, the processor may complain the first time about security and you have to agree to use it. Once you agree, it should work.\n\nCompiling from source\n\n### Compiling from source\n\n`rudof` has been implemented in Rust and is compiled using [cargo](https://doc.rust-lang.org/cargo/). The command `cargo run` can be used to compile and run locally the code.\n\nFor example:\n\n\n\n```\ncargo run -- validate examples/user.ttl --schema examples/user.shex --shapemap examples/user.sm\n```\n\n\n\n#### Troubleshooting\n\nIf the example doesn’t work as expected, here are a few things you can try:\n\n- **Use the --release flag** to compile in release mode, which can resolve some build issues and improve performance:\n\n```\ncargo run --release -- validate examples/user.ttl --schema examples/user.shex --shapemap examples/user.sm\n```\n\n- **Run the command inside WSL** (Windows Subsystem for Linux). If you're using Windows, compiling the project in WSL can help resolve environment-related issues, as Rust tends to compile more reliably and efficiently in Linux-based systems.\n\n### Compiling from source and installing the binary (Debian)\n\nInstall `cargo deb` (only the first time)\n\n\n\n```\ncargo install cargo-deb\n```\n\nCreate the `.deb` package by:\n\n\n\n```\ncargo deb\n```\n\nAnd run:\n\n\n\n```\nsudo dpkg -i target/debian/rudof__amd64.deb\n```\n\n\n\n### Alternative for Linux\n\nTo create a binary for Linux with debug information:\n\n\n\n```\ncargo build --target x86_64-unknown-linux-gnu\n```\n\nThe binary will be created in: `target/x86_64-unknown-linux-gnu/debug/rudof`\n\nIf you want a release binary which is more optimized, you can run:\n\n\n\n```\ncargo build --target x86_64-unknown-linux-gnu\n```\n\nIn this case, the binary will be `target/x86_64-unknown-linux-gnu/release/rudof`\n\n\n\n## Docker\n\nThe library is also published as a Docker image (`angelip2303/rudof:latest`).\n\n\n\n## Usage\n\n\n\n### Some examples\n\nThe folder `examples` contains several example files with ShEx schemas and RDF data.\n\n\n\n### Validate a simple RDF file with a ShEx schema using a ShapeMap\n\n\n\n```\nrudof validate examples/user.ttl --schema examples/user.shex --shapemap examples/user.sm\n```\n\nWe maintain a Wiki page with some common [Usage scenarios and How-to guides](https://github.com/rudof-project/rudof/wiki/Howto-guides).\n\n\n\n### Debugging information\n\nIt is possible to change the debug level information with:\n\n\n\n```\nexport RUST_LOG=info\n```\n\nwhere `value` can be `info`, `debug` or `trace` to show more information. It is also possible to have more control about the logs using more complex filters. For example, to show `trace` for the elements in crate `shacl_validation`, and supress any logs for crates `hyper` and `reqwest` (which can be quite verbose with traces), you can use:\n\n\n\n```\nexport RUST_LOG=info,shacl_validation=trace,hyper=off,reqwest=off\n```\n\nIn case you use nu_shell, you can use:\n\n\n\n```\n$env.RUST_LOG = 'info,shacl_validation=trace,hyper=off,reqwest=off'\n```\n\n\n\n## Command line usage\n\n\n\n```\nRDF and Knowledge Graphs processing tool\n\nUsage: rudof [OPTIONS] [COMMAND]\n\nCommands:\nmcp Export rudof as an MCP server\nshapemap Show information about ShEx ShapeMaps\nshex Show information about ShEx schemas\npgschema Show information about Property Graph Schemas\nvalidate Validate RDF data using ShEx or SHACL\nshex-validate Validate RDF using ShEx schemas\nshacl-validate Validate RDF data using SHACL shapes\ndata Show information about RDF data\nnode Show information about a node in an RDF Graph\nshacl Show information about SHACL shapes\ndctap Arguments for the `dctap` command\nconvert Arguments for the `convert` command\ncompare Compare two shapes (which can be in different formats)\nrdf-config Show information about rdf config\nservice Show information about SPARQL service\nquery Run SPARQL queries\ngenerate Generate synthetic RDF data from ShEx or SHACL schemas\nmaterialize Materialize an RDF graph from a ShEx schema and Map semantic-action state\npgschema-validate Validate Property Graph data using PGSchema\ncompletion Generates a shell completion script for the specified shell\nconfig Dump the effective configuration rudof is using as TOML\nhelp Print this message or the help of the given subcommand(s)\n\nOptions:\n-d, --debug... Increase logging verbosity\n-h, --help Print help\n-V, --version Print version\n```\n\nYou can see the [manual](https://rudof-project.github.io/rudof/)\n\n\n\n## Main modules\n\nThe repo is divided in the following modules:\n\n- [rudof_iri](https://github.com/rudof-project/rudof/tree/master/rudof_iri) defines simple IRIs.\n- [srdf](https://github.com/rudof-project/rudof/tree/master/srdf) simple RDF model which will be used for validation.\n- [prefixmap](https://github.com/rudof-project/rudof/tree/master/prefixmap) Prefix maps implementation.\n- [shapemap](https://github.com/rudof-project/rudof/tree/master/shapemap) ShapeMap implementation.\n- [shex_ast](https://github.com/rudof-project/rudof/tree/master/shex_ast) defines the ShEx Abstract syntax\n- [shex_compact](https://github.com/rudof-project/rudof/tree/master/shex_compact) contains the code required to handle ShEx compact syntax.\n- [shex_validation](https://github.com/rudof-project/rudof/tree/master/shex_validation) contains the code required to validate RDF using ShEx.\n- [shex_testsuite](https://github.com/rudof-project/rudof/tree/master/shex_testsuite) contains the code required to run the ShEx testsuite.\n- [shacl_ast](https://github.com/rudof-project/rudof/tree/master/shacl_ast) defines the SHACL core Abstract syntax.\n- [shacl_validation](https://github.com/rudof-project/rudof/tree/master/shacl_validation) contains the code required to validate RDF using SHACL.\n- [dctap](https://github.com/rudof-project/rudof/tree/master/dctap) contains the code required to do handle DCTAP files.\n- [shapes_converter](https://github.com/rudof-project/rudof/tree/master/shapes_converter) contains the code required to do conversion between different shapes formalisms.\n\n## Publishing the crates\n\n\n\n```\ncargo workspaces publish\n```\n\n\n\n## Worskpaces\n\nThe project is using cargo workspaces wihch can be installed with:\n\n\n\n```\ncargo install cargo-workspaces\n```\n\n\n\n## Unit-testing\n\nIn order to test all the sub-projects\n\n\n\n```\ncargo test --all\n```\n\nTesting one specific subproject:\n\n\n\n```\ncargo test -p shex_validation\n```\n\n\n\n## Using the ShEx test-suite\n\nThe ShEx testsuite is included in a git submodule. In order to obtain it, it is necessary to do:\n\n\n\n```\ngit submodule update --init --recursive\ncargo run -p shex_testsuite\n```\n\n\n\n```\nUsage: shex_testsuite [OPTIONS]\n\nOptions:\n-m, --manifest\nName of Manifest file [default: shex_testsuite/shexTest/validation/manifest.jsonld]\n-c, --config\n[default: shex_testsuite/config.toml]\n-x, --run_mode\n[default: collect-errors] [possible values: collect-errors, fail-first-error]\n-f, --manifest_mode\n[possible values: schemas, validation, negative-syntax, negative-structure]\n-p, --print_result_mode\n[default: basic] [possible values: basic, failed, passed, not-implemented, all]\n-e, --entry\n\n-t, --trait\n\n-h, --help\nPrint help\n-V, --version\nPrint version\n```\n\n\n\n### Validation conformance tests for ShEx\n\n\n\n```\ncargo run -p shex_testsuite -- -m shex_testsuite/shexTest/validation/manifest.jsonld\n```\n\nIf you want to see the failed tests, you can run:\n\n\n\n```\ncargo run -p shex_testsuite -- -m shex_testsuite/shexTest/validation/manifest.jsonld -p failed\n```\n\n\n\n### Schemas tests\n\n\n\n```\ncargo run -p shex_testsuite -- -m shex_testsuite/shexTest/schemas/manifest.jsonld -f schemas -p failed\n```\n\n\n\n## Benchmarks\n\nPerformance benchmarks live in [`benchmarks/`](https://github.com/rudof-project/rudof/blob/master/benchmarks). They are not published to crates.io and are not executed in CI. Run them locally with Criterion.\n\n\n\n## License\n\nLicensed under either of\n\n- Apache License, Version 2.0 ([LICENSE-APACHE](https://github.com/rudof-project/rudof/blob/master/LICENSE-APACHE) or [http://www.apache.org/licenses/LICENSE-2.0](http://www.apache.org/licenses/LICENSE-2.0))\n- MIT license ([LICENSE-MIT](https://github.com/rudof-project/rudof/blob/master/LICENSE-MIT) or [http://opensource.org/licenses/MIT](http://opensource.org/licenses/MIT)) at your option.\n\n\n\n## Contributors\n\n\n\n### Contribution\n\nUnless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.\n\n\n\n### Local development\n\n[Precommit](https://pre-commit.com/) has been configured to run formatters and linters before each commit. It is recommended to use it to ensure that the code is formatted and linted correctly before pushing it to the repository.\n\nIn order to install it, you can run:\n\n\n\n```\n# Installs pre-commit it self\npip install pre-commit\n\n# Installs the pre-commit hooks defined in .pre-commit-config.yaml\npre-commit install\n```\n\n\n\n#### Nix\n\nIf you have [Nix](https://nixos.org/download) with flakes enabled, the repository provides a ready-to-use development shell that includes all required dependencies.\n\nSimply run the following command from the root of the repository:\n\n\n\n```\nnix develop\n```\n\nThis drops you into a shell with everything pre-configured. No manual installation of Rust, `cargo`, or any other tool is needed.\n\nYou can also run a one-off command without entering the shell interactively:\n\n\n\n```\nnix develop --command cargo test\n```\n\n\n\n> If you use [direnv](https://direnv.net/), add a `.envrc` file with `use flake` to activate the development environment automatically whenever you `cd` into the repository: ``` echo \"use flake\" > .envrc && direnv allow ```"},"author":{"name":"rudof-project","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/2572e38168c2a7bc/avatar-6a9577cd4f7f.svg","bio":"RDF data shapes implementation in Rust . Contribute to rudof-project/rudof development by creating an account on GitHub."},"metadata":{"timestamp":"2026-08-20T08:34:28.254Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/BUIoNWgCM9/media/0.png","type":"image"}],"aiComments":[]},{"id":"web-hrcnay","shareId":"MWI8htgnaL","platform":"web","url":"https://github.com/Arquisoft/Arquisoft.github.io","title":"Arquisoft/Arquisoft.github.io: Web page of the course","shareMode":"full","createdAt":1787214880266,"postedAt":"2026-08-20T08:34:30.453Z","publishedDate":"2026-08-20T08:34:30.453Z","archivedAt":"2026-08-20T08:34:33.321Z","archivedDate":"2026-08-20T08:34:33.321Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/MWI8htgnaL","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/GVfIxT8MUD/media/0.png","contentType":"article","content":{"text":"[Branches](https://github.com/Arquisoft/Arquisoft.github.io/branches) [Tags](https://github.com/Arquisoft/Arquisoft.github.io/tags)\n\n[1,465 Commits](https://github.com/Arquisoft/Arquisoft.github.io/commits/master/)\n\n| Name | Name | Last commit message | Last commit date |\n| --- | --- | --- | --- |\n| course2021 | course2021 |\n| course2122 | course2122 |\n| course2223 | course2223 |\n| course2324 | course2324 |\n| course2425/seminars | course2425/seminars |\n| course2526/seminars | course2526/seminars |\n| mindMapFiles | mindMapFiles |\n| slides | slides |\n| styles | styles |\n| .gitignore | .gitignore |\n| ISO25010.html | ISO25010.html |\n| README.md | README.md |\n| course1819.html | course1819.html |\n| course1920.html | course1920.html |\n| course2021.html | course2021.html |\n| course2122.html | course2122.html |\n| course2223.html | course2223.html |\n| course2324.html | course2324.html |\n| course2425.html | course2425.html |\n| course2526.html | course2526.html |\n| debug.log | debug.log |\n| index.html | index.html |\n| View all files |\n\n## Arquisoft.github.io\n\nWeb page of the [Software architecture course](http://arquisoft.github.io/)."},"author":{"name":"Arquisoft","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/e96a0922db6dc676/avatar-6a9577cd4f7f.svg","bio":"Web page of the course. Contribute to Arquisoft/Arquisoft.github.io development by creating an account on GitHub."},"metadata":{"timestamp":"2026-08-20T08:34:30.453Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/GVfIxT8MUD/media/0.png","type":"image","width":1200,"height":600}],"aiComments":[]},{"id":"web-ycuczj","shareId":"bjxPiuWerE","platform":"web","url":"http://labra.weso.es/","title":"Labra's home page","shareMode":"full","createdAt":1787214861383,"postedAt":"2019-11-14T18:37:00.000Z","publishedDate":"2019-11-14T18:37:00.000Z","archivedAt":"2026-08-20T08:34:17.562Z","archivedDate":"2026-08-20T08:34:17.562Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/bjxPiuWerE","contentType":"article","content":{"text":"## Biography\n\nFull Professor (Catedrático), [University of Oviedo](http://uniovi.es/), Spain. Founder and main researcher of [WESO (Web Semantics Oviedo)](http://www.weso.es/) research group, which collaborates with different companies around the world applying semantic web technologies to solve practical problems.\n\nMember of [Data Shapes](https://www.w3.org/2014/data-shapes/wiki/Main_Page) W3C Working Groups and of [Shape Expressions](https://www.w3.org/community/shex/), [SHACL](https://www.w3.org/community/shacl/), [RAX (RDF and XML interoperability)](https://www.w3.org/community/rax/) and [Best practices of Multilingual Linked Open Data](https://www.w3.org/community/bpmlod/) W3C community groups.\n\nPreviously, coordinator of the [Master in Web Engineering](http://miw.uniovi.es/) - University of Oviedo (2016-2017), and Dean of the [School of Computer Science Engineering](http://ingenieriainformatica.uniovi.es/) - [University of Oviedo](http://uniovi.es/) (2004-2012).\n\n### Interests\n\n- Semantic Web\n- Programming languages\n- Software Architecture\n\n### Education\n\n- PhD in Computer Science Engineering, 2001 University of Oviedo\n\n## Publications\n\nSee [All publications](http://labra.weso.es/publication/). Other lists: [DBLP](https://dblp.uni-trier.de/pers/hd/g/Gayo:Jos=eacute=_Emilio_Labra), [Google scholar](https://scholar.google.com/citations?user=TGfRNZkAAAAJ),, [Research gate](https://www.researchgate.net/profile/Jose_Labra_Gayo)\n\n- [TogoMCP: natural language querying of life-science knowledge graphs via schema-guided LLMs and the Model Context Protocol](http://labra.weso.es/publication/2026_togomcp_database/), [Akira R Kinjo](https://labra.weso.es/authors/akira-r-kinjo), [Yasunori Yamamoto](https://labra.weso.es/authors/yasunori-yamamoto), [Samuel Bustamante-Larriet](https://labra.weso.es/authors/samuel-bustamante-larriet), [Jose-Emilio Labra-Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Takatomo Fujisawa](https://labra.weso.es/authors/takatomo-fujisawa), Database - 2026\n- [rudof-MCP: A Model Context Protocol Server for Semantic Web Operations](http://labra.weso.es/publication/2026_mcp_rudof/), [Samuel Bustamante Larriet](https://labra.weso.es/authors/samuel-bustamante-larriet), [Diego Martín Fernández](https://labra.weso.es/authors/diego-mart%C3%ADn-fern%C3%A1ndez), [Álvaro García Fernández](https://labra.weso.es/authors/%C3%A1lvaro-garc%C3%ADa-fern%C3%A1ndez), [Daniel Fernández Álvarez](https://labra.weso.es/authors/daniel-fern%C3%A1ndez-%C3%A1lvarez), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), *Extended Semantic Web Conference*, ESWC26, Posters and Demos - 2026\n- [Common Foundations for Recursive Shape Languages](http://labra.weso.es/publication/2026_foundations_recursive_shapes_languages/), [Shqiponja Ahmetaj](https://labra.weso.es/authors/shqiponja-ahmetaj), [Iovka Boneva](https://labra.weso.es/authors/iovka-boneva), [Jan Hidders](https://labra.weso.es/authors/jan-hidders), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Wim Martens](https://labra.weso.es/authors/wim-martens), [Fabio Mogavero](https://labra.weso.es/authors/fabio-mogavero), [Filip Murlak](https://labra.weso.es/authors/filip-murlak), [Cem Okulmus](https://labra.weso.es/authors/cem-okulmus), [Ognjen Savković](https://labra.weso.es/authors/ognjen-savkovi%C4%87), [Mantas Šimkus](https://labra.weso.es/authors/mantas-%C5%A1imkus), [Dominik Tomaszuk](https://labra.weso.es/authors/dominik-tomaszuk), 23rd International Conference on Principles of Knowledge Representation and Reasoning - 2026\n- [sheXer: A robust and versatile library for automatic extraction of RDF shapes](http://labra.weso.es/publication/2026_shexer_software_x/), [Daniel Fernández Álvarez](https://labra.weso.es/authors/daniel-fern%C3%A1ndez-%C3%A1lvarez), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), Software X - 2026\n- [MCP server tools with RDF shapes](http://labra.weso.es/publication/2025_mcp_server_tools_rdf/), [Jose Emilio Labra-Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Yasunori Yamamoto](https://labra.weso.es/authors/yasunori-yamamoto), [Akira R. Kinjo](https://labra.weso.es/authors/akira-r.-kinjo), [Andra Waagmeester](https://labra.weso.es/authors/andra-waagmeester), [Javier Acosta](https://labra.weso.es/authors/javier-acosta), [Shuichi Kawashima](https://labra.weso.es/authors/shuichi-kawashima), [Yoko Okabeppu](https://labra.weso.es/authors/yoko-okabeppu), [Julia Koblitz](https://labra.weso.es/authors/julia-koblitz), [Samuel Bustamante Larriet](https://labra.weso.es/authors/samuel-bustamante-larriet), BioHackrXiv preprint - 2025\n- [On Property Constraints in PG-Schema](http://labra.weso.es/publication/2025_property_constraints_pg_schema/), [Dominik Tomaszuk](https://labra.weso.es/authors/dominik-tomaszuk), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), *Knowledge Capture and Knowledge Representation Conference*, KCAP25 - 2025\n- [PG-Schema with Property Constraints validator in Rudof](http://labra.weso.es/publication/2026_rudof_pgschema_pc/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Dominik Tomaszuk](https://labra.weso.es/authors/dominik-tomaszuk), [Diego Martín Fernández](https://labra.weso.es/authors/diego-mart%C3%ADn-fern%C3%A1ndez), [Samuel Bustamante Larriet](https://labra.weso.es/authors/samuel-bustamante-larriet), [Álvaro García Fernández](https://labra.weso.es/authors/%C3%A1lvaro-garc%C3%ADa-fern%C3%A1ndez), [Daniel Fernández Álvarez](https://labra.weso.es/authors/daniel-fern%C3%A1ndez-%C3%A1lvarez), *Knowledge Capture and Knowledge Representation Conference*, KCAP25, Posters and Demos - 2025\n- [xpSHACL: Explainable SHACL Validation using Retrieval-Augmented Generation and Large Language Models](http://labra.weso.es/publication/2025_xp_shacl/), [Gustavo Correa Publio](https://labra.weso.es/authors/gustavo-correa-publio), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), *LLM+Graph: 2nd International Workshop on Data Management Opportunities in Bringing LLMs with Graph Data*, VLDB25, London, 2025 - 2025\n- [Shape Expressions with Inheritance](http://labra.weso.es/publication/2025_shex_inheritance/), [Iovka Boneva](https://labra.weso.es/authors/iovka-boneva), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Eric Prud'hommeaux](https://labra.weso.es/authors/eric-prudhommeaux), [Katherine Thornton](https://labra.weso.es/authors/katherine-thornton), [Andra Waagmeester](https://labra.weso.es/authors/andra-waagmeester), *Extended Semantic Web Conference*, Portoroz, Slovenia, 2025 - 2025\n- [Common Foundations for SHACL, ShEx, and PG-Schema](http://labra.weso.es/publication/2025_common_foundations_shacl_shex_pgschema/), [Shqiponja Ahmetaj](https://labra.weso.es/authors/shqiponja-ahmetaj), [Iovka Boneva](https://labra.weso.es/authors/iovka-boneva), [Jan Hidders](https://labra.weso.es/authors/jan-hidders), [Katja Hose](https://labra.weso.es/authors/katja-hose), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Wim Martens](https://labra.weso.es/authors/wim-martens), [Fabio Mogavero](https://labra.weso.es/authors/fabio-mogavero), [Filip Murlak](https://labra.weso.es/authors/filip-murlak), [Cem Okulmus](https://labra.weso.es/authors/cem-okulmus), [Axel Polleres](https://labra.weso.es/authors/axel-polleres), [Ognjen Savković](https://labra.weso.es/authors/ognjen-savkovi%C4%87), [Mantas Šimkus](https://labra.weso.es/authors/mantas-%C5%A1imkus), [Dominik Tomaszuk](https://labra.weso.es/authors/dominik-tomaszuk), International World Wide Web Conference, Sidney, Australia, 2025 - 2025\n- [Componentizing autonomous underwater vehicles by physical-running algorithms](http://labra.weso.es/publication/2024_underwater_vehicles_peerj/), [Claudio Navarro](https://labra.weso.es/authors/claudio-navarro), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Francisco A. Escobar Jara](https://labra.weso.es/authors/francisco-a.-escobar-jara), [Carlos Cares](https://labra.weso.es/authors/carlos-cares), PeerJ Computer Science - 2024\n- [Toward Efficient Legislative Processes: Analysis of Chilean Congressional Bill Votes Using Semantic Web Technologies](http://labra.weso.es/publication/2024_towardsefficientlegislativeprocesses/), [Francisco Cifuentes Silva](https://labra.weso.es/authors/francisco-cifuentes-silva), [Hernán Astudillo](https://labra.weso.es/authors/hern%C3%A1n-astudillo), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Felipe Rivera Polo](https://labra.weso.es/authors/felipe-rivera-polo), SN Computer Science - 2024\n- [rudof: A Rust Library for handling RDF data models and Shapes](http://labra.weso.es/publication/2024_rudof_demo/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Ángel Iglesias Préstamo](https://labra.weso.es/authors/%C3%A1ngel-iglesias-pr%C3%A9stamo), [Diego Martín Fernández](https://labra.weso.es/authors/diego-mart%C3%ADn-fern%C3%A1ndez), [Marc-Antoine Arnaud](https://labra.weso.es/authors/marc-antoine-arnaud), *International Semantic Web Conference*, ISWC24, Posters and Demos - 2024\n- [Extending Shape Expressions for different types of knowledge graphs](http://labra.weso.es/publication/2024_shex_extensions/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), In 1st Workshop on *Data Quality meets Machine Learning and Knowledge Graphs*, DQMLKG, part of *Extended Semantic Web Conference 2024*, ESWC24. - 2024\n- [Introduction to ShEx and ShEx and SHACL Compared](http://labra.weso.es/publication/2024_dagsthulseminar/), [Shqiponja Ahmetaj](https://labra.weso.es/authors/shqiponja-ahmetaj), [Slawomir Staworko](https://labra.weso.es/authors/slawomir-staworko), [Jan Van den Bussche](https://labra.weso.es/authors/jan-van-den-bussche), [Maxime Jakubowsk](https://labra.weso.es/authors/maxime-jakubowsk), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), In *Dagstuhl Reports, Volume 14, Issue 3*, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) - 2024\n- [Extracting shapes from large RDF data collections](http://labra.weso.es/publication/2024_extracting_shapes_consolidator-copy/), [Daniel Fernández Álvarez](https://labra.weso.es/authors/daniel-fern%C3%A1ndez-%C3%A1lvarez), [Yasunori Yamamoto](https://labra.weso.es/authors/yasunori-yamamoto), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Andra Waagmeester](https://labra.weso.es/authors/andra-waagmeester), In *Semantic Web Applications and Tools for Health Care and Life Sciences*, SWAT4HCLS. - 2024\n- [Extracting shapes from large RDF data collections](http://labra.weso.es/publication/2024_extracting_shapes_consolidator/), [Daniel Fernández Álvarez](https://labra.weso.es/authors/daniel-fern%C3%A1ndez-%C3%A1lvarez), [Yasunori Yamamoto](https://labra.weso.es/authors/yasunori-yamamoto), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Andra Waagmeester](https://labra.weso.es/authors/andra-waagmeester), In *Semantic Web Applications and Tools for Health Care and Life Sciences*, SWAT4HCLS. - 2024\n- [Using Polarization and Alignment to Identify Quick-Approval Law Propositions: An Open Linked Data Application](http://labra.weso.es/publication/2023_polarization_icai/), [Francisco Cifuentes Silva](https://labra.weso.es/authors/francisco-cifuentes-silva), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Hernán Astudillo](https://labra.weso.es/authors/hern%C3%A1n-astudillo), [Felipe Rivera Polo](https://labra.weso.es/authors/felipe-rivera-polo), In *International Conference on Applied Informatics*, ICAI 2023. - 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2015\n- [Validating and Describing Linked Data Portals using RDF Shape Expressions](http://labra.weso.es/publication/2015_validatinglinkeddataportals/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Eric Prud'hommeaux](https://labra.weso.es/authors/eric-prudhommeaux), [Harold Solbrig](https://labra.weso.es/authors/harold-solbrig), [Jose María Álvarez Rodríguez](https://labra.weso.es/authors/jose-mar%C3%ADa-%C3%A1lvarez-rodr%C3%ADguez), In *1st Workshop on Linked Data Quality*, Brussels, Belgique - 2015\n- [Multilingual linked data patterns](http://labra.weso.es/publication/2015_mlodpatterns/) , [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Dimitris Kontokostas](https://labra.weso.es/authors/dimitris-kontokostas), [Sören Auer](https://labra.weso.es/authors/s%C3%B6ren-auer), Semantic Web Journal - 2015\n- [Representing Statistical Indexes as Linked Data Including Metadata about Their Computation Process](http://labra.weso.es/publication/2014_representingstatisticalindexes/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Hania Farham](https://labra.weso.es/authors/hania-farham), [Juan Castro Fernández](https://labra.weso.es/authors/juan-castro-fern%C3%A1ndez), [Jose María Álvarez Rodríguez](https://labra.weso.es/authors/jose-mar%C3%ADa-%C3%A1lvarez-rodr%C3%ADguez), Metadata and Semantics Research - 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2014\n- [Shape Expressions: An RDF validation and transformation language](http://labra.weso.es/publication/2014_shex/), [Eric Prud'hommeaux](https://labra.weso.es/authors/eric-prudhommeaux), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Harold Solbrig](https://labra.weso.es/authors/harold-solbrig), In [10th International Conference on Semantic Systems](http://2014.semantics.cc/www.semantics.cc/index.html), Leipzig, Germany - 2014\n- [New trends on e-Procurement applying semantic technologies](http://labra.weso.es/publication/2014_newtrendseprocurement/), [Jose María Álvarez Rodríguez](https://labra.weso.es/authors/jose-mar%C3%ADa-%C3%A1lvarez-rodr%C3%ADguez), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Patricia Ordóñez de Pablos](https://labra.weso.es/authors/patricia-ord%C3%B3%C3%B1ez-de-pablos), Computers in Industry - 2014\n- [New trends on e-Procurement applying semantic technologies: current status and future challenges](http://labra.weso.es/publication/2014_newtrendseprocurementstatus/), [Jose María Álvarez Rodríguez](https://labra.weso.es/authors/jose-mar%C3%ADa-%C3%A1lvarez-rodr%C3%ADguez), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Patricia Ordóñez de Pablos](https://labra.weso.es/authors/patricia-ord%C3%B3%C3%B1ez-de-pablos), Computers in Industry - 2014\n- [ACOTA: A multilingual and Semi-automatic collaborative tagging system](http://labra.weso.es/publication/2014_acota/), [César Luis Alvargonzález](https://labra.weso.es/authors/c%C3%A9sar-luis-alvargonz%C3%A1lez), [Jose María Álvarez Rodríguez](https://labra.weso.es/authors/jose-mar%C3%ADa-%C3%A1lvarez-rodr%C3%ADguez), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Patricia Ordóñez de Pablos](https://labra.weso.es/authors/patricia-ord%C3%B3%C3%B1ez-de-pablos), Journal of Web Engineering - 2014\n- [Inductive Representations of RDF Graphs](http://labra.weso.es/publication/2013_inductivetriplegraphs/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Johan Jeuring](https://labra.weso.es/authors/johan-jeuring), [Jose María Álvarez Rodríguez](https://labra.weso.es/authors/jose-mar%C3%ADa-%C3%A1lvarez-rodr%C3%ADguez), Science of Computer Programming - 2013\n- [Towards a Stepwise Method for Unifying and Reconciling Corporate Names in Public Contracts Metadata: The CORFU Technique](http://labra.weso.es/publication/2013_corfutechnique/), [Jose María Álvarez Rodríguez](https://labra.weso.es/authors/jose-mar%C3%ADa-%C3%A1lvarez-rodr%C3%ADguez), [Patricia Ordoñez de Pablos](https://labra.weso.es/authors/patricia-ordo%C3%B1ez-de-pablos), [Michail Vafopoulos](https://labra.weso.es/authors/michail-vafopoulos), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), Metadata and Semantics Research - 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Carolina Medina Ramírez](https://labra.weso.es/authors/r.-carolina-medina-ram%C3%ADrez), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [S. Masoud Sadjadi](https://labra.weso.es/authors/s.-masoud-sadjadi), IKE’13: The 12th International Conference on Information and Knowledge Engineering, Las Vegas, USA - 2013\n- [Cases on Open-Linked Data and Semantic Web Applications](http://labra.weso.es/publication/2013_caseslinkedopendata/), [Patricia Ordóñez de Pablos](https://labra.weso.es/authors/patricia-ord%C3%B3%C3%B1ez-de-pablos), [Miltiadis D. Lytras](https://labra.weso.es/authors/miltiadis-d.-lytras), [Robert D. Tennyson](https://labra.weso.es/authors/robert-d.-tennyson), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), IGI Global, ISBN: 978-1466628274 - 2013\n- [E-Procurement Management for Successful Electronic Government Systems](http://labra.weso.es/publication/2013_eprocurementmanagement/), [Patricia Ordóñez de Pablos](https://labra.weso.es/authors/patricia-ord%C3%B3%C3%B1ez-de-pablos), [Juan Manuel Cueva Lovelle](https://labra.weso.es/authors/juan-manuel-cueva-lovelle), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Robert D. Tennyson](https://labra.weso.es/authors/robert-d.-tennyson), IGI Global, ISBN: 9781466621190 - 2013\n- [Applying MapReduce to Spreading Activation Algorithm on Large RDF Graphs](http://labra.weso.es/publication/2013_mapreducespreadingactivation/), [Jorge González Lorenzo](https://labra.weso.es/authors/jorge-gonz%C3%A1lez-lorenzo), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Jose María Alvarez Rodríguez](https://labra.weso.es/authors/jose-mar%C3%ADa-alvarez-rodr%C3%ADguez), Communications in Computer and Information Science, vol 278, pp. 601-611 - 2013\n- [Automated Diagnosis through Ontologies and Logical Descriptions: The ADONIS Approach](http://labra.weso.es/publication/2013_adonisbookchapter/), [Alejandro Rodríguez González](https://labra.weso.es/authors/alejandro-rodr%C3%ADguez-gonz%C3%A1lez), [Ángel García Crespo](https://labra.weso.es/authors/%C3%A1ngel-garc%C3%ADa-crespo), [Ricardo Colomo Palacios](https://labra.weso.es/authors/ricardo-colomo-palacios), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Juan Miguel Gómez Berbis](https://labra.weso.es/authors/juan-miguel-g%C3%B3mez-berbis), [Giner Alor Hernández](https://labra.weso.es/authors/giner-alor-hern%C3%A1ndez), Engineering Effective Decision Support Technologies: New Models and Applications - 2013\n- [ONTOSPREAD: A Framework for Supporting the Activation of Concepts in Graph-Based Structures through the Spreading Activation Technique](http://labra.weso.es/publication/2013_ontospreadframework/), [Jose María Álvarez Rodríguez](https://labra.weso.es/authors/jose-mar%C3%ADa-%C3%A1lvarez-rodr%C3%ADguez), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Patricia Ordóñez de Pablos](https://labra.weso.es/authors/patricia-ord%C3%B3%C3%B1ez-de-pablos), Communications in Computer and Information Science, vol 278, pp. 454-459 - 2013\n- [Towards a Practical Solution for Data Grounding in a Semantic Web Services Environment](http://labra.weso.es/publication/2012_datagrounding/), [Miguel García Rodríguez](https://labra.weso.es/authors/miguel-garc%C3%ADa-rodr%C3%ADguez), [Jose María Alvarez Rodríguez](https://labra.weso.es/authors/jose-mar%C3%ADa-alvarez-rodr%C3%ADguez), [Diego Berrueta Muñoz](https://labra.weso.es/authors/diego-berrueta-mu%C3%B1oz), [Luis Polo Paredes](https://labra.weso.es/authors/luis-polo-paredes), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Patricia Ordoñez De Pablos](https://labra.weso.es/authors/patricia-ordo%C3%B1ez-de-pablos), Journal of Universal Computer Science - 2012\n- [Web Semántica: comprendiendo el cambio hacia la Web 3.0](http://labra.weso.es/publication/2012_websemantica/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), Pocket Innova - 2012\n- [The effects of ERP implementations on the profitability of big firms: the case of Spain](http://labra.weso.es/publication/2012_effectserp/), [Javier de Andrés](https://labra.weso.es/authors/javier-de-andr%C3%A9s), [Pedro Lorca](https://labra.weso.es/authors/pedro-lorca), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), International Journal on Technology Management, vol. 59, number 1 / 2, 2012 - 2012\n- [Towards a Pan-European E-Procurement platform to Aggregate, Publish and Search Public Procurement Notices powered by Linked Open Data: The MOLDEAS Approach](http://labra.weso.es/publication/2012_paneuropeaneprocurement/), [Jose María Álvarez Rodríguez](https://labra.weso.es/authors/jose-mar%C3%ADa-%C3%A1lvarez-rodr%C3%ADguez), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Francisco Cifuentes](https://labra.weso.es/authors/francisco-cifuentes), [Giner Hérnandez](https://labra.weso.es/authors/giner-h%C3%A9rnandez), [C. 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Guzmán Luna](https://labra.weso.es/authors/j.-a.-guzm%C3%A1n-luna), International Journal of Software Engineering and Knowledge Engineering (IJSEKE ) Spceial Issue on Consuming and Producing Linked Data on Real World Applications, vol 22, num. 3, 2012 - 2012\n- [Towards an architecture and adoption process for Linked Data technologies in Open Government contexts](http://labra.weso.es/publication/2011_linkeddatalibrarycongress/), [Francisco Cifuentes Silva](https://labra.weso.es/authors/francisco-cifuentes-silva), [Christian Sifaqui](https://labra.weso.es/authors/christian-sifaqui), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), In *I-Semantics* - 2011\n- [SeDeLo: Using Semantics and Description Logics to Support Aided Clinical Diagnosis](http://labra.weso.es/publication/2011_sedelo/), [Alejandro Rodríguez García](https://labra.weso.es/authors/alejandro-rodr%C3%ADguez-garc%C3%ADa), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Ricardo Colomo Palacio](https://labra.weso.es/authors/ricardo-colomo-palacio), [Miguel A. Mayer](https://labra.weso.es/authors/miguel-a.-mayer), [Juan Manual Gómez Berbis](https://labra.weso.es/authors/juan-manual-g%C3%B3mez-berbis), [Angel García Crespo](https://labra.weso.es/authors/angel-garc%C3%ADa-crespo), Journal of Medical Systems, vol. 36, number 4, pp: 2471-2481 - 2011\n- [Towards the evaluation of usability in educative websites](http://labra.weso.es/publication/2010_towardsevaluationusability/), [María Elena Alba Obeso](https://labra.weso.es/authors/mar%C3%ADa-elena-alba-obeso), [Ana Belén Martínez Prieto](https://labra.weso.es/authors/ana-bel%C3%A9n-mart%C3%ADnez-prieto), [María del Carmen Suárez Torrente](https://labra.weso.es/authors/mar%C3%ADa-del-carmen-su%C3%A1rez-torrente), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Juan Manuel Cueva Lovelle](https://labra.weso.es/authors/juan-manuel-cueva-lovelle), [Hernán Sagastegui Chigne](https://labra.weso.es/authors/hern%C3%A1n-sagastegui-chigne), International Journal on Technology Enhanced Learning, vol. 2 - 2010\n- [WESONet: Applying semantic web technologies and collaborative tagging to multimedia web information systems](http://labra.weso.es/publication/2009_wesonet/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Patricia Ordóñez de Pablos](https://labra.weso.es/authors/patricia-ord%C3%B3%C3%B1ez-de-pablos), [Juan Manuel Cueva Lovelle](https://labra.weso.es/authors/juan-manuel-cueva-lovelle), Computers in Human Behaviour, vol 26, pp: 205-209, 2010 - 2009\n- [A proposal for a Semantic Intelligent Document Repository Architecture](http://labra.weso.es/publication/2009_sidra-cerma/), [Alejandro Rodríguez](https://labra.weso.es/authors/alejandro-rodr%C3%ADguez), [Ricardo Colomo](https://labra.weso.es/authors/ricardo-colomo), [Juan Miguel Gómez](https://labra.weso.es/authors/juan-miguel-g%C3%B3mez), [Giner Alor-Hernandez](https://labra.weso.es/authors/giner-alor-hernandez), [Ruben Posada-Gomez](https://labra.weso.es/authors/ruben-posada-gomez), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Krishnamurthy Vidyasankar](https://labra.weso.es/authors/krishnamurthy-vidyasankar), In *Electronics, Robotics and Automotive Mechanics Conference* (CERMA 2009) - 2009\n- [Ontologies in Checking for Inconsistency of Requirements Specification](http://labra.weso.es/publication/2009_ontologiesrequirementspecifications/), [Petr Kroha](https://labra.weso.es/authors/petr-kroha), [R. Janetzko](https://labra.weso.es/authors/r.-janetzko), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), In *Third International Conference on Advances in Semantic Processing* SEMAPRO, 09 - 2009\n- [Automated Diagnosis through Ontologies and Logical Descriptions: The ADONIS Approach](http://labra.weso.es/publication/2011_adonis/), [Alejandro Rodríguez González](https://labra.weso.es/authors/alejandro-rodr%C3%ADguez-gonz%C3%A1lez), [Ángel García Crespo](https://labra.weso.es/authors/%C3%A1ngel-garc%C3%ADa-crespo), [Ricardo Colomo Palacios](https://labra.weso.es/authors/ricardo-colomo-palacios), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Juan Miguel Gómez Berbis](https://labra.weso.es/authors/juan-miguel-g%C3%B3mez-berbis), [Giner Alor Hernández](https://labra.weso.es/authors/giner-alor-hern%C3%A1ndez), International Journal of Decision Support System Technology - 2009\n- [Doing Business by selling free services](http://labra.weso.es/publication/2009_doingbusinesssellingfreeservices/), [Jose Luis Marín de la Iglesia](https://labra.weso.es/authors/jose-luis-mar%C3%ADn-de-la-iglesia), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), Web 2.0 Business Models - 2009\n- [SOAF: Semantic Indexing System Based on Collaborative Tagging](http://labra.weso.es/publication/2008_semanticindexingcollaborativetagging/), [Ana Cernea Doina](https://labra.weso.es/authors/ana-cernea-doina), [Ester del Moral](https://labra.weso.es/authors/ester-del-moral), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), In [Interdisciplinary Journal of E-Learning and Learning Objects](https://www.learntechlib.org/j/IJELLO), vol 4(1) - 2008\n- [Analysis of XBRL documents representing financial statements using Semantic Web Technologies](http://labra.weso.es/publication/2007_analysisxbrl/), [Sheila Méndez Núñez](https://labra.weso.es/authors/sheila-m%C3%A9ndez-n%C3%BA%C3%B1ez), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Javier de Andrés Suárez](https://labra.weso.es/authors/javier-de-andr%C3%A9s-su%C3%A1rez), [Patricia Ordóñez de Pablos](https://labra.weso.es/authors/patricia-ord%C3%B3%C3%B1ez-de-pablos), In [2nd International Conference on Metadata and Semantic Web Research](http://www.mtsr.ionio.gr/) - 2007\n- [Combining Collaborative Tagging and Ontologies in Image Retrieval Systems](http://labra.weso.es/publication/2007_combiningcollaborativetaggingimageretrieval/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Patricia Ordóñez de Pablos](https://labra.weso.es/authors/patricia-ord%C3%B3%C3%B1ez-de-pablos), [Juan Manuel Cueva Lovelle](https://labra.weso.es/authors/juan-manuel-cueva-lovelle), In [2nd International Conference on Metadata and Semantic Web Research](http://www.mtsr.ionio.gr/) - 2007\n- [Mailing lists meet the semantic web](http://labra.weso.es/publication/2007_mailinglistssemanticweb/), [Sergio Fernández](https://labra.weso.es/authors/sergio-fern%C3%A1ndez), [Diego Berrueta](https://labra.weso.es/authors/diego-berrueta), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), In *Workshop on Social Aspects of the Semantic Web (SAW 2007)*, Poznan, Poland - 2007\n- [Utilización de herramientas colaborativas de desarrollo de software libre en un modelo de aprendizaje basado en proyectos](http://labra.weso.es/publication/2006_herramientascolaborativas/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Daniel Fernández Lanvin](https://labra.weso.es/authors/daniel-fern%C3%A1ndez-lanvin), [Jesús Calvo Salvador](https://labra.weso.es/authors/jes%C3%BAs-calvo-salvador), [Agustín Cernuda del Río](https://labra.weso.es/authors/agust%C3%ADn-cernuda-del-r%C3%ADo), XII Jornadas de Enseñanza Universitaria de Informática (Jenui 2006), Bilbao, Spain - 2006\n- [A monadic program slicer](http://labra.weso.es/publication/2006_monadicprogramslicer/), [Yingzhou Zhang](https://labra.weso.es/authors/yingzhou-zhang), [[Jose Emilio Labra Gayo](http://di.uniovi.es/~labra)](https://labra.weso.es/authors/jose-emilio-labra-gayohttp//di.uniovi.es/~labra), [Agustín Cernuda del Río](https://labra.weso.es/authors/agust%C3%ADn-cernuda-del-r%C3%ADo), ACM SIGPLAN Notices, 41 (5), pp. 30-38 - 2006\n- [A Formal Method for program Slicing](http://labra.weso.es/publication/2005_formalmethodprogramslicing/), [Yingzhou Zhang](https://labra.weso.es/authors/yingzhou-zhang), [Baowen Xu](https://labra.weso.es/authors/baowen-xu), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), In [Australian Software Engineering Conference, ASWEC 2005](http://aswec2005.itee.uq.edu.au/home.php) - 2005\n- [Representaciones gráficas y Mundos Virtuales infinitos en las Prácticas de Programación Lógica y Funcional](http://labra.weso.es/publication/2003_graphicalrepresentationslogicfunctionalprogrammingjenui/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [IX Jornadas de Enseñanza Universitaria de Informática (Jenui 2003)](http://neptuno.uca.es/jenui2003/), Cádiz, Spain - 2004\n- [¿Hay Lógica en la situación actual de las titulaciones informáticas?](http://labra.weso.es/publication/2004_logicaspainjenui/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [X Jornadas de Enseñanza Universitaria de Informática (Jenui 2004)](http://www.eps.ua.es/jenui/), Almería, Spain - 2004\n- [Web Engineering](http://labra.weso.es/publication/2003_webengineering/), [Juan Manuel Cueva Lovelle](https://labra.weso.es/authors/juan-manuel-cueva-lovelle), [Bernardo Martín González Rodríguez](https://labra.weso.es/authors/bernardo-mart%C3%ADn-gonz%C3%A1lez-rodr%C3%ADguez), [Luis Joyanes Aguilar](https://labra.weso.es/authors/luis-joyanes-aguilar), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [María del Puerto Paule](https://labra.weso.es/authors/mar%C3%ADa-del-puerto-paule), Proceedings of the [International Conference on Web Engineering](http://www.icwe2003.org/), ICWE 2003, Oviedo, Spain, July 14-18, Lecture Notes in Computer Science, Vol. 2722 - 2003\n- [A Generic e-Learning Multiparadigm Programming Language System: IDEFIX Project](http://labra.weso.es/publication/2002_agenericelearningmultiparadigm_idefixsigcse/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Jose Manuel Morales Gil](https://labra.weso.es/authors/jose-manuel-morales-gil), [Alberto Manuel Fernández Álvarez](https://labra.weso.es/authors/alberto-manuel-fern%C3%A1ndez-%C3%A1lvarez), [Hernán Sagastegui Chigne](https://labra.weso.es/authors/hern%C3%A1n-sagastegui-chigne), In [ACM Technical Symposium on Computer Science Education](http://www.csis.gvsu.edu/sigcse2003/) (SIGCSE 2003), Reno, Nevada (USA) - 2003\n- [Specification of Logic Programming Languages from Reusable Semantic Building Blocks](http://labra.weso.es/publication/2003_specificationlogicprogramminglanguages/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [María C. Luengo Díaz](https://labra.weso.es/authors/mar%C3%ADa-c.-luengo-d%C3%ADaz), [Juan Manuel Cueva Lovelle](https://labra.weso.es/authors/juan-manuel-cueva-lovelle), [Agustín Cernuda del Río](https://labra.weso.es/authors/agust%C3%ADn-cernuda-del-r%C3%ADo), Electronic Notes on Theoretical Computer Science, vol. 64 - 2003\n- [Plataforma de enseñanza de lenguajes de programación a través de Internet: Proyecto IDEFIX](http://labra.weso.es/publication/2002_plataformaensenianzalenguajesprogramacion_idefix/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Jose Manuel Morales Gil](https://labra.weso.es/authors/jose-manuel-morales-gil), [Roberto Turrado Camblor](https://labra.weso.es/authors/roberto-turrado-camblor), In *VIII Jornadas de Enseñanza Universitaria de Informática*, Cáceres, Spain - 2002\n- [Modular development of Language Processors from Reusable Semantic Specifications](http://labra.weso.es/publication/2001_phdthesis/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), PhD thesis (in Spanish) - 2001\n- [Programación Práctica en Prolog](http://labra.weso.es/publication/1998_progpracticaprolog/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), Ed. Servitec, Num. 13, ISBN: 84-8416-612-0 - 1998\n- [Ejercicios de lógica informática](http://labra.weso.es/publication/1998_ejercicioslogica/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Ana I. Fernández](https://labra.weso.es/authors/ana-i.-fern%C3%A1ndez), Ed. Servitec, Num. 9, ISBN: 84-8416-357-1 - 1998\n- [Lógica proposicional para informática](http://labra.weso.es/publication/1998_propositionallogic/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Ana I. Fernández](https://labra.weso.es/authors/ana-i.-fern%C3%A1ndez), Ed. Servitec, Num. 12, ISBN: 84-8416-613-9 - 1998\n- [An Implementation of Modular Monadic Semantics using Folds and Monadic Folds](http://labra.weso.es/publication/1998_mms_usingfoldsmonadicfolds/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), Workshop on Research Themes on Functional Programming, Third International Summer School on Advanced Functional Programming - 1998\n- [Harmony: a functional system for musical composition](http://labra.weso.es/publication/1997_harmony/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Juan Manuel Cueva Lovelle](https://labra.weso.es/authors/juan-manuel-cueva-lovelle), [Luis Ángel Oliveira](https://labra.weso.es/authors/luis-%C3%A1ngel-oliveira), In *II Conferencia Latinoamericana de Programación Funcional* - 1997\n- [Introducción al lenguaje Haskell](http://labra.weso.es/publication/1995_introhaskell/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), Cuaderno didáctico, Número 87, Depto. Matemáticas - 1995\n- [Lógica de predicados de primer orden](http://labra.weso.es/publication/1993_logica/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), Cuaderno didáctico, Número 77, Depto. Matemáticas - 1993\n- [Simulación Entorno Operativo Unix](http://labra.weso.es/publication/1991_simulacionunix/), [Jose Emilio Labra Gayo](https://labra.weso.es/authors/jose-emilio-labra-gayo), [Oliverio González](https://labra.weso.es/authors/oliverio-gonz%C3%A1lez), [Miguel Riesco Albizu](https://labra.weso.es/authors/miguel-riesco-albizu), Cuaderno didáctico, Número 39, Depto. Matemáticas - 1991\n\n## Recent & Upcoming Talks\n\n[More Talks](https://labra.weso.es/talk/)\n\n- [Shaping Knowledge and Interoperable Graphs](http://labra.weso.es/talk/2026_shaping_knowledge_interoperable_graphs_poland/) Mon, 20 Apr, 2026, Invited talk at Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Poland\n- [Shaping Knowledge and Interoperable Graphs](http://labra.weso.es/talk/2025_iswc_2025/) Sun, 2 Nov, 2025, Tutorial at ISWC’25\n- [Shaping Linked Data and Knowledge Graphs](http://labra.weso.es/talk/2025_dcmi_2025/) Sat, 25 Oct, 2025, Tutorial at DCMI-25 Conference\n- [Workshop on Data Validation](http://labra.weso.es/talk/2025_raildataforum/) Thu, 12 Jun, 2025, Workshop at Rail Data Forum\n- [Shaping Knowledge Graphs](http://labra.weso.es/talk/2025_eswc_2025/) Wed, 11 Jun, 2025, Tutorial at ESWC’25\n- [Validating Knowledge Graphs](http://labra.weso.es/talk/2024_validating_kgs_laplata/) Wed, 11 Dec, 2024, Charla invitada en LIFIA, Universidad de La Plata\n- [Validating Knowledge Graphs](http://labra.weso.es/talk/2024_validating_kgs/) Tue, 19 Nov, 2024, Charla invitada en Máster Oficial de Ingeniería del Software e Inteligencia Artificial\n- [Shaping Knowledge Graphs](http://labra.weso.es/talk/2024_shaping_kgs_iswc/) Mon, 11 Nov, 2024, Tutorial at International Semantic Web Conference\n- [Let's dive into EntitySchemas](http://labra.weso.es/talk/2023_datamodelingdays/) Thu, 30 Nov, 2023, Wikidata Data Modeling Days\n- [Knowledge graphs: description, validation and subsetting](http://labra.weso.es/talk/2023_dresden/) Thu, 5 Oct, 2023, Invited talk at International Center for Computational Logic at Dresden\n\n## Other info\n\n## Supervised PhD students\n\n- [Francisco Cifuentes Silva](http://www.fcifuentes.cl/): Tecnologías Semánticas en el ámbito político-legislativo, October, 2025\n- [Daniel Fernández Álvarez](http://danifdez.weso.es/): Extracción de conocimiento semántico estructurado mediante minería de medios sociales, Sept, 2022\n- [Herminio García González](http://herminiogarcia.com/): Integración semántica de grandes fuentes de datos heterogéneas, 2021\n- [Jose Alberto Benítez Andrades](http://www.jabenitez.com/): Tecnologías Semánticas aplicadas al Análisis de Redes Sociales en el ámbito de la Salud, 2017\n- [Hernán Sagastegui Chigne](https://www.linkedin.com/in/hernan-sagastegui-chigne-48264025/): Desarrollo de Tecnologías Colaborativas para Entornos virtuales de apoyo al aprendizaje, 2015\n- [Jose María Álvarez Rodríguez](http://www.josemalvarez.es/): Métodos semánticos de reutilización de datos abiertos enlazados en las licitaciones públicas, 2012\n\n## PhD Students supervision (Current)\n\n- Hugo Lebredo Buján: Aplicación de grafos de conocimiento en la interoperabilidad de datos descentralizados de ámbito privado\n- Claudio Andrés Navarro Cruces: Semantic Technologies Applied to Cyber-Physical Systems Modelling\n- Ángel García Menéndez\n- Enrique José Rodríguez Martín\n- Jorge Álvarez Fidalgo\n- Pablo Valdés Fernández\n\n## PhD Thesis Committees\n\n- [Ammar Ammar](https://www.linkedin.com/in/ammar-ammar/): July, 2025, Maastricht, Enhancing the interoperability and reusability of nanosafety data: a foundation towards deeper insights and intelligent applications\n- [Ben De Meester](https://work.de-meester.org/), [IDLab, University of Ghent, Belgium](https://www.ugent.be/ea/idlab/en/), May 2020, title: Improving and Assessing Data Quality of Knowledge Graphs.\n- [Mikko Koho](https://www.linkedin.com/in/mikko-koho/), [School of Science in Aalto University](http://cs.aalto.fi/), April 2020, title: Representing, Using, and Maintaining Military Historical Linked Data on the Semantic Web.\n- [Andrii Berezovskyi](https://www.kth.se/profile/andriib?l=en), [KTH](https://www.kth.se/en), Jan 2020, title: A generic framework for integration of Cyber-physical Systems by use of intelligent systems (Midterm PhD Examination)\n\n## Member of Scientific/Organizing committee\n\n- [International Semantic Web Conference, 2020](https://iswc2020.semanticweb.org/)\n- [Joint International Conference on Knowledge Graphs 2020](https://language-semantic.org/jist-kg-2020/)\n- [DaMaLOS-2020: First workshop on Research data* management for linked open science (* and associated Research Objects)](https://zbmed.github.io/damalos/)\n- [3rd Workshop on Quality of Open Data](https://bisconf.org/2020/qod/)\n- [2nd Iberoamerican Knowledge Graph and Semantic Web Conference](http://www.kgswc.org/)\n- [International Semantic Web Conference, 2019](https://iswc2019.semanticweb.org/)\n- [24th European Conference on Artificial Intelligence](http://ecai2020.eu/)\n- [International Semantic Web Conference - ISWC 2019](http://iswc2019.semanticweb.org/)\n- [8th Workshop on Ontology Design and Patterns](http://ontologydesignpatterns.org/wiki/WOP:2017#WOP2017_Chairs), WOP, 2017\n- [Workshop on Linked Enterprise Data Services, Provenance, Linking and QualitY](https://informatik2017.de/ws29-ledsplay17/), LEDSPLaY17, 2017\n- [Linked Data Quality Workshop](http://ldq.semanticmultimedia.org/), 2017\n- [ISW-LOD2016](http://ciep.ing.uaslp.mx/sw-lod/) (4th International Workshop on Semantic Web and Linked Open Data), Puerto Rico, 2016\n- [SEMANTiCS 2016](https://2016.semantics.cc/), Senior PC member\n- [Latin American Symposium on Data Management Systems](http://www.clei2016.cl/Sim7.html), Co-chair\n- [W3c workshop on Multilingual web](https://www.multilingualweb.eu/documents/2015-riga-workshop/2015-riga-cfp), 2015\n- [SEMANTiCS 2015](https://2015.semantics.cc/) Research Track (11th International Conference on Semantic Systems, Research Track), Senior PC member\n- [ReCert 2015 (1st International Workshop on Linked Data Repair and Certification)](http://recert-ld.github.io/2015/), 2015\n- [International Conference on Knowledge Engineering and Semantic Web](http://2014.kesw.ru/), 2014\n- 16th International Simposium on Computers in Education, 2014\n- [Workshop on Ontology and Semantic Web Patterns](http://ontologydesignpatterns.org/wiki/WOP:2016), WOP, 2014, 2015, 2016, 2017\n- [Spanish conference on service science and engineering](https://labra.weso.es/www.congresocedi.es/es/jcis), 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014\n- [Encuentro Nacional en Ciencias de la Computación](http://enc2014.cicese.mx/index.html), Mexico, 2014\n- Jornadas de Enseñanza Universitaria de Informática, Jenui, 2014, 2015, 2016, [2017](http://jenui2017.unex.es/)\n- 12th International Semantic Web Conference - Evaluation Track, 2012\n- 9th Extended Semantic Web Conference, 2012\n- Metadata and Semantics Research Conference, MTSR, 2012\n- Social Data and Semantic Web, Workshop of the 10th International Conference on Semantic Web\n- Workshop on LInked Data en Conferencia Española de la Asociación para La Inteligencia Artificial (CAEPIA, 2011)\n- Workshop on Software Engineering and eLearning (ISELEAR), 2010, 2011\n- Brazilian Symposium on Programming Languages (SBLP), 2003, 2004, 2005, 2006, 2007, 2008, 2009\n- Jornadas sobre Programación y Lenguajes (PROLE), 2008\n- International Conference on Web Engineering, ICWE, 2003, 2004, 2006\n- Fourth International Workshop on Language, Descriptions, Tools and Applications, 2004\n\n## Reviewer of papers in the following journals\n\n- [Computer Standards and Interfaces](https://www.journals.elsevier.com/computer-standards-and-interfaces), Reviewer, 2017\n- [Bioinformatics](https://academic.oup.com/bioinformatics), 2015\n- [Computers and Human Behaviour](https://www.journals.elsevier.com/computers-in-human-behavior), Reviewer, 2013-2016\n- [Computers in Industry](https://www.journals.elsevier.com/computers-in-industry), Reviewer and Special issue editor, 2014\n- [Telematics and Informatics](https://www.journals.elsevier.com/telematics-and-informatics), Reviewer, 2016, 2017\n- [Expert Systems with Applications](https://www.journals.elsevier.com/expert-systems-with-applications), Reviewer, 2017\n- [Engineering Applications of Artificial Intelligence](https://www.journals.elsevier.com/engineering-applications-of-artificial-intelligence/), reviewer, 2016\n- [Information Sciences](https://www.journals.elsevier.com/information-sciences/), reviewer, 2014\n- [International Journal of Universal Computer Science](http://www.jucs.org/), reviewer, 2013\n- [Science of Computer Programming](https://www.journals.elsevier.com/science-of-computer-programming/), reviewer, 2013\n- [Semantic Web Journal](http://www.semantic-web-journal.net/), reviewer, 2013\n- [Web Semantics: Science, Services and Agents on the World Wide Web](http://www.sciencedirect.com/science/journal/15708268), reviewer, 2013\n\n## Advisory board of the following publications\n\n- [Global Hospitality and Tourism Management Technologies: Applications and Issues](https://www.igi-global.com/book/global-hospitality-tourism-management-technologies/51923), Editors: Patricia Ordóñez de Pablos, R. Tennyson, and J-Y. Zhao, 2011, IGI-Global. Pp. 1-270 ISBN DOI: 10.4018 ⁄ 978 -1-61350-041-5, ISBN13: 978-1-61350-041-5, ISBN10: 1-61350-041-6\n- [Semantic Web Personalization and Context Awareness: Management of Personal Identities and Social Networking](https://www.igi-global.com/book/semantic-web-personalization-context-awareness/47405), Editors: Lytras, M.D., Ordóñez de Pablos, P. and Damiani, E., IGI-Global, pp.1-232, 2011, DOI: 10.4018 ⁄ 978 -1-61520-921-7, ISBN13: 9781615209217, ISBN10: 1615209212, EISBN13: 9781615209224.\n- [Digital Culture and E-Tourism: Technologies, Applications and Management Approaches](https://www.igi-global.com/book/digital-culture-tourism/45944), Editors: Lytras, M.D., Ordóñez de Pablos, P., Damiani, E. and Diaz, L. (2011), Editorial IGI-Global. Pp. 1-270. ISBN 9781615208678.\n- [Technology Enhanced Learning for People with Disabilities: Approaches and Applications](https://www.igi-global.com/book/technology-enhanced-learning-people-disabilities/41739), Editors: Ordóñez de Pablos, P., Zhao, Y. and Tennyson, R., 2010, Editorial IGI-Global, pp- 1-276. ISBN-10: 1615209239 -ISBN-13: 978-1615209231. DOI: 10.4018 ⁄ 978 -1-61520-923-1\n\n## More personal information\n\nI was the drummer of [Kactus Jack](https://es.wikipedia.org/wiki/Kactus_Jack). You can see the original [unofficial home page](https://labra.weso.es/Kactus/Welcome.html), vintage style.\n\nI was also the drummer of [Los Murciélagos](http://no80s-gruposnacionales.blogspot.com.es/2009/01/los-murcielagos.html) and *Los Aborígenes*.\n\nI think I wrote my first Web Page in 1994. I found 2 versions of my home page from:\n\n- [2003](https://web.archive.org/web/20031029101917/http://www.di.uniovi.es/~labra/) (I found funny the Hobbies section…)\n- [2013](https://web.archive.org/web/20130616144520/http://di002.edv.uniovi.es/~labra/)\n\n## Recent Posts\n\n[More Posts](https://labra.weso.es/post/)\n\nComentario sobre el libro *El arte de la tesis doctoral*\n\nComentario sobre el libro *Datanomics*\n\nComentario sobre el libro *Científico en España*\n\nComentario sobre el libro *El Arte y la Ciencia de no hacer nada* de Andrew J. Smart\n\nDescription of my new home page\n\n## Projects\n\n- [Shapes-rs](https://www.weso.es/shapes-rs/) RDF data shapes implementation in Rust\n- [WShEx](https://www.weso.es/WShEx/) Wikibase varaint of ShEx\n- [rdfshape](https://rdfshape.weso.es/) RDF playground\n- VARSSHA Validating RDF Streams using Shapes\n- [SHACLex](http://labra.github.io/shaclex/) SHACL & ShEx implementation in Scala\n- [ShExkell](https://github.com/weso/shexkell/) A preliminary implementation of ShEx in Haskell\n- Language Prototyping System This project was part of my PhD thesis where the main goal was to implement a system that could create programming languages by combining different semantic blocks. It was based on the use of monads and I was happy to build functional, imparative, logic and object oriented programming languages by combining those building blocks. The implementation was developed in Haskell.\n- [Multilingual Linked Data Patterns](http://www.weso.es/MLODPatterns) Multilingual Linked Data Patterns\n\n## Teaching\n\nI teach the following courses:\n\n- [Software architecture](https://arquisoft.github.io/) - [Bachelor of Software Engineering](http://ingenieriainformatica.uniovi.es/web/ingenieriainformatica/infoacademica/grado), [University of Oviedo](http://uniovi.es/), Spain. This course is taught in Spanish and English.\n- [Semantic Web](http://www.weso.es/websem/) - [Master in Web Engineering](http://miw.uniovi.es/), [University of Oviedo](http://uniovi.es/), Spain\n- [Advances in Semantic Web](http://www.weso.es/websem/) - [Master in Web Engineering](http://miw.uniovi.es/), [University of Oviedo](http://uniovi.es/), Spain\n- Web systems and applications - [Master in Information Technology](http://mti.cl/), [Technical University Federico Santa María](http://utfsm.cl/), Chile I also taught the courses:\n\n- Languages and Web standards - [Master in Web Engineering](http://miw.uniovi.es/), [University of Oviedo](http://uniovi.es/), Spain\n- Object Oriented Programming - [Master in Web Engineering](http://miw.uniovi.es/), [University of Oviedo](http://uniovi.es/), Spain\n- Web services - [Master in Web Engineering](http://miw.uniovi.es/), [University of Oviedo](http://uniovi.es/), Spain\n- [Logic](http://di002.edv.uniovi.es/~labra/Logica/Logica.html) - Bachelor of Computer Science, [University of Oviedo](http://uniovi.es/)\n- [Declarative Programming](http://www.di.uniovi.es/~labra/PDec) - Bachelor of Computer Science, [University of Oviedo](http://uniovi.es/)\n- Language Processors - [EPIG](http://www.epig.uniovi.es/)"},"author":{"name":"Jose Emilio Labra Gayo","bio":"Full Professor"},"metadata":{"timestamp":"2019-11-14T18:37:00.000Z"},"media":[],"aiComments":[]},{"id":"web-xhx5o1","shareId":"RbMRdMHa7m","platform":"web","url":"https://link.springer.com/chapter/10.1007/978-3-030-30793-6_9","title":"Validating Shacl Constraints over a Sparql Endpoint","shareMode":"full","createdAt":1787214663744,"postedAt":"2019-01-01T00:00:00.000Z","publishedDate":"2019-01-01T00:00:00.000Z","archivedAt":"2026-08-20T08:30:58.947Z","archivedDate":"2026-08-20T08:30:58.947Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/RbMRdMHa7m","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/VDJ8rhwIuG/media/0.jpg","contentType":"article","content":{"text":"## Abstract\n\nshacl (Shapes Constraint Language) is a specification for describing and validating RDF graphs that has recently become a W3C recommendation. While the language is gaining traction in the industry, algorithms for shacl constraint validation are still at an early stage. A first challenge comes from the fact that RDF graphs are often exposed as sparql endpoints, and therefore only accessible via queries. Another difficulty is the absence of guidelines about the way recursive constraints should be handled. In this paper, we provide algorithms for validating a graph against a shacl schema, which can be executed over a sparql endpoint. We first investigate the possibility of validating a graph through a single query for non-recursive constraints. Then for the recursive case, since the problem has been shown to be NP-hard, we propose a strategy that consists in evaluating a small number of sparql queries over the endpoint, and using the answers to build a set of propositional formulas that are passed to a SAT solver. Finally, we show that the process can be optimized when dealing with recursive but tractable fragments of shacl, without the need for an external solver. We also present a proof-of-concept evaluation of this last approach.\n\nThis is a preview of subscription content, [log in via an institution](https://wayf.springernature.com/?redirect_uri=https%3A%2F%2Flink.springer.com%2Fchapter%2F10.1007%2F978-3-030-30793-6_9%3Ferror%3Dcookies_not_supported%26code%3D0231c810-7858-4e62-838d-c6d0b0800f20) to check access.\n\n## Access this chapter\n\n[Log in via an institution](https://wayf.springernature.com/?redirect_uri=https%3A%2F%2Flink.springer.com%2Fchapter%2F10.1007%2F978-3-030-30793-6_9%3Ferror%3Dcookies_not_supported%26code%3D0231c810-7858-4e62-838d-c6d0b0800f20)\n\n[Institutional subscriptions](https://www.springernature.com/gp/librarians/licensing/agc/ebooks)\n\n## Notes\n\n1. 1.[https://www.w3.org/TR/shacl/](https://www.w3.org/TR/shacl/).\n2. 2.[https://w3c.github.io/data-shapes/data-shapes-test-suite/](https://w3c.github.io/data-shapes/data-shapes-test-suite/).\n3. 3.with the exception of *Shaclex* [[4](#fn:4)], which can handle recursion, but not recursion and negation together in a principled way.\n4. 4.More exactly, *I* is an abstraction, standing for any syntactic constraint over an rdf term: exact value, datatype, regex, etc.\n5. 5.shacl paths are built like sparql property paths, but without the *NegatedPropertySet* operator.\n6. 6.We omit the trivial FILTER (?y1 =?y1 AND?y2 =?y2) for readability.\n7. 7.For some normalized schemas, it could happen that \$[\\![q_{{{\\,\\mathrm{def}\\,}}(s)} ]\\!]^{\\mathcal {G}}\$ always retrieves all nodes from \$\\mathcal {G} \$. This would be the case for example if \${{\\,\\mathrm{def}\\,}}(s) = s_1 \\wedge s_2\$. A simple optimization technique here consists in not executing such queries, and instantiate instead the rule pattern \$p_{{{\\,\\mathrm{def}\\,}}(s)}\$ with all nodes retrieved by all other queries (and bound to variable?x).\n\n## References\n\n## Editor information\n\n### Editors and Affiliations\n\n## Rights and permissions\n\n## About this paper\n\n### Cite this paper\n\nCorman, J., Florenzano, F., Reutter, J.L., Savković, O. (2019). Validating Shacl Constraints over a Sparql Endpoint. In: Ghidini, C., *et al.* The Semantic Web – ISWC 2019. ISWC 2019. Lecture Notes in Computer Science(), vol 11778. Springer, Cham. https://doi.org/10.1007/978-3-030-30793-6_9\n\n- [.RIS](https://citation-needed.springer.com/v2/references/10.1007/978-3-030-30793-6_9?format=refman&flavour=citation)\n- [.ENW](https://citation-needed.springer.com/v2/references/10.1007/978-3-030-30793-6_9?format=endnote&flavour=citation)\n- [.BIB](https://citation-needed.springer.com/v2/references/10.1007/978-3-030-30793-6_9?format=bibtex&flavour=citation) - DOI https://doi.org/10.1007/978-3-030-30793-6_9\n- Published 17 October 2019\n- Publisher NameSpringer, Cham\n- Print ISBN978-3-030-30792-9\n- Online ISBN978-3-030-30793-6\n- eBook Packages [Computer Science](https://link.springer.com/search?facet-content-type=%22Book%22&package=11645&facet-start-year=2019&facet-end-year=2019) [Computer Science (R0)](https://link.springer.com/search?facet-content-type=%22Book%22&package=43710&facet-start-year=2019&facet-end-year=2019) [Springer Nature Proceedings Computer Science](https://link.springer.com/search?facet-content-type=%22Book%22&package=85344&facet-start-year=2019&facet-end-year=2019)\n\n## Publish with us\n\n[Policies and ethics](https://www.springernature.com/gp/policies/book-publishing-policies)\n\n## Societies and partnerships\n\n- [![the Semantic Web Science Association](https://published-with.public.springernature.app/img/swsa.jpg) the Semantic Web Science Association](http://swsa.semanticweb.org/)\n1. DBpedia. [wiki.dbpedia.org/downloads-2016-10](https://wiki.dbpedia.org/downloads-2016-10)\n2. Extended version. [https://www.inf.unibz.it/krdb/tech-reports/](https://www.inf.unibz.it/krdb/tech-reports/)\n3. SHACL Test Suite. [w3c.github.io/data-shapes/data-shapes-test-suite/](http://w3c.github.io/data-shapes/data-shapes-test-suite/)\n4. Shaclex. [http://github.com/labra/shaclex/](http://github.com/labra/shaclex/) [↩](#fnref:4)\n5. Shex.js. [http://github.com/shexSpec/shex.js/](http://github.com/shexSpec/shex.js/)\n6. Source code and experiment’s material. [http://github.com/rdfshapes/shacl-sparql](http://github.com/rdfshapes/shacl-sparql)\n7. Stardog ICV. [https://www.stardog.com/blog/data-quality-with-icv/](https://www.stardog.com/blog/data-quality-with-icv/)\n8. TopBraid Composer. [http://www.topquadrant.com/products/topbraid-composer/](http://www.topquadrant.com/products/topbraid-composer/)\n9. 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[https://doi.org/10.1007/978-3-030-00671-6_19](https://doi.org/10.1007/978-3-030-00671-6_19) [Chapter](https://link.springer.com/doi/10.1007/978-3-030-00671-6_19) [Google Scholar](https://scholar.google.com/scholar_lookup?&title=Semantics%20and%20validation%20of%20recursive%20SHACL&pages=318-336&publication_year=2018%202018%202018&author=Corman%2CJ&author=Reutter%2CJL&author=Savkovi%C4%87%2CO)\n11. Corman, J., Reutter, J.L., Savković, O.: Semantics and validation of recursive SHACL (extended version). Technical report KRDB18-1, Free University Bozen-Bolzano (2018). [https://www.inf.unibz.it/krdb/tech-reports/](https://www.inf.unibz.it/krdb/tech-reports/) [Google Scholar](https://scholar.google.com/scholar_lookup?&title=Semantics%20and%20Validation%20of%20Recursive%20SHACL&pages=318-336&publication_year=2018&author=Corman%2CJulien&author=Reutter%2CJuan%20L.&author=Savkovi%C4%87%2COgnjen)\n12. Corman, J., Reutter, J.L., Savković, O.: A tractable notion of stratification for SHACL. 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Agents World Wide Web **7** (2), 74–89 (2009) [Article](https://doi.org/10.1016%2Fj.websem.2009.02.001) [Google Scholar](https://scholar.google.com/scholar_lookup?&title=Bridging%20the%20gap%20between%20OWL%20and%20relational%20databases&journal=Web%20Semant.%3A%20Sci.%20Serv.%20Agents%20World%20Wide%20Web&volume=7&issue=2&pages=74-89&publication_year=2009&author=Motik%2CB&author=Horrocks%2CI&author=Sattler%2CU)\n15. Reutter, J.L., Soto, A., Vrgoč, D.: Recursion in SPARQL. In: Arenas, M., et al. (eds.) ISWC 2015. LNCS, vol. 9366, pp. 19–35. Springer, Cham (2015). [https://doi.org/10.1007/978-3-319-25007-6_2](https://doi.org/10.1007/978-3-319-25007-6_2) [Chapter](https://link.springer.com/doi/10.1007/978-3-319-25007-6_2) [Google Scholar](https://scholar.google.com/scholar_lookup?&title=Recursion%20in%20SPARQL&pages=19-35&publication_year=2015%202015%202015&author=Reutter%2CJL&author=Soto%2CA&author=Vrgo%C4%8D%2CD)\n16. Staworko, S., Boneva, I., Labra Gayo, J.E., Hym, S., Prud’hommeaux, E.G., Solbrig, H.: Complexity and expressiveness of ShEx for RDF. In: ICDT (2015) [Google Scholar](https://scholar.google.com/scholar?&q=Staworko%2C%20S.%2C%20Boneva%2C%20I.%2C%20Labra%20Gayo%2C%20J.E.%2C%20Hym%2C%20S.%2C%20Prud%E2%80%99hommeaux%2C%20E.G.%2C%20Solbrig%2C%20H.%3A%20Complexity%20and%20expressiveness%20of%20ShEx%20for%20RDF.%20In%3A%20ICDT%20%282015%29)\n17. Tao, J., Sirin, E., Bao, J., McGuinness, D.L.: Integrity constraints in owl. In: AAAI (2010) [Google Scholar](https://scholar.google.com/scholar?&q=Tao%2C%20J.%2C%20Sirin%2C%20E.%2C%20Bao%2C%20J.%2C%20McGuinness%2C%20D.L.%3A%20Integrity%20constraints%20in%20owl.%20In%3A%20AAAI%20%282010%29) [↩](#fnref:17)"},"author":{"name":"Julien Corman, Fernando Florenzano, Juan L. Reutter, Ognjen Savković","bio":"shacl (Shapes Constraint Language) is a specification for describing and validating RDF graphs that has recently become a W3C recommendation. While the language is gaining traction in the industry, algorithms for shacl constraint validation are still at an early..."},"metadata":{"timestamp":"2019-01-01T00:00:00.000Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/VDJ8rhwIuG/media/0.jpg","type":"image","width":153,"height":232}],"aiComments":[]},{"id":"web-hdcw6y","shareId":"NPet9IueAt","platform":"web","url":"https://dl.acm.org/doi/10.1007/978-3-030-30793-6_9","title":"Validating Shacl Constraints over a Sparql Endpoint | The Semantic Web","shareMode":"full","createdAt":1787214623164,"postedAt":"2026-08-20T08:30:18.735Z","publishedDate":"2026-08-20T08:30:18.735Z","archivedAt":"2026-08-20T08:30:20.512Z","archivedDate":"2026-08-20T08:30:20.512Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/NPet9IueAt","thumbnail":"https://dl.acm.org/cms/asset/c586a540-46fd-4b00-8004-4e59a0d5a2a6/978-3-030-30793-6.cover.jpg","contentType":"article","content":{"text":"## Abstract\n\nshacl (Shapes Constraint Language) is a specification for describing and validating RDF graphs that has recently become a W3C recommendation. While the language is gaining traction in the industry, algorithms for shacl constraint validation are still at an early stage. A first challenge comes from the fact that RDF graphs are often exposed as sparql endpoints, and therefore only accessible via queries. Another difficulty is the absence of guidelines about the way recursive constraints should be handled. In this paper, we provide algorithms for validating a graph against a shacl schema, which can be executed over a sparql endpoint. We first investigate the possibility of validating a graph through a single query for non-recursive constraints. Then for the recursive case, since the problem has been shown to be NP-hard, we propose a strategy that consists in evaluating a small number of sparql queries over the endpoint, and using the answers to build a set of propositional formulas that are passed to a SAT solver. Finally, we show that the process can be optimized when dealing with recursive but tractable fragments of shacl, without the need for an external solver. We also present a proof-of-concept evaluation of this last approach."},"author":{"name":"dl.acm.org"},"metadata":{"timestamp":"2026-08-20T08:30:18.735Z"},"media":[{"url":"https://dl.acm.org/cms/asset/c586a540-46fd-4b00-8004-4e59a0d5a2a6/978-3-030-30793-6.cover.jpg","type":"image"}],"aiComments":[]},{"id":"web-qhx5ei","shareId":"3n9DfB2usx","platform":"web","url":"https://www.dataaihub.co/learn/knowledge-graph-best-practices","title":"Knowledge Graph Best Practices Guide | Data AI Hub","shareMode":"full","createdAt":1787214598606,"postedAt":"2026-07-20T00:00:00.000Z","publishedDate":"2026-07-20T00:00:00.000Z","archivedAt":"2026-08-20T08:29:54.364Z","archivedDate":"2026-08-20T08:29:54.364Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/3n9DfB2usx","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/4iM5q4ALRx/media/0.png","contentType":"article","content":{"text":"## TL;DR\n\n- **Start with use-case-driven modeling** — define the questions your graph must answer before designing the full ontology. A knowledge graph is a semantic model; the graph database is just where you store it.\n- **Entity resolution is non-negotiable** — duplicate nodes destroy trust faster than missing data. Resolution is a platform capability, not an ETL afterthought.\n- **Schema evolution is continuous** — plan for additive changes, versioning, and backward-compatible migrations from day one. Ontology changes follow the same rigor as API versioning.\n- **Data quality gates belong in the pipeline** — validate at ingest with [SHACL](https://www.dataaihub.co/learn/shacl) or constraints, not after users discover bad data in production.\n- **Governance beats technology** — assign stewards per domain, version ontologies in Git, and review schema changes like API changes. Neo4j, Stardog, GraphDB, Neptune, and Jena are interchangeable compared to modeling discipline.\n\n## Why This Matters\n\nMost knowledge graph projects fail quietly. Not because Neo4j or GraphDB was the wrong choice, but because the graph became an unmaintainable tangle of duplicate entities, inconsistent relationship types, and ontologies nobody dared to change.\n\nA support team builds a graph to link customers, tickets, and products. Six months later, `Customer` nodes exist under four naming conventions, `RELATED_TO` edges mean different things in different domains, and a schema change breaks three downstream dashboards. The graph still exists — but nobody trusts it. A pharma team loads drug–target–trial data without [SHACL](https://www.dataaihub.co/learn/shacl) validation; 12% of `ClinicalTrial` nodes reference deprecated trial IDs. Compliance reporting fails an audit.\n\nBest practices are not bureaucracy. They are the engineering patterns that keep a [knowledge graph](https://www.dataaihub.co/learn/what-is-a-knowledge-graph) queryable, trustworthy, and evolvable as your organization learns what it actually needs from structured knowledge. They are the difference between a departmental experiment and an [enterprise knowledge graph](https://www.dataaihub.co/learn/enterprise-knowledge-graphs) that powers search, analytics, compliance, and [GraphRAG](https://www.dataaihub.co/learn/graphrag) / [RAG](https://www.dataaihub.co/learn/rag) consumers for years.\n\nThe critical distinction throughout: **a knowledge graph is not a graph database**. Stardog, GraphDB, Neptune, Neo4j, and Apache Jena are storage and query engines. Best practices govern the semantic layer — ontology, identity, provenance, validation, and stewardship — that makes those engines worth operating.\n\n\n\n## The Problem\n\nKnowledge graphs are deceptively flexible. Unlike relational schemas, you can add nodes and edges without migrations — which encourages organic growth until the graph becomes impossible to reason about.\n\nThree failure modes drive the need for disciplined practices:\n\n**Ontology sprawl.** Every team adds classes and predicates for their immediate need. `worksFor`, `employedBy`, `hasEmployer`, and `employeeOf` coexist as synonyms nobody consolidates. Queries become archaeology. Downstream [GraphRAG](https://www.dataaihub.co/learn/graphrag) pipelines retrieve inconsistent relationship types, and LLM answers contradict themselves.\n\n**Data quality decay.** Without validation at ingest, 15% of `Person` nodes lack email, `suppliedBy` edges point to deprecated vendors, and entity resolution duplicates accumulate weekly. Trust erodes silently until a compliance officer finds double-counted counterparty exposure or a [RAG](https://www.dataaihub.co/learn/rag) system cites a merged-but-wrong entity.\n\n**Schema change paralysis.** Downstream consumers hardcode relationship names. Changing `dependsOn` to `DEPENDS_ON` breaks [SPARQL](https://www.dataaihub.co/learn/sparql) queries in production. Teams stop evolving the schema; the graph fossilizes while business requirements change.\n\n**Graph-database confusion.** Teams optimize Neo4j indexing or Stardog cluster sizing while ignoring ontology governance. They have a fast graph store — not a knowledge graph. Performance tuning matters, but it cannot fix duplicate entities or missing provenance.\n\nBest practices provide **guardrails** — not to slow delivery, but to prevent rework that costs 10x more than upfront discipline.\n\n\n\n## How We Got Here\n\nKnowledge graph best practices emerged from repeated project failures across semantic web, graph database, and enterprise data integration communities:\n\n**Diagram: Evolution of KG engineering practices**\n\n\n\n```\nflowchart LR\nA[Ad-hoc graph loads] --> B[Ontology standards / OWL]\nB --> C[SHACL validation]\nC --> D[MDM + entity resolution]\nD --> E[Governed enterprise KG]\nE --> F[GraphRAG + LLM grounding]\n```\n\n*Each generation added discipline after learning that flexible graphs without governance become unmaintainable.*\n\n\n\n| Phase | What teams learned | Practice that emerged |\n| --- | --- | --- |\n| **Early graph DB projects (2010s)** | Fast traversals ≠ trusted data | Use-case-first modeling |\n| **Semantic web adoption (2010s–2020s)** | OWL complexity kills projects | Minimal ontology, version in Git |\n| **Enterprise MDM integration (2010s–2020s)** | Golden records need graph relationships | Canonical identity + `sameAs` |\n| **SHACL standardization (2017+)** | Post-load cleaning fails at scale | Validate at ingest, quarantine violations |\n| **AI consumption (2024+)** | LLM extraction injects noise | Human-in-the-loop + SHACL before merge |\n| **Enterprise platforms (2020s+)** | Departmental graphs don't scale | Stewardship councils, named graphs, federation |\n\nFrameworks like [LangChain](https://www.dataaihub.co/tools/langchain) and [LlamaIndex](https://www.dataaihub.co/tools/llamaindex) make it easy to connect LLMs to graphs — but they do not replace modeling discipline. The graph you connect must be governed first.\n\n\n\n## Architecture\n\nBest practices define the **semantic architecture** of a production knowledge graph — independent of whether you store in Stardog, GraphDB, Neptune, Neo4j, or Jena.\n\n**Diagram: Knowledge graph best-practices architecture**\n\n\n\n```\nflowchart TB\nsubgraph Modeling[\"Modeling Layer\"]\nUC[Use-Case Query Patterns]\nONT[Minimal Ontology]\nID[Canonical Identity Strategy]\nend\n\nsubgraph Quality[\"Data Quality Layer\"]\nSHACL[SHACL / Constraints]\nER[Entity Resolution]\nPROV[Provenance on Every Fact]\nend\n\nsubgraph Evolution[\"Schema Evolution Layer\"]\nVER[Ontology Versioning in Git]\nDUAL[Dual-Write Migrations]\nIMP[Impact Analysis]\nend\n\nsubgraph Governance[\"Governance Layer\"]\nST[Domain Stewards]\nREV[PR Review for Schema Changes]\nMET[Quality Metrics Dashboard]\nend\n\nsubgraph Engine[\"Graph Database Engine\"]\nDB[Stardog / GraphDB / Neptune / Neo4j / Jena]\nend\n\nUC --> ONT\nONT --> ID\nID --> SHACL\nSHACL --> ER\nER --> PROV\nPROV --> DB\nVER --> ONT\nDUAL --> VER\nIMP --> REV\nST --> REV\nREV --> MET\nMET --> SHACL\n```\n\n*The knowledge graph is the modeled, validated, governed semantic layer — the database engine is the bottom box.*\n\n\n\n### Graph design principles\n\n\n\n#### Principle 1: Use-case-first modeling\n\nDo not model the entire enterprise before loading data. Pick one high-value use case — supplier risk, customer 360, document entity linking, fraud counterparty exposure — and model only the entities and relationships that use case requires.\n\n\n\n| Use Case | Core Entities | Key Relationships |\n| --- | --- | --- |\n| Customer 360 | Customer, Account, Contact | `hasAccount`, `primaryContact`, `ownsSubscription` |\n| Supply chain risk | Product, Component, Supplier, Country | `contains`, `suppliedBy`, `locatedIn` |\n| Fraud / compliance | Counterparty, Trade, SanctionList | `references`, `listedOn`, `holds` |\n| Life sciences | Drug, Target, Trial, Disease | `targets`, `tests`, `treats` |\n| Expert finder | Person, Skill, Project, Document | `hasSkill`, `workedOn`, `authored` |\n| Digital twin | Asset, Sensor, Event | `hasSensor`, `emits`, `triggers` |\n\nExpand the ontology when a **new use case** needs entities the current schema lacks — not when someone imagines a future need.\n\n\n\n#### Principle 2: Stable identity\n\nEvery entity gets a canonical ID independent of source system identifiers.\n\n\n\n```\n# Bad - source ID as primary key\n(customer:CRM-8842)\n\n# Good - canonical ID with source links\n(customer:acme-corp-001 { crmId: \"CRM-8842\", billingId: \"BILL-991\" })\n```\n\nUse `sameAs` ([RDF](https://www.dataaihub.co/learn/rdf)) or `SAME_AS` edges (property graphs) to link source records. Entity resolution merges duplicates into the canonical node.\n\n\n\n#### Principle 3: Typed, minimal relationships\n\nPrefer specific relationship types over generic ones.\n\n\n\n| Avoid | Prefer | Why |\n| --- | --- | --- |\n| `RELATED_TO` | `suppliedBy`, `authoredBy`, `dependsOn` | Queries filter on edge type; generics are unqueryable |\n| `hasProperty` edges for everything | Node attributes for scalar values | Properties on nodes are simpler; reserve edges for traversals |\n| Deep reification | Edge properties (LPG) or RDF-star | Reification adds triples for every edge attribute |\n\n\n\n> Tip Cap relationship types at what your query patterns need. If nobody traverses `mentoredBy`, do not model it until someone asks.\n\n\n\n#### Principle 4: Provenance on every fact\n\nStore where each assertion came from:\n\n- `sourceSystem` — CRM, ERP, manual steward, LLM extraction\n- `assertedAt` — timestamp of ingestion\n- `confidence` — for ML-extracted facts\n- `validFrom` / `validTo` — for temporal facts Without provenance, debugging wrong answers and satisfying auditors is impossible.\n\n\n\n### Ontology design\n\nAn [ontology](https://www.dataaihub.co/learn/ontologies) defines the vocabulary your graph speaks — classes, properties, constraints, and hierarchies.\n\n**Start minimal, version always:**\n\n1. **Core classes** — 5–15 types covering your use case (e.g., `Person`, `Organization`, `Product`).\n2. **Object properties** — relationships between classes (`worksAt`, `supplies`).\n3. **Data properties** — scalar attributes (`email`, `foundedYear`).\n4. **Constraints** — cardinality, required fields, allowed value ranges. Store ontologies in Git. Tag releases (`ontology-v1.3.0`). Downstream pipelines pin to a version.\n\n\n\n> Important Treat ontology changes like API versioning. Breaking renames require migration scripts and consumer notification.\n\n\n\n### RDF vs property graph modeling\n\n\n\n| Practice | RDF (Stardog/GraphDB/Neptune/Jena) | Property Graph (Neo4j) |\n| --- | --- | --- |\n| Class definition | `rdfs:Class`, OWL | Node labels |\n| Relationship typing | Predicate URI | Relationship type |\n| Validation | SHACL shapes | Neo4j constraints, Cypher checks |\n| Hierarchy | `rdfs:subClassOf` | Label inheritance (varies by DB) |\n| Identity linking | `owl:sameAs` | `SAME_AS` edges |\n\nPick one model per graph. Converting between RDF and property graphs in production is expensive — design for your query language and compliance requirements upfront. See [RDF vs Property Graph](https://www.dataaihub.co/learn/rdf-vs-property-graph).\n\n\n\n## Step-by-Step Flow\n\nFollow this flow when designing, building, and maintaining a production knowledge graph:\n\n1. **Document query patterns** — Write 5–10 questions the graph must answer. These drive schema design, not hypothetical future needs.\n2. **Draft minimal ontology** — 5–15 classes, typed relationships, required attributes for [SHACL](https://www.dataaihub.co/learn/shacl). Review with domain expert.\n3. **Define identity strategy** — Canonical ID format, `sameAs` linking, entity resolution thresholds. Align with MDM if present.\n4. **Write SHACL shapes** — Required fields, cardinality, allowed enums. Run in CI against sample data.\n5. **Build ingest pipeline with validation gate** — Map source → ontology → validate → resolve → publish. Quarantine failures.\n6. **Load pilot dataset** — Real data for one use case. Run golden queries. Fix modeling gaps.\n7. **Implement entity resolution** — Deterministic first, then fuzzy/ML, then steward review queue.\n8. **Connect first consumer** — Dashboard, search, or [GraphRAG](https://www.dataaihub.co/learn/graphrag) pilot. Measure against KPIs.\n9. **Establish stewardship cadence** — Biweekly ontology review, weekly quality metrics, PR review for schema changes.\n10. **Plan schema evolution** — Additive changes freely; breaking changes via dual-write migration with impact analysis. **Diagram: Entity resolution flow**\n\n\n\n```\nflowchart LR\nA[Source Records] --> B[Normalize]\nB --> C[Blocking]\nC --> D[Score Matches]\nD --> E{Confidence}\nE -->|≥ 0.95| F[Auto-merge]\nE -->|0.70–0.95| G[Steward Review]\nE -->| I[Canonical Entity]\nG --> I\nH --> I\nI --> J[Audit Log Entry]\n```\n\n*Every merge is logged and reversible. Auto-merge only above measured precision thresholds.*\n\n**Diagram: Knowledge ingestion pipeline with quality gates**\n\n\n\n```\nflowchart LR\nA[Extract] --> B[Map to Ontology]\nB --> C[SHACL Validate]\nC -->|Pass| D[Entity Resolution]\nC -->|Fail| Q[Quarantine]\nQ --> S[Steward Fix]\nS --> D\nD --> E[Publish to Graph]\nE --> F[Update Metrics]\nE --> G[Sync Search / Vector Index]\n```\n\n*Validation before resolution before publication — never load first and clean later.*\n\n\n\n## Real Production Example\n\n\n\n### Retail: phased product knowledge graph\n\nA retail company models `Product`, `Category`, `Brand`, and `Supplier` in phase one — 10K SKUs from PIM with SHACL requiring `sku`, `name`, and `brand`. Phase two adds `Component` and `contains` for compliance (conflict minerals, restricted substances) without breaking changes — new classes and optional relationships only. Phase three runs entity resolution on duplicate suppliers (\"Acme Inc\" vs \"ACME Corporation\") with steward review below 0.9 confidence.\n\n**Quality gates:** Biweekly ontology reviews. CI-gated SHACL validation — failure rate > 0.1% blocks deploy. Weekly metrics: orphan rate, duplicate queue depth, staleness.\n\n**Outcome:** Compliance team queries restricted-substance exposure across 40K SKUs in seconds. [GraphRAG](https://www.dataaihub.co/learn/graphrag) answers \"Which products contain Component X from Supplier Y?\" with graph citations. [RAG](https://www.dataaihub.co/learn/rag) handles policy document retrieval; the graph handles structure.\n\n\n\n### Financial services: fraud counterparty graph\n\nA bank builds a property graph in Neo4j for real-time fraud traversals while maintaining RDF canonical entities in GraphDB for compliance exports. Best practices enforced on both:\n\n- Canonical `Counterparty` IDs from MDM with `sameAs` links to trading system IDs\n- Typed relationships: `HOLDS`, `REFERENCES`, `LISTED_ON` — no generic `RELATED_TO`\n- Provenance on every edge: `{sourceSystem, recordId, assertedAt}`\n- SHACL validation on RDF layer before compliance reporting\n- Steward review for entity merges below 0.92 confidence **Outcome:** Fraud analysts traverse counterparty exposure in sub-second Neo4j queries. Compliance exports auditable RDF triples with full lineage.\n\n\n\n### Life sciences: drug–target–trial linkage\n\nA pharma company models `(Drug)-[:TARGETS]->(Protein)-[:ASSOCIATED_WITH]->(Disease)` and `(Drug)-[:TESTED_IN]->(ClinicalTrial)` using RDF + OWL on GraphDB. Best practices:\n\n- Minimal ontology extended only when R&D teams need new relationship types\n- Ontology versioned in Git; ingest pipelines pin to `ontology-v2.4.0`\n- Entity resolution on drug names using InChIKey deterministic match + fuzzy fallback\n- LLM-extracted relationships from publications validated by SHACL before merge\n- Named graphs isolate internal R&D from licensed external data\n\n### Government: citizen services graph\n\nA government agency connects benefits, tax, and permit systems. Best practices emphasize security and governance:\n\n- Named graph isolation per agency with query-time RBAC\n- No LLM-extracted facts without steward approval\n- Temporal edges (`validFrom` / `validTo`) for eligibility periods\n- Ontology evolution through public stewardship council with documented changelogs **Diagram: Ontology evolution workflow**\n\n\n\n```\nflowchart LR\nA[New Use Case Request] --> B[Gap Analysis]\nB --> C[Ontology Change Proposal]\nC --> D[Steward Review]\nD --> E[Git PR + SHACL CI]\nE --> F[Staging Validation]\nF --> G[Golden Query Tests]\nG --> H[Release Tag]\nH --> I[Consumer Notification]\n```\n\n*Schema evolution is a governed workflow — not ad-hoc triple injection.*\n\n\n\n## Design Decisions\n\n\n\n| Decision | Option A | Option B | When to choose |\n| --- | --- | --- | --- |\n| Ontology depth | Minimal (RDFS) | Rich (OWL reasoning) | Minimal for most production; OWL when automated inference is worth latency |\n| Schema authority | Central ontology team | Federated domain stewards | Central for Best Practice ✅ **Best Practices** — Track quality metrics weekly, version ontologies in Git, enforce SHACL in CI, and maintain a golden query suite per use case.\n\n\n\n| Dimension | Requirement |\n| --- | --- |\n| **Use case scope** | Documented query patterns driving schema; no orphan classes |\n| **Identity** | Canonical IDs; `sameAs` links to sources; entity resolution pipeline |\n| **Ontology governance** | Git-versioned; PR review for new types; deprecation policy |\n| **Validation** | SHACL or constraints at ingest; CI gate on staging loads |\n| **Provenance** | `sourceSystem`, `assertedAt` on all assertions |\n| **Schema evolution** | Additive-first; dual-write for breaking changes; migration runbooks |\n| **Monitoring** | Validation failure rate, orphan edges, duplicate queue, staleness |\n| **Access control** | Subgraph permissions for sensitive domains |\n| **Documentation** | Data dictionary with class/property definitions and example queries |\n| **Engine ops** | Backups, cluster health — necessary but insufficient without semantic discipline |\n\n\n\n### Data quality metrics to track weekly\n\n- **Orphan rate** — edges pointing to missing nodes\n- **Validation failure rate** — % of ingest batch rejected by SHACL\n- **Duplicate candidate queue depth** — unresolved entity resolution items\n- **Staleness** — % of nodes not updated within freshness SLA\n- **Attribute completeness** — % of required fields populated per class\n- **Ontology version drift** — consumers querying deprecated predicates **Diagram: Governance and security layers**\n\n\n\n```\nflowchart TB\nsubgraph Gov[\"Governance\"]\nST[Named Domain Stewards]\nPR[Schema PR Review]\nCHG[Changelog + Impact Analysis]\nend\n\nsubgraph Sec[\"Security\"]\nACL[Subgraph Access Control]\nAUD[Query Audit Log]\nend\n\nsubgraph Qual[\"Quality\"]\nSHACL[Ingest Validation]\nMET[Weekly Metrics Review]\nGOLD[Golden Query Suite]\nend\n\nST --> PR\nPR --> CHG\nACL --> AUD\nSHACL --> MET\nMET --> GOLD\nGOLD --> ST\n```\n\n*Governance, security, and quality form a continuous loop — not one-time setup.*\n\n\n\n> Important Assign a named steward per domain ontology. Anonymous shared ownership means nobody fixes data quality.\n\n\n\n## Related Guides\n\n**Knowledge graph cluster:**\n\n- [What Is a Knowledge Graph?](https://www.dataaihub.co/learn/what-is-a-knowledge-graph) · [Knowledge Graphs](https://www.dataaihub.co/learn/knowledge-graphs) · [Learn Knowledge Graphs](https://www.dataaihub.co/learn/learn-knowledge-graphs)\n- [Enterprise Knowledge Graphs](https://www.dataaihub.co/learn/enterprise-knowledge-graphs) · [Enterprise Knowledge Graph Architecture](https://www.dataaihub.co/learn/enterprise-knowledge-graph-architecture)\n- [Ontologies](https://www.dataaihub.co/learn/ontologies) · [SHACL](https://www.dataaihub.co/learn/shacl) · [RDF](https://www.dataaihub.co/learn/rdf) · [SPARQL](https://www.dataaihub.co/learn/sparql) · [OWL](https://www.dataaihub.co/learn/owl)\n- [Graph Databases](https://www.dataaihub.co/learn/graph-databases) · [Property Graphs](https://www.dataaihub.co/learn/property-graphs) · [Cypher](https://www.dataaihub.co/learn/cypher) · [RDF vs Property Graph](https://www.dataaihub.co/learn/rdf-vs-property-graph) **AI consumption:**\n\n- [GraphRAG](https://www.dataaihub.co/learn/graphrag) · [GraphRAG Architecture](https://www.dataaihub.co/learn/graphrag-architecture)\n- [Knowledge Graph + LLM](https://www.dataaihub.co/learn/knowledge-graph-llm) · [RAG](https://www.dataaihub.co/learn/rag) **Tools and rankings:**\n\n- [Best Vector Databases](https://www.dataaihub.co/tools/rankings/best-vector-databases) · [Neo4j Vector](https://www.dataaihub.co/tools/neo4j-vector) · [LangChain](https://www.dataaihub.co/tools/langchain) · [LlamaIndex](https://www.dataaihub.co/tools/llamaindex) **Prerequisites:** [What Is a Knowledge Graph?](https://www.dataaihub.co/learn/what-is-a-knowledge-graph) · [Ontologies](https://www.dataaihub.co/learn/ontologies) · [Knowledge Graphs](https://www.dataaihub.co/learn/knowledge-graphs)\n\n**Next topics:** [SHACL](https://www.dataaihub.co/learn/shacl) · [Enterprise Knowledge Graphs](https://www.dataaihub.co/learn/enterprise-knowledge-graphs) · [Graph Databases](https://www.dataaihub.co/learn/graph-databases)\n\n\n\n## Interview Questions\n\n1. **What is the most important best practice for a new knowledge graph?** - Expected: use-case-first modeling with minimal ontology; load real data early; validate at ingest.\n2. **Why is a knowledge graph not the same as a graph database?** - Expected: KG is semantic model (ontology, governance, identity, provenance); graph DB is storage engine.\n3. **How do you handle schema changes without breaking consumers?** - Expected: additive-first; dual-write migration; version ontology in Git; impact analysis; deprecation window.\n4. **Why auto-merge entity resolution cautiously?** - Expected: false merges are hard to reverse and corrupt all downstream queries; start conservative, measure precision.\n5. **When would you use SHACL vs database constraints?** - Expected: SHACL for RDF graphs (Stardog, GraphDB, Jena); Neo4j constraints for property graphs; both at ingest.\n6. **How do best practices enable GraphRAG and RAG?** - Expected: governed entities/relationships + provenance give AI systems trustworthy structure; [RAG](https://www.dataaihub.co/learn/rag) handles documents.\n7. **What metrics indicate a graph is failing?** - Expected: rising duplicate queue, validation failure rate, orphan edges, declining query adoption, staleness.\n8. **RDF or Neo4j for a new project — how do you decide?** - Expected: RDF for SHACL/OWL/federation/compliance; Neo4j for Cypher velocity and operational traversals.\n\n## Key Takeaways\n\n- Model for concrete use cases, not the entire enterprise upfront.\n- **A knowledge graph is not a graph database** — Stardog, GraphDB, Neptune, Neo4j, and Jena store graphs; best practices govern the semantic layer above them.\n- Canonical identity and entity resolution are prerequisites for trust.\n- Validate at ingest with [SHACL](https://www.dataaihub.co/learn/shacl); measure quality continuously.\n- Schema evolution is normal — plan additive changes and migration paths.\n- Governance (stewards, versioning, PR review) matters as much as technology.\n- Provenance on every fact enables debugging, auditing, and confident [GraphRAG](https://www.dataaihub.co/learn/graphrag) / [RAG](https://www.dataaihub.co/learn/rag) grounding.\n- Compare vector tools for hybrid AI pipelines in [Best Vector Databases](https://www.dataaihub.co/tools/rankings/best-vector-databases).\n\n## FAQs\n\n\n\n### How do I start building a knowledge graph?\n\nPick one use case, model 5–15 core classes, ingest a small real dataset, validate with [SHACL](https://www.dataaihub.co/learn/shacl), and iterate based on query failures — not hypothetical future needs.\n\n\n\n### How detailed should my ontology be?\n\nDetailed enough to answer your use-case queries and enforce data quality. Avoid OWL complexity you will not use. Expand when new use cases require new types.\n\n\n\n### RDF or property graph for a new project?\n\nRDF if you need standards compliance, linked data, and SHACL validation (Stardog, GraphDB, Neptune, Jena). Property graphs if your team prioritizes Cypher ergonomics and fast traversals (Neo4j). See [What Is a Knowledge Graph?](https://www.dataaihub.co/learn/what-is-a-knowledge-graph) and [RDF vs Property Graph](https://www.dataaihub.co/learn/rdf-vs-property-graph).\n\n\n\n### How do I handle schema changes in production?\n\nAdditive changes freely. Breaking changes go through dual-write migration with consumer notification. Version ontologies in Git with changelogs.\n\n\n\n### What is the biggest mistake teams make?\n\nOver-engineering the ontology before loading data, combined with skipping entity resolution. Both erode trust before the graph delivers value.\n\n\n\n### How do I measure data quality?\n\nTrack validation failure rate, orphan edges, duplicate entity rate, attribute completeness per class, and data freshness against SLA.\n\n\n\n### When is a knowledge graph the wrong choice?\n\nWhen your data is purely tabular with no relationship traversal needs, or when source data quality is too poor to invest in cleansing. Fix data foundations first.\n\n\n\n### Can LLMs replace ontology design?\n\nNo. LLMs can extract entities from documents, but ontology structure requires domain expertise and governance. Validate all LLM extractions before production merge.\n\n\n\n### How do best practices differ for enterprise vs departmental graphs?\n\nDepartmental graphs need Levels 1–2 practices (use-case ontology, ingest validation, basic stewardship). Enterprise graphs add federated governance, MDM integration, named graph isolation, and platform SLAs — see [Enterprise Knowledge Graphs](https://www.dataaihub.co/learn/enterprise-knowledge-graphs).\n\n\n\n### Which graph database should I choose?\n\nThe engine matters less than modeling discipline. Stardog and GraphDB excel at RDF/SHACL/federation. Neo4j excels at Cypher operational graphs. Neptune offers managed AWS. Jena offers open-source standards compliance. Choose based on team skills and compliance requirements — then apply the same best practices regardless.\n\n\n\n## References\n\n- [W3C — SHACL Specification](https://www.w3.org/TR/shacl/)\n- [W3C — OWL 2 Web Ontology Language](https://www.w3.org/TR/owl2-overview/)\n- [W3C — RDF 1.1 Concepts](https://www.w3.org/TR/rdf11-concepts/)\n- [Protégé Ontology Editor](https://protege.stanford.edu/)\n- [Apache Jena Documentation](https://jena.apache.org/documentation/)\n- [Neo4j — Graph Data Modeling Guidelines](https://neo4j.com/docs/getting-started/data-modeling/)\n- [Stardog Documentation — Data Modeling](https://docs.stardog.com/)"},"author":{"name":"Data AI Hub","bio":"Practical guidelines for designing, modeling, and maintaining knowledge graphs in production - ontology design, data quality, schema evolution, and governance patterns."},"metadata":{"timestamp":"2026-07-20T00:00:00.000Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/4iM5q4ALRx/media/0.png","type":"image","width":1200,"height":630}],"aiComments":[]},{"id":"web-jhm48a","shareId":"Zjka8TAGU3","platform":"web","url":"https://ipn4.paymentus.com/cp/www/terms-and-conditions-no-fee.html","title":"Payment Authorization Terms and Conditions: Customer Portal: Paymentus Corp","shareMode":"full","createdAt":1787120967463,"postedAt":"2026-08-19T06:29:23.170Z","publishedDate":"2026-08-19T06:29:23.170Z","archivedAt":"2026-08-19T06:29:24.984Z","archivedDate":"2026-08-19T06:29:24.984Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/Zjka8TAGU3","contentType":"article","content":{"text":"## Payment Authorization Terms & E-Sign Disclosure and Consent Notice\n\nWelcome to the secure bill payment technology service provided by **Paymentus Corporation** (“Paymentus”, \"we\" or \"us\"). 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We will provide you with notice of termination or change as required by law.\n\nRevision Date: May, 2019"},"author":{"name":"ipn4.paymentus.com"},"metadata":{"timestamp":"2026-08-19T06:29:23.170Z"},"media":[],"aiComments":[]},{"id":"web-p4trlo","shareId":"HQIPmp4TU4","platform":"web","url":"https://digiwares.xyz/","title":"Small Tools That Do One Thing Well","shareMode":"full","createdAt":1786055091881,"postedAt":"2026-08-06T22:24:45.362Z","publishedDate":"2026-08-06T22:24:45.362Z","archivedAt":"2026-08-06T22:24:47.600Z","archivedDate":"2026-08-06T22:24:47.600Z","viewCount":3,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/HQIPmp4TU4","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/XlnEjllL4F/media/0.png","contentType":"article","content":{"text":"## DigiWares — Privacy-First Tools Built in Bangkok\n\nPrivacy-first utilities for voice, documents, and productivity. Many run entirely in your browser - your files never leave your device. No signup required for most tools.\n\n## // flagship\n\n- [tera.fm](https://tera.fm/) -Stop scrolling. Start listening.\n- [voicetotextonline.com](https://voicetotextonline.com/) -Speech to text in 55+ languages\n- [tickk.app](https://tickk.app/) -Speak, save, sort it later\n- [voicebraindump.app](https://voicebraindump.app/) -Speak now, organize never\n- [sornic.com](https://sornic.com/) -Turn any article, PDF, or photo into audio\n\n## // documents & privacy\n\n- [ikrypt.com](https://ikrypt.com/) -Stop DM-ing passwords. 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Voice-to-text, audio news, document utilities, and more."},"metadata":{"timestamp":"2026-08-06T22:24:45.362Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/XlnEjllL4F/media/0.png","type":"image","width":2400,"height":1260}],"aiComments":[]},{"shareId":"1hEmwZs6Eb","platform":"instagram","url":"https://www.instagram.com/p/DbbvXvZMTXV/","shareMode":"full","createdAt":1786045080757,"postedAt":"2026-07-30T22:15:46.000Z","publishedDate":"2026-07-30T22:15:46.000Z","archivedAt":"2026-08-06T19:37:20.781Z","archivedDate":"2026-08-06T19:37:20.781Z","viewCount":3,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/1hEmwZs6Eb","content":{"text":"HOME SERVICE BUSINESS DOING $75K+/MONTH!\n\nMost marketing agencies get paid whether your marketing works or not.\nWe decided that wasn't good enough.\n\nThat's why we created the Growth Lead Machine—our proven system for helping established home service companies generate predictable, high-quality booked jobs.\n\nWe're so confident in it that we'll help you generate $10,000 in new booked jobs within 30 days—or we'll continue working for free.\n\nWhy are we willing to make that promise?\n\nBecause we've done it before:\n\n✅ Accurate Leak & Line nearly doubled their monthly revenue in less than four months after implementing our Growth Lead Machine.\n\n✅ Premier Window Tinting increased their internet-generated leads by over 3,000%, creating a consistent pipeline of qualified customers.\n\nWe don't celebrate impressions.\nWe don't brag about clicks.\nWe don't count junk leads.\n\nWe measure success by what actually grows your business:\n- Qualified homeowners\n- ooked jobs\n- Predictable revenue\n- Measurable ROI\n\nIf your home service company is already doing around $1M+ annually and has the capacity to take on more work, this was built for you.\n\nClick below and apply today to see if your company qualifies for our $10,000 Booked Job Guarantee."},"author":{"name":"Billy Scott","handle":"grow_marketing_","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/da3e8abd255ccd80/avatar-2091167dd541.jpg"},"metadata":{"timestamp":"2026-07-30T22:15:46.000Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/9wm5VUCJH6/media/0.mp4","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/9wm5VUCJH6/media/thumb-0.jpg","type":"video","width":720,"height":1280}],"aiComments":[]},{"id":"t3_1s31sok","shareId":"4FpqCUvgZa","platform":"reddit","url":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ocdddwd/","title":"S&P 500 Technical View","shareMode":"full","createdAt":1786044235566,"postedAt":"2026-03-25T05:15:21.113Z","publishedDate":"2026-03-25T05:15:21.113Z","archivedAt":"2026-08-06T19:22:22.868Z","archivedDate":"2026-08-06T19:22:22.868Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/4FpqCUvgZa","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/myTYHVnpwM/media/1.jpg","contentType":"post","content":{"text":"We’re clearly seeing a shift from an uptrend into a short-term downtrend.\n\nStructure: Lower highs + lower lows forming since late Feb bearish structure confirmed\n\nResistance: 6800–6900 zone (previous supply area where price kept rejecting)\n\nSupport: 6500 is being tested right now; below that next key zone is 6400\n\nMomentum:\n\nRecent candles show strong selling pressure (multiple red candles breakdown move)\n\nAny bounce so far looks like a relief rally, not a reversal\n\nTrend Insight:\n\nThe earlier rally (Dec–Feb) has lost momentum\n\nPrice rejected near all-time highs (7000) classic distribution zone\n\nWhat I’m watching:\n\nIf 6500 breaks cleanly continuation towards 6400\n\nIf price holds 6500 and reclaims 6700+possible short-term bounce\n\nNeed a higher low break above 6800 to even think about trend reversal\n\nBias (short-term): Bearish / cautious\n\nMarket context: Geopolitics macro uncertainty = volatility stays high\n\nTL;DR:\n\nTrend flipped bearish. 6500 is key support. Break = more downside, hold = temporary bounce.\n\nRead more"},"author":{"name":"Illustrious_Lie_954","handle":"u/Illustrious_Lie_954","avatar":"https://preview.redd.it/snoovatar/avatars/f92d94d1-e781-4b03-b3f0-029a3099226f-headshot.png?width=64&height=64&crop=smart&auto=webp&s=c5dbaa6736b97a991b0c4b36680f26899883dfc6"},"metadata":{"likes":139,"shares":0,"views":0,"timestamp":"2026-03-25T05:15:21.113Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/myTYHVnpwM/media/0.jpg","r2Url":"https://social-archiver-api.social-archive.org/media/archives/arc/myTYHVnpwM/media/1.jpg","type":"image","width":2179,"height":831},{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/myTYHVnpwM/media/1.jpg","r2Url":"https://social-archiver-api.social-archive.org/media/archives/arc/myTYHVnpwM/media/1.jpg","type":"video","width":2179,"height":831}],"comments":[{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ocxyyuy/","content":"No shit","author":{"name":"keepingitreal68","username":"keepingitreal68","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-28T12:16:49.142Z","likes":1},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ocod0oc/","content":"Not looking good, folks. Gonna head even lower as people realize Tweets mean nothing, and oil and fertilizer shortages send shockwaves…","author":{"name":"NewHope13","username":"NewHope13","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-26T23:28:54.025Z","likes":1},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ochp8xi/","content":"This is too technical for the current economic landscape.. enough of a discount with positive news about the war ending.. and all the big institutions will buy the shit out of the market, rendering supply and demand zones and all that stuff worthless. Technical analysis works better on lower time frames in normal conditions.","author":{"name":"Fragtag1","username":"Fragtag1","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-26T00:07:19.728Z","likes":1,"replies":[{"id":"reply-1786044141724","content":"You’re absolutely right man. In this kind of environment TA almost doesn’t even matter anymore. Can you teach me how you trade when the market’s being moved this hard by big money?","author":{"name":"ExcellentSh","username":"ExcellentSh","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-26T16:18:04.125Z","likes":1}]},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/och2eol/","content":"It's cute to think technical analysis still means anything in the market lol the fact that Trump can swing the market either way with a simple post invalidates any real trends or signals.","author":{"name":"HoS_CaptObvious","username":"HoS_CaptObvious","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T22:06:01.862Z","likes":1},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ocg7qvn/","content":"And bulls over here just talking madddd…..","author":{"name":"parks387","username":"parks387","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T19:38:48.063Z","likes":-1},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ocfv4dt/","content":"Thank you president Dump","author":{"name":"jazzy095","username":"jazzy095","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T18:39:11.817Z","likes":2},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ocfe3fp/","content":"Lmk in 10 years","author":{"name":"Stoic_Nut","username":"Stoic_Nut","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T17:20:53.502Z","likes":1},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/oceq9wm/","content":"Zero confidence in the US market anymore, and this sentiment is growing world wide.","author":{"name":"PurpleGarbageDonkey","username":"PurpleGarbageDonkey","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T15:31:42.904Z","likes":1},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/oce537i/","content":"The S&P 500 is showing a clear shift in price behavior. After a period of consolidation near 7,000, we’re seeing a sharp breakdown below previous support levels. This downward momentum suggests sellers are currently in control as the index tests the 6,550 area.","author":{"name":"Dry_Environment_9631","username":"Dry_Environment_9631","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T13:50:56.918Z","likes":1},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/oce26va/","content":"Personally think it is much better to look at the 10-year. Clear trump put at 4.5%","author":{"name":"gamjatang111","username":"gamjatang111","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T13:36:17.683Z","likes":1},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ocdyfui/","content":"This is helpful for an overall view, but I'm seeing a basket of stocks that are doing well even in this environment. Always remember that it's a market of stocks. We're in a stock picker's market.","author":{"name":"Wide_Air_4702","username":"Wide_Air_4702","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T13:16:51.962Z","likes":4},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ocdexi8/","content":"The lion does not care about technicals","author":{"name":"Some_Edge1544","username":"Some_Edge1544","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T11:18:44.217Z","likes":-2},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ocdep1b/","content":"We wont drop that simply. We’ll do a bounce attempt for new highs, maybe even blow off on a sugar rush before the era of 7% tbills begins around 2028 The millennials will once again be the ones cleaning up the boomers shit","author":{"name":"vtsandtrooper","username":"vtsandtrooper","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T11:17:02.627Z","likes":1},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ocdbl2q/","content":"🥭 tweets are the catalyst, everything else is just algorithmic noise.","author":{"name":"Upset-Motor-2602","username":"Upset-Motor-2602","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T10:53:50.973Z","likes":1},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ocda9qh/","content":"Do people actually trade with just a bar chart like this? It's like a naked chart with barely any information.","author":{"name":"NavyDean","username":"NavyDean","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T10:43:43.563Z","likes":2,"replies":[{"id":"reply-1786044141724","content":"You can tell a lot about crowd psychology from a chart.","author":{"name":"Upset-Motor-2602","username":"Upset-Motor-2602","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T10:55:39.159Z","likes":3}]},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ocd8gv5/","content":"this whole chart is supported by AI one misstep or realignemnt of expectations in AI and it will crumble","author":{"name":"Hot_Individual5081","username":"Hot_Individual5081","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T10:29:16.235Z","likes":1},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/ocd4fj5/","content":"We are below 200 day SMA. We did not shock below like with liberation day. Liberation day was caused by a tweet and reversed with a tweet. This is not caused by words. We have real disruptions and actual war. I think we are staying under the 200 day SMA for a while.","author":{"name":"GeX_64_","username":"GeX_64_","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T09:55:21.986Z","likes":30,"replies":[{"id":"reply-1786044141724","content":"But I was told this isn’t a war. And it would be over soon. And it’s already over. And it never started. And no boots on the ground. And, and, and… Man it’s been 2 weeks and these jokes are already tired.","author":{"name":"Metals4J","username":"Metals4J","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T11:53:36.329Z","likes":7}]},{"id":"https://www.reddit.com/r/StockMarket/comments/1s31sok/comment/occwkkw/","content":"This is all worthless. Market is manipulated on a market close market open basis with scammy moves on the weekend.","author":{"name":"C_Pala","username":"C_Pala","url":"https://www.reddit.com/svc/shreddit/comments/r/StockMarket/undefined"},"timestamp":"2026-03-25T08:41:55.615Z","likes":169}],"aiComments":[]},{"id":"t3_1ohplbp","shareId":"qxXJmuGdFp","platform":"reddit","url":"https://www.reddit.com/user/Think_Reporter_8179/comments/1ohplbp/greed_just_broke_17_if_youre_laddering_out_its/","title":"Greed just broke 17 - If you're laddering out, it's time for another 20% (3 of 5 steps)","shareMode":"full","createdAt":1786044025600,"postedAt":"2025-10-27T20:29:16.267Z","publishedDate":"2025-10-27T20:29:16.267Z","archivedAt":"2026-08-06T19:20:22.741Z","archivedDate":"2026-08-06T19:20:22.741Z","viewCount":2,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/qxXJmuGdFp","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/RMxmHcofjw/media/0.webp","contentType":"post","content":{"text":"Hey everyone,\n\nJust a heads up, the Shiller PE has broken through 41 and has deviated by 17.04 from its historical trend. This is the second time in history this has occurred, the only other time being the Dot-Com Bubble of the late 1990's, where Greed went as high as 22.08 in April, 1999.\n\nJust before The Great Depression, it deviated 16.89 before the downturn.\n\nIf you want to be mathematically Fearful while everyone is Greedy, this is about as close as you're going to get.\n\nEnjoy the exuberance."},"author":{"name":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/e404c65d26347c53/avatar-531e9d4eb798.webp"},"metadata":{"likes":5,"shares":0,"views":0,"timestamp":"2025-10-27T20:29:16.267Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/RMxmHcofjw/media/0.webp","type":"image","width":640,"height":591},{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/RMxmHcofjw/media/1.webp","type":"image","width":640,"height":572},{"url":"https://www.reddit.com/gallery/1ohplbp","type":"video","width":640,"height":591}],"comments":[{"id":"https://www.reddit.com/svc/shreddit/comments/r/undefined/undefined","content":"","author":{"name":"[deleted]","username":"[deleted]","url":"https://www.reddit.com/svc/shreddit/comments/r/undefined/undefined"},"timestamp":"2025-10-28T05:20:33.054Z","likes":0,"replies":[{"id":"reply-1786044021687","content":"Better than ever","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","url":"https://www.reddit.com/svc/shreddit/comments/r/undefined/undefined"},"timestamp":"2025-10-28T11:29:41.130Z","likes":1}]},{"id":"https://www.reddit.com/user/Think_Reporter_8179/comments/1ohplbp/comment/nlpm3iw/","content":"Any guesses on what will be the thing that finally drops this market? Bond auction fail, rate hike, poor earnings, black swan?","author":{"name":"Dick_Wiener","username":"Dick_Wiener","url":"https://www.reddit.com/user/Think_Reporter_8179/comments/1ohplbp/comment/npwb3i2/?force-legacy-sct=1"},"timestamp":"2025-10-27T20:36:06.989Z","likes":1,"replies":[{"id":"reply-1786044021687","content":"Lack of incredible earnings by the major tech companies. If their earnings aren't truly incredible, it'll all fall. We're at the point where everyone is expecting to fuck a dime, and if it's \"just a 9 in a bikini\", it will no longer be good enough. My analogies might be dogshit, but I think it gets the point across. Only a 10 will do at this point, or the entire market is going to drop. The AI tech has to sell at levels to make up for the prices people are buying at . So coming back to this after Nvidia earnings what do you think? Theres people who say it’s just going to keep running until there’s competition. I mean shit, China was just caught stealing 100s of Nvidia GPUs by the FBI. If they’re that valuable, and Nvidia is like most of the market, I don’t see how it goes down. Again I have no idea what I’m talking about. Maybe. I think the capital transfer circlejerk has provided enough of a balance sheet pop to give another quarter of runway at least. I don’t think end-user AI revenue is an expectation at this point.","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179/comments/1ohplbp/comment/npwb3i2/?force-legacy-sct=1"},"timestamp":"2025-10-27T20:40:35.964Z","likes":1}]}],"aiComments":[]},{"id":"web-kfabkb","shareId":"BEJCODf6Tu","platform":"web","url":"https://hotleadalerts.com/","title":"SaaS Lead Generation Tool: Find Customers on Reddit, LinkedIn & More","shareMode":"full","createdAt":1786043930088,"postedAt":"2026-08-06T19:18:44.216Z","publishedDate":"2026-08-06T19:18:44.216Z","archivedAt":"2026-08-06T19:18:46.286Z","archivedDate":"2026-08-06T19:18:46.286Z","viewCount":3,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/BEJCODf6Tu","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/TO71LECUkv/media/0.png","contentType":"article","content":{"text":"notifications_active Real-Time Lead Generation for SaaS\n\n## SaaS Lead Generation: Find Paying Customers Fast - or Pay Nothing\n\nHotLeadAlerts monitors social media for leads and finds people asking for SaaS solutions like yours across Reddit, X, LinkedIn, and Facebook - so you reach them first, before competitors do.\n\ncheck_circle Free 7-day trial and\n60-Day Money Back Guarantee\n\n![Social listening dashboard showing hot leads from Reddit, Facebook,\nLinkedIn, Twitter, and Instagram in real time](https://hotleadalerts.com/image/catalog/main.jpg)\n\n## Stuck in the zero-customers SaaS club?Here's how lead generation for SaaS companies actually works.\n\nRight now, someone is posting on Reddit, Facebook Groups, LinkedIn, or Twitter/X asking for exactly what your SaaS does - and your competitor is about to answer them first.\nHotLeadAlerts is the **saas lead generation** tool that monitor social media for leads and finds these high-intent posts, filters out the noise, and delivers a **short, clean list of ready-to-buy leads** directly to you.\n\ntarget\n\n##### Describe Your Product & Ideal Buyer\n\nDescribe your product, who you help, and what \"ready to buy\" signals look like (frustrations with competitors, asking for alternatives, seeking specific features - anything). No exact keyword. No broad topic matching. Just your real business goals.\n\nsearch_insights\n\n##### Get a Short List of High-Intent Leads\n\nWe scan conversations across Reddit, LinkedIn, Facebook, Twitter (X), and Instagram - in real time.\nWhile other tools dump every keyword mention, our AI understands context and intent - what people are actually trying to solve.\n**Everything else gets filtered out.**\nYou get a short, clean list of conversations with the highest chance to convert.\n\ntrending_up\n\n##### Gets Smarter Over Time\n\nThe system learns from your feedback. Every time you react to a lead - good or bad - HotLeadAlerts fine-tunes itself to match what a real opportunity looks like for your business.\n\nThe more you use it, the **better the leads get**.\n\n## Try HotLeadAlerts for 2 Months Risk-Free\n\nGive HotLeadAlerts a try for 2 months. If you're not satisfied with the results, we'll give you a full refund. No questions asked.\n\nverified_user\n\nGuaranteed Results\n\n60-Day Money Back\n\n### Built by a Founder for Founders\n\n- Fair pricing - even one sale per month can cover the cost\n- Validate your SaaS idea quickly and cheaply\n\n### Why 2 Months?\n\nHotLeadAlerts gets smarter the more you use it.\n\nI built this tool to solve my own problem. If it doesn't solve yours too, you shouldn't pay for it.\n\nFree 7-day trial + 60-Day Money Back Guarantee\n\n## See the Magic: Conversations Turn Into Customers\n\nThis is exactly how HotLeadAlerts gets customers - real conversations our system discovers that turn into signups.\n\n🔍 Active Keyword ✕\n\nreddit.com \"how\" AND \"get\" AND \"users\"\n\n##### How did you get your first 1,000 users?\n\n6.0\n\nRelevance\n\nreddit.com \"how\" AND \"get\" AND \"users\"\n\n##### How to get first 50 Users?\n\n7.0\n\nRelevance\n\nreddit.com \"how\" AND \"get\" AND \"users\"\n\n##### How do you get visibility/new users for your app?\n\n7.0\n\nRelevance\n\nreddit.com \"how\" AND \"get\" AND \"users\"\n\n##### I turned my personal Excel budget into a SaaS app last week. I have 0 real users and I don't know how to get them.\n\n8.0\n\nRelevance\n\nreddit.com \"how\" AND \"get\" AND \"users\"\n\n##### For those who grew a SaaS with little to no paid marketing - how did you actually get your first users?\n\n6.0\n\nRelevance\n\nreddit.com \"how\" AND \"get\" AND \"users\"\n\n##### Built my first micro-SaaS but I'm a dev with zero marketing skills. How do I get my first 10 users?\n\n7.0\n\nRelevance\n\nFree 7-day trial. Setup takes 2 minutes.\n\n![Fast and affordable lead generation for\nfounders](https://hotleadalerts.com/image/catalog/why1.jpg)\n\n#### Get leads fast and cheap\n\nFounder-friendly pricing - only **$39/mo for 1,000 leads**. No ads, no funnels, no guesswork. Pure **SaaS lead generation** via social listening.\n\n![High-quality filtered social media leads](https://hotleadalerts.com/image/catalog/why2.jpg)\n\n#### Noise-less, high-quality leads\n\nI hate spending hours chasing low-value conversations. **4-level noise filtering** surfaces only opportunities that are worth your time - leads that actually convert.\n\n![Monitor Reddit, LinkedIn, Facebook, Twitter and\nInstagram for leads](https://hotleadalerts.com/image/catalog/why3.jpg)\n\n#### Monitor All 5 Platforms in Real Time\n\nNot just Reddit like everyone else. HotLeadAlerts tracks Reddit, X (Twitter), LinkedIn, Facebook, and Instagram - you reach potential customers **the moment they're looking for a solution**.\n\n## 5 Platforms, 1 Alert Stream\n\nMost **social listening tools** only monitor Reddit or Twitter. HotLeadAlerts monitors **all five** - so you can **find leads on social media** across all five, no matter where your next customer is asking.\n\n###### [Reddit](https://hotleadalerts.com/reddit-leads)\n\nBuyers ask for recommendations every hour\n\n###### [Facebook Groups](https://hotleadalerts.com/facebook-leads)\n\nThe most underrated B2C lead source\n\n###### [LinkedIn](https://hotleadalerts.com/linkedin-leads)\n\nB2B buyers post \"we need a solution\" publicly\n\n###### [Twitter / X](https://hotleadalerts.com/twitter-leads)\n\nCatch buying-intent tweets in real time\n\n## This Is a Lead Tool,Not a PR Tool\n\nMost [**social listening tools**](https://hotleadalerts.com/social-listening-for-leads) are built for PR teams - they track brand mentions, measure reach, and generate reports nobody reads.\n\nHotLeadAlerts is built for one thing: **finding customers who are ready to buy right now.**\n\nIf you want to know who's saying your name - use [Founderalerts](https://founderalerts.com/).\nIf you want to find your next customer - use HotLeadAlerts.\n\n| Feature | Brand Monitoring Tools | HotLeadAlerts |\n| --- | --- | --- |\n| Goal | Track brand mentions | Find buyers ready to convert |\n| Filter quality | Keyword matches | 4-level AI intent filtering |\n| Alert timing | Daily digest | Real time |\n| Platforms | 2–3 platforms | Reddit, Facebook, LinkedIn, Twitter, Instagram |\n| Price | $99–$299/mo | From $39/mo |\n\n## Who Uses Hot Lead Alerts\n\nAnyone who needs customers - not brand reports. Here's who gets the most out of our social media lead generation tool.\n\nrocket_launch\n\n##### SaaS Founders\n\nValidate your idea and get your first paying users before burning runway on ads that don't convert.\n\ncode\n\n##### Indie Hackers\n\nFind customers for your micro-SaaS without spending $1 on ads - just pure buying-intent signals from social media.\n\nbusiness_center\n\n##### Consultants\n\nRespond to prospects asking for your expertise the moment they post - before your competitors even see the thread.\n\nlaptop_mac\n\n##### Freelancers\n\nLand your next project from someone already looking for your skills - no cold email, no LinkedIn spam.\n\ngroups\n\n##### Marketing Agencies\n\nSurface warm B2B leads for your clients across all 5 platforms - and deliver results other agencies can't match.\n\nschool\n\n##### Coaches & Creators\n\nFind people asking questions only you can answer - and turn a helpful reply into a paying client.\n\nFree 7-day trial + 60-Day Money Back Guarantee. No credit card required."},"author":{"name":"Hot Lead Alerts","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/e123a3bd3c6a8f48/avatar-cec5a7df457a.png","bio":"Hot Lead Alerts is the SaaS lead generation tool that monitors Reddit, Facebook Groups, LinkedIn, Twitter/X, and Instagram for buying-intent posts - reach customers before your competitors. 2-month risk-free."},"metadata":{"timestamp":"2026-08-06T19:18:44.216Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/TO71LECUkv/media/0.png","type":"image","width":205,"height":43}],"aiComments":[]},{"id":"web-nwzu00","shareId":"IokXPP05vH","platform":"web","url":"https://customersproof.com/?mlft=261b2438a67be68b534b089e772a4350-57","title":"Replace 7 customer tools with one cockpit","shareMode":"full","createdAt":1786043921981,"postedAt":"2026-08-06T19:18:35.737Z","publishedDate":"2026-08-06T19:18:35.737Z","archivedAt":"2026-08-06T19:18:37.843Z","archivedDate":"2026-08-06T19:18:37.843Z","viewCount":1,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/IokXPP05vH","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/17bumzRSuw/media/0.png","contentType":"article","content":{"text":"## Founders shouldn’t manage customers across 7 different tools.\n\nMost founders start simple, then slowly accumulate tools for support, feedback, roadmap, analytics, and announcements. Each one adds another dashboard, another login, and another place where customer context gets lost. CustomersProof replaces that fragmented workflow with one system.\n\n## See every customer across all your projects - live.\n\nStop checking multiple inboxes, dashboards, and email threads just to stay on top of customer activity. CustomersProof automatically brings support chats, bug reports, feature requests, testimonials, and visitor activity from all your projects into one real-time control center.\n\nWhy founders love this\n\nEverything updates live\n\nNew chats, votes, reviews, and bug reports appear instantly across all projects.\n\nOne inbox for every project\n\nManage multiple SaaS products, client projects, or side businesses from one screen.\n\nNever miss customer signals\n\nSee support requests, feature demand, churn risks, and positive feedback the moment they happen.\n\napp.customersproof.com / projects\n\nLive\n\n![Multi-project dashboard with live activity from all your projects](https://customersproof.com/image/catalog/multi-project-dashboard.jpg)\n\nEverything updates in real time across every project you manage.\n\n## Your all-in-one customer management cockpit.\n\nReplace 5-7 separate SaaS subscriptions. Every widget, page, and popup is 100% customizable to match your brand.\n\n### Collect, manage, and showcase testimonials\n\nEverything you need for social proof in one place. Smart Auto-Collect proactively asks for reviews at strategic moments in the customer journey - boosting collection by dozens of percent vs passive widgets. Bulk-import the reviews you already have from dozens of sources. Then showcase your wall of love with 10 fully customizable widgets anywhere on your site.\n\n- Smart auto-collect at strategic customer-journey moments - toggle on or off any time\n- 10 customizable showcase widgets - masonry wall, carousel, rating badge, video grid, and more\n- Bulk import from dozens of sources - Google, G2, Trustpilot, Capterra, Twitter, Facebook, Instagram, YouTube, ProductHunt, and more, plus CSV\n- Collect via widget, hosted \"wall of love\" you share by URL, or in-app prompt\n\n![Testimonials wall - customer reviews with stars and avatars](https://customersproof.com/image/catalog/landing/testimonials.png)\n\n### Customer support that builds loyalty\n\nHappy customers stay. Customer support isn't about closing tickets fast - it's about making people feel heard, understood, and looked after. CustomersProof gives your customers every way to reach you - a chat bubble on your site, a hosted contact page they can email or share by URL, an embeddable contact form - and gives you one inbox to manage all of it, from a quick chat reply to a multi-step ticket.\n\n- Every channel in one inbox - chat widget, hosted contact page, embeddable form, direct email\n- Reply in live-chat mode for quick answers, or switch to ticketing mode with statuses, priorities, and assignment for complex cases\n- Internal notes hidden from customers - pinned to a customer or a specific ticket, so context never gets lost between handoffs\n- Statuses (open / responded / closed) and priority levels (low / regular / high) to keep your inbox triaged\n\n![Support chat thread with status, importance and internal notes](https://customersproof.com/image/catalog/landing/support.jpg)\n\n### Bug reports\n\nCustomers hate writing detailed bug reports - so most bugs never get reported. CustomersProof gives them a simple report button anywhere you put it (widget, hosted page, or shared URL), and you manage the whole triage queue in your dashboard. No more \"it broke but I don't know what I clicked\" tickets.\n\n- Multiple capture surfaces - embedded widget on any page, hosted bug-report page (share by URL or email), in-app form\n- Customers report bugs with a screenshot and a short description - no technical jargon required\n- Manage statuses (new / in progress / resolved) and add private internal notes for your team\n- 100% customizable look - match your brand colors and design\nSlack alerts firing twice for the same trigger\n\nvia widget · screenshot attached · 11h ago\n\nNew CSV export cuts off long reviews\n\nvia hosted page · reproduced · 2d\n\nIn progress Mobile dashboard hides delete button\n\nvia in-app form · fixed in v2.4 · 5d\n\nResolved\n\n### Feature requests & voting\n\nStop guessing what to build next. Let your customers submit ideas, vote on what matters, and comment to add context - so every sprint ships what people actually want. When a request is ready to ship, one click promotes it straight to your public roadmap. No copy-pasting between tools.\n\n- One-click promote any feature request to your public roadmap - and demote back if priorities change\n- Public board with vote counts, comments, and threaded discussion\n- Multiple capture surfaces - widget on any page, hosted feature page (share by URL), in-app submission\n- 100% customizable look - colors, layout, status labels - match your brand\n\n![Feature requests list with up-vote arrows and status badges](https://customersproof.com/image/catalog/landing/feature.jpg)\n\n### Public roadmap\n\nA public roadmap turns your product into a conversation. Customers see what's coming, vote on priorities, and watch their requests move from *Planned → Building → Shipped*. You have full control over the stages - add, rename, reorder, recolor them to match your process.\n\n- Fully customizable stages - add, edit, remove, reorder columns to fit your workflow\n- Embed on your site OR share a hosted roadmap page by URL - works anywhere\n- Users vote and comment on roadmap items - no separate tool needed\n- 100% customizable design - colors, fonts, stage names - match your brand\n\n![Public roadmap kanban - Review, Planned, In Progress columns](https://customersproof.com/image/catalog/landing/roadmap.jpg)\n\n### Announcements that always arrive\n\nEvery release is a chance to bring customers back - but email tools are expensive and your messages keep landing in spam. CustomersProof delivers announcements directly inside your product, where users actually see them. No newsletter fees, no spam filters, no deliverability anxiety.\n\n- Direct in-app delivery - personal, instant, never sent to spam\n- Cancel your newsletter subscription for product updates - save $20-200/mo on email tooling\n- Multiple formats - banner at the top of the page, modal popup, or in-app message - pick what fits\n- 100% customizable design - colors, fonts, CTAs - match your product UI exactly\nv2.4 - Webhooks are live\n\nSent Spring sale - 20% off basic plans\n\nModal popup · brand-matched design\n\nSent We miss you - here's what's new\n\nIn-app message · no Mailchimp needed\n\nScheduled\n\n### Visitor & conversion tracking\n\nAll your traffic data, conversion funnels, and ROI metrics in one place - sitting next to the customers and conversations those numbers represent. See who's on your site right now, track every conversion goal, and measure ROI on every channel. No cookie banner, GDPR-safe.\n\n- Live visitor view - see who's on your site right now, where they came from, what page they're on\n- Conversion goals + funnels - visitor → signup → paid, with drop-off rate at every step\n- ROI by traffic source - know which channels make money, not just which bring clicks\n- Privacy-friendly - no cookie banner needed, GDPR-safe out of the box\n· 1,486 visitors · 28 conversions (1.9%) · **7 users live now**"},"author":{"name":"CustomersProof","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/fb676022a9d96fa6/avatar-197de1b8a902.png","bio":"Replace 7 customer tools with one cockpit: support, testimonials, bug reports, feature voting, roadmap & analytics. Free 7-day trial, no card needed."},"metadata":{"timestamp":"2026-08-06T19:18:35.737Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/17bumzRSuw/media/0.png","type":"image","width":300,"height":94}],"aiComments":[]},{"id":"web-e2oy1j","shareId":"KjhQ3gzmGx","platform":"web","url":"https://cashcowleads.com/#pricing-section","title":"CashCow Leads — the AI employee that turns Facebook into a lead machine","shareMode":"full","createdAt":1786043877909,"postedAt":"2026-08-06T19:17:50.226Z","publishedDate":"2026-08-06T19:17:50.226Z","archivedAt":"2026-08-06T19:17:52.551Z","archivedDate":"2026-08-06T19:17:52.551Z","viewCount":1,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/KjhQ3gzmGx","contentType":"article","content":{"text":"🔧\n\nPlumbing\n\nleads cost\n\n$10/lead\n\n⚡\n\nElectrical\n\nleads cost\n\n$10/lead\n\n📣\n\nMarketing\n\nleads cost\n\n$10/lead\n\n🏠\n\nRenovation\n\nleads cost\n\n$10/lead\n\n💻\n\nWeb Design\n\nleads cost\n\n$10/lead\n\n🌿\n\nLandscaping\n\nleads cost\n\n$10/lead\n\n🧹\n\nCleaning\n\nleads cost\n\n$10/lead\n\n🔒\n\nSecurity\n\nleads cost\n\n$10/lead\n\n🚗\n\nAuto Repair\n\nleads cost\n\n$10/lead\n\n🐾\n\nPet Services\n\nleads cost\n\n$10/lead\n\n📸\n\nPhotography\n\nleads cost\n\n$10/lead\n\n🍽️\n\nCatering\n\nleads cost\n\n$10/lead\n\n📦\n\nMoving\n\nleads cost\n\n$10/lead\n\n🖥️\n\nIT Support\n\nleads cost\n\n$10/lead\n\n📊\n\nAccounting\n\nleads cost\n\n$10/lead\n\n❄️\n\nHVAC\n\nleads cost\n\n$10/lead\n\n⚖️\n\nLegal Services\n\nleads cost\n\n$10/lead\n\n🐜\n\nPest Control\n\nleads cost\n\n$10/lead\n\n🏘️\n\nRoofing & Siding\n\nleads cost\n\n$10/lead\n\n🎨\n\nPainting & Decorating\n\nleads cost\n\n$10/lead\n\n🎉\n\nEvent Planning\n\nleads cost\n\n$10/lead\n\n💪\n\nFitness & Training\n\nleads cost\n\n$10/lead\n\n💇\n\nHair & Beauty\n\nleads cost\n\n$10/lead\n\n🧠\n\nTherapy & Counseling\n\nleads cost\n\n$10/lead\n\n📚\n\nTutoring & Education\n\nleads cost\n\n$10/lead\n\n🛋️\n\nInterior Design\n\nleads cost\n\n$10/lead\n\n🗑️\n\nJunk Removal\n\nleads cost\n\n$10/lead\n\n💡\n\nSmart Home\n\nleads cost\n\n$10/lead\n\n🔑\n\nLocksmith\n\nleads cost\n\n$10/lead\n\n🚚\n\nCourier & Delivery\n\nleads cost\n\n$10/lead\n\nDon't want to wait? Buy leads on the spot.\n\nBrowse a live pool of leads across **every niche we cover** — filter by category and location, and buy only the ones you want. Leads start at just **$2.50** and never cost more than **$10.00**.\n\n🛒 Marketplace\n\nBrowse and buy leads by category and location\n\n💰 Balance: **$339.00**\n\nAll\n\nPlumbing\n\nElectrical\n\nMarketing\n\nRenovation\n\nWeb Design\n\nLandscaping\n\nCleaning\n\nSecurity\n\nAuto Repair\n\nPet Services\n\nPhotography\n\nCatering\n\nMoving\n\nIT Support\n\nAccounting\n\nHVAC (Heating & Cooling)\n\nLegal Services\n\nPest Control\n\nRoofing & Siding\n\nPainting & Decorating\n\nEvent Planning\n\nFitness & Personal Training\n\nHair & Beauty Services\n\nTherapy & Counseling\n\nTutoring & Education\n\nInterior Design\n\nJunk Removal & Hauling\n\nSmart Home & Automation\n\nLocksmith Services\n\nCourier & Delivery Services\n\n422 leads found\n\nLandscapingWarm Lead\n\nLooking for yard work or landscaping opportunities.\n\n$2.50\n\nPosted todayExpires in 30 days\n\n[Purchase Lead](https://cashcowleads.com/signup)\nLandscapingCold Lead\n\nLooking for advice on maintaining new Bermuda grass.\n\n📍 Georgia\n\n$10.00\n\nPosted todayExpires in 30 days\n\n[Purchase Lead](https://cashcowleads.com/signup)\nLandscapingHot Lead\n\nNeed tilling and leveling before sod installation.\n\n📍 Atlanta, GA\n\n$2.50\n\nPosted todayExpires in 30 days\n\n[Purchase Lead](https://cashcowleads.com/signup)\nMarketingHot Lead\n\nNeed an agency to run Google Ads — $2k/mo budget.\n\n📍 Dallas, TX\n\n$10.00\n\nPosted todayExpires in 30 days\n\n[Purchase Lead](https://cashcowleads.com/signup)\nElectricalWarm Lead\n\nBreaker tripping nightly — need an evening electrician.\n\n📍 Phoenix, AZ\n\n$7.50\n\nPosted todayExpires in 30 days\n\n[Purchase Lead](https://cashcowleads.com/signup)\nWeb DesignHot Lead\n\nFull site rebuild needed in 4 weeks, budget approved.\n\n📍 Atlanta, GA\n\n$10.00\n\nPosted todayExpires in 30 days\n\n[Purchase Lead](https://cashcowleads.com/signup)\nEvery lead priced between $2.50 and $10.00 · Pay per lead · No monthly fee\n\nReal people. Real requests. Caught in real time.\n\nThis is what your AI employee pulls out of local Facebook groups every single day — people asking, in their own words, for exactly what you sell.\n\n👩\n\nDanielle M.\n\n📍 Austin Homeowners · 12.4k members\n\n“Need a **good local plumber** ASAP — kitchen sink has been leaking for 3 days. Happy to pay for same-day service!”\n\n🔧 Plumbing⚡ Urgent💰 Ready to Pay\n\n23 min ago\n\n🧔\n\nRay T.\n\n📍 Dallas Biz Network · 5.8k members\n\n“Anyone know a solid **marketing agency**? We need someone to run our Google Ads. Budget is around $2k/mo, ongoing.”\n\n📢 Marketing💰 High Budget🔁 Retainer\n\n41 min ago\n\n👵\n\nMarlene O.\n\n📍 Phoenix Neighbors · 22.1k members\n\n“My breaker keeps tripping every night and I'm honestly nervous about it. Can someone recommend an **electrician** who does evenings?”\n\n⚡ Electrical🚨 Emergency📍 Local\n\n1 hr ago\n\n👨💼\n\nChris B.\n\n📍 Atlanta Startup Hub · 9.3k members\n\n“Looking for a **web designer** to rebuild our site. Need it done in 4 weeks, we have budget approved already.”\n\n💻 Web Design💰 Budget Approved⏳ Deadline\n\n1 hr ago\n\n👩🦰\n\nSofia R.\n\n📍 Tampa Moms Group · 31.7k members\n\n“Who do y'all use for **lawn care**? Ours is out of control and I need someone reliable every two weeks.”\n\n🌳 Landscaping🔁 Recurring⭐ Referral Ask\n\n2 hrs ago\n\n🧔\n\nDevon W.\n\n📍 Denver Home Reno · 7.2k members\n\n“Just closed on a fixer-upper. Need a **general contractor** for a full kitchen gut. Serious quotes only please.”\n\n🏠 Renovation💰 Big Ticket📍 Local\n\n3 hrs ago\n\n👩💻\n\nNina P.\n\n📍 Seattle Small Biz · 4.6k members\n\n“Our office needs a **weekly cleaning crew** starting next month. Anyone have someone they'd vouch for?”\n\n🧺 Cleaning🔁 Recurring📅 Starts Soon\n\n4 hrs ago\n\n🧓\n\nWalter H.\n\n📍 Nashville Neighbors · 18.9k members\n\n“AC died in the middle of this heat wave. Need an **HVAC tech** out here today — I'll pay the emergency rate, no problem.”\n\n❄️ HVAC🚨 Emergency💰 Ready to Pay\n\n5 hrs ago\n\n👩🏫\n\nAmara J.\n\n📍 Charlotte Parents · 26.3k members\n\n“My son is struggling with algebra and finals are coming. Looking for a **math tutor** — twice a week, in person preferred.”\n\n📚 Tutoring🔁 Recurring⏳ Deadline\n\n6 hrs ago\n\nThree steps. Zero effort on your end.\n\nSet it up in two minutes. After that, your AI employee does everything.\n\n1\n\n📋\n\nTell us your city & services\n\nPick your metro areas and service categories. Takes two minutes and it's the last time you'll need to do anything.\n\n2\n\n🤖\n\nAI scans Facebook groups 24/7\n\nOur AI monitors hundreds of local groups, reading every post around the clock for people who need what you offer.\n\n3\n\n📧\n\nWe email you the lead\n\nWithin 24 hours — the original post, the poster's name, location, and a direct link to respond first.\n\nIf locals ask for it on Facebook, we find it.\n\nFrom urgent plumbing calls to month-long marketing retainers — our AI catches every professional service request in your area.\n\n🔧Plumbing\n\n⚡Electrical\n\n📢Marketing\n\n🏠Renovation\n\n💻Web Design\n\n🌳Landscaping\n\n🧺Cleaning\n\n🔒Security\n\n🚗Auto Repair\n\n🐕Pet Services\n\n📷Photography\n\n🍰Catering\n\n📦Moving\n\n🖥️IT Support\n\n⚖️Legal\n\n💰Accounting\n\n🏋️Personal Training\n\n✂️Hair & Beauty\n\n📚Tutoring\n\n＋Many more\n\nReal businesses. Real jobs closed.\n\n★★★★★ **4.9** out of 5 · based on 1,840+ reviews\n\n★★★★★\n\n“I got a $2,400 plumbing job from a lead on my first day. The woman posted in a neighborhood group and I was the first plumber to message her.”\n\n🔧\n\nMarcus D.\n\nPlumber · Houston, TX\n\n★★★★★\n\n“CashCow Leads replaced cold outreach entirely. We get warm inbound leads every single day — people who are actively looking.”\n\n📢\n\nPriya K.\n\nMarketing Agency · Atlanta, GA\n\n★★★★★\n\n“Someone posted at 11pm asking for an electrician — I got the alert at 11:04, and by morning had a $5,800 signed contract.”\n\n⚡\n\nTyler R.\n\nElectrician · Phoenix, AZ\n\n★★★★★\n\n“The marketplace is the sleeper feature. I grab three or four leads for a couple bucks each on slow weeks and it fills my whole calendar.”\n\n🌳\n\nJamal W.\n\nLandscaper · Tampa, FL\n\n★★★★★\n\n“I used to spend two hours a night scrolling groups myself. Now it just shows up in my inbox. That time back is worth more than the lead cost.”\n\n🏠\n\nRebecca L.\n\nGeneral Contractor · Denver, CO\n\n★★★★★\n\n“Not every lead closes — that's just sales. But at $10 I only need one job a month to be way ahead. We're booked out six weeks now.”\n\n🧺\n\nOwen S.\n\nCleaning Company · Seattle, WA\n\nThe simplest pricing in the industry.\n\nNo subscriptions. No monthly bill. Only charged when we deliver a real lead.\n\n$ 10 /lead\n\nOnly charged when a lead is delivered\n\n**Pay as you go.**Upload your card, turn your campaign on, and we'll email leads straight to you.\n\nEstimate your monthly spend **20 leads / mo**\n\n150100150200+\n\n**20** leads / mo\n\n**$200** est. monthly spend\n\n**$10** per lead\n\nA single closed job typically covers **40+** leads — most customers are profitable from week one.\n\n✓ Unlimited cities monitored\n\n✓ Unlimited service categories\n\n✓ Email alert within 24 hours\n\n✓ Original post forwarded\n\n✓ Poster name & location included\n\n✓ Direct link to respond instantly\n\n✓ Lead quality scoring included\n\n✓ Marketplace access included\n\n✓ Turn campaigns on/off anytime\n\n✓ No contracts, no minimums"},"author":{"name":"cashcowleads.com"},"metadata":{"timestamp":"2026-08-06T19:17:50.226Z"},"media":[],"aiComments":[]},{"id":"web-xdnxnb","shareId":"9GZJtSo5E9","platform":"web","url":"https://trendwatchers.co/#twlp-pricing","title":"Trend Watchers - Go Viral With Trends","shareMode":"full","createdAt":1786043871169,"postedAt":"2023-05-02T05:44:24.000Z","publishedDate":"2023-05-02T05:44:24.000Z","archivedAt":"2026-08-06T19:17:45.066Z","archivedDate":"2026-08-06T19:17:45.066Z","viewCount":1,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/9GZJtSo5E9","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/oV7KRMfUHA/media/0.jpg","contentType":"article","content":{"text":"100+\n\nVideos per batch\n\nGenerate a full month of content in one session\n\n<10 min\n\nRaw footage to viral\n\nFrom upload to 100 finished videos in minutes\n\n30+\n\nTemplate categories\n\nEvery niche covered, new templates added weekly\n\n3\n\nPlatforms supported\n\nTikTok, Instagram Reels & YouTube Shorts\n\n0\n\nEditing skills needed\n\nAI does all the work — just upload and download\n\n## Three steps.One month of content.\n\nStep 01\n\nUpload your footage\n\nDrop any raw B-roll clips into Trend Watchers. No prep needed — unedited footage works perfectly.\n\n⚡ Under 60 seconds\n\nStep 02\n\nAI applies templates\n\nOur AI instantly matches your clips to trending templates from our 30+ category marketplace, automatically.\n\n⚡ 90 seconds to process\n\nStep 03\n\nDownload & go viral\n\nDownload up to 100 finished, platform-optimized videos ready for TikTok, Instagram, and YouTube.\n\n⚡ 100 videos at once\n\n## Every niche. Every trend. 30+ categories.\n\nNew viral templates added weekly — engineered to stop the scroll in every niche.\n\n## Built for creatorswho move fast.\n\n🍕\n\n### Food & Restaurant\n\nTurn food footage into high-converting shorts that drive foot traffic, orders, and reservations.\n\n✈\n\n### Travel Creators\n\nTransform destination clips into viral travel shorts with templates optimized for what people search.\n\n💪\n\n### Fitness Creators\n\nEdit workout footage into shorts that explode across TikTok, Reels, and YouTube Shorts at once.\n\n🏪\n\n### Local Businesses\n\nBecome the go-to destination in your area with professional content that outpaces every competitor.\n\n🎯\n\n### Personal Brands\n\nTurn thought leadership footage into high-performing shorts that build authority across every platform.\n\n🛒\n\n### Lifestyle Creators\n\nGenerate months of viral lifestyle content in one session — the consistent schedule that actually ranks.\n\n## Real creators.Real results.\n\n★★★★★\n\nI made 87 videos in one afternoon. My content schedule is fully covered for the next 6 weeks. This changed everything for my restaurant's TikTok.\n\nMK\n\nMarcus K.\n\nFood Creator · 142K followers\n\n★★★★★\n\nThe food template category alone got my client 3 million views in a week. I now run 12 accounts and Trend Watchers is the backbone of all of them.\n\n★★★★★\n\nWent from posting twice a week to 14 times across 3 platforms. My gym's TikTok hit 50K followers in 30 days using the fitness templates.\n\nDJ\n\nDarius J.\n\nFitness Creator · 51K followers\n\n★★★★★\n\nI was spending 20 hours a week editing videos for my boutique. Now I spend 20 minutes and get 60+ pieces of content. The ROI is completely insane.\n\nSR\n\nSofia R.\n\nFashion Creator · 89K followers\n\n★★★★★\n\nOur travel agency went from invisible to 200K views a month on TikTok. The travel templates are dialed in — they hook people in the first second every time.\n\nTN\n\nTyler N.\n\nTravel Creator · 203K followers\n\n★★★★★\n\nI manage content for 8 local businesses. Trend Watchers cut my production time by 90%. Every single client has seen a massive jump in reach since we started.\n\nJM\n\nJordan M.\n\nContent Agency Owner\n\n## Simple pricing.Serious output.\n\n1 credit = 1 video of any size & length\n\nor buy extra credits anytime\n\n⚡ Buy Extra Credits\n\nNo subscription needed · Valid 1 year · 1 credit = 1 video\n\n$0.60\n\nper video\n\n🕐 Time you'll save\n\n31h 40m\n\n🌿 Editing cost saved\n\n$1,400\n\nCredits100 videos\n\nPer video$0.60\n\nTotal charge$60.00\n\n🔒 Charged immediately · Secure checkout via Stripe · Credits valid for 1 year"},"author":{"name":"Trend Watchers","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/7e841e30f636fde2/avatar-444d23b03132.png","bio":"The #1 Bulk AI Editor for Viral Short-Form Content. Built for Lifestyle, Travel, Fitness, and Food Creators. Drop raw footage into viral-ready templates"},"metadata":{"timestamp":"2023-05-02T05:44:24.000Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/oV7KRMfUHA/media/0.jpg","type":"image","width":1170,"height":1335}],"aiComments":[]},{"id":"1jrgqns","shareId":"eTjMc8zit9","platform":"reddit","url":"https://www.reddit.com/r/u_Think_Reporter_8179/comments/1jrgqns/whitepaper_the_greedfear_residual_strategy/","title":"Whitepaper: The Greed/Fear Residual Strategy","shareMode":"full","createdAt":1786043796721,"postedAt":"2025-04-04T16:54:42.000Z","publishedDate":"2025-04-04T16:54:42.000Z","archivedAt":"2026-08-06T19:16:28.969Z","archivedDate":"2026-08-06T19:16:28.969Z","viewCount":3,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/eTjMc8zit9","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/ZcHnfIUQ8X/00-image.jpg","contentType":"article","content":{"text":"# The Greed/Fear Residual Strategy\n\nA Quantitative Model for Timing Market Extremes, by Think\\_Reporter\\_8179\n\n[Raw data here ](https://docs.google.com/spreadsheets/d/1asVTn8TUOWKwli_w7n8r6-CNZQv0vzhgcJPuTF1tHBU/edit?usp=sharing)\n\n# Overview\n\nThis strategy builds on the foundational work of economist Robert Shiller and his widely recognized Cyclically-Adjusted Price-to-Earnings ratio (CAPE) also known as Shiller PE. The Shiller PE smooths out earnings over a 10-year period to adjust for economic cycles, offering a more stable signal of market valuation than traditional P/E ratios.\n\nResidual Concept:\n\nWhile the Shiller PE is a powerful tool, it exhibits a general upward trend over time due to long-term economic growth, inflation, and shifts in market structure. To adjust for this and extract meaningful overvaluation signals, a linear regression was applied to the full historical Shiller PE dataset (1871–present). This regression line represents the expected value of the Shiller PE based on its historical trajectory. The “Greed/Fear” value is the deviation above and below this trend. (Figure1, bottom graph)\n\n# Variants\n\nThe 20/4 variant - This optimized strategy exits the market when the Greed/Fear Number exceeds 20 and re-enters when it drops below 4. It represents extremely rare euphoria and deep pessimism. Despite only triggering two exits historically, it consistently outperforms Buy & Hold from 1940 onward. CAGR since 1980 is 9.67% compared to 9.11% for Buy & Hold.\n\nThe 15/4 variant - This variant exits the market more frequently—whenever the Greed/Fear Number exceeds 15 and re-enters below 4. It also consistently outperforms Buy & Hold across the modern market era. CAGR since 1980 is 9.61%, with 7.73% since 1940, making it a strong alternative for more active positioning. (Figure 2, images 1 & 2)\n\nWhile Buy & Hold remains robust, these Greed/Fear threshold strategies demonstrate that valuation-based sentiment timing can improve long-term returns. The 20/4 model is best for minimalist investors. The 15/4 model balances performance and responsiveness. Both outperform Buy & Hold from 1940 and 1980 onward.\n\n**Procedure**\n\nLet PE(t) be the Shiller PE at time t. Let L(t) = a + bt be the best-fit linear regression of PE(t) over time. I define the residual R(t) = PE(t) - L(t). This residual represents the deviation from the trend—a proxy for market sentiment.\n\nInterpreting Residuals:\n\n\\- When R(t) >> 0: the market is overvalued relative to trend (potential euphoria or bubble).\n\n\\- When R(t) << 0: the market is undervalued (panic or capitulation).\n\n\\- When R(t) \\~ 0: the market is roughly in equilibrium with its long-term valuation.\n\n**Strategy**\n\nUsing empirical analysis, I observed that high positive residuals (e.g., R > 15 or R > 20) often precede sharp market declines, typically within 3–6 months. I also found that low residuals (e.g., R < 4) correlate with market bottoms and recovery periods. The strategy is to:\n\n1. Exit the market when R(t) > X (e.g., X = 15 or 20).\n2. Re-enter the market when R(t) < Y (e.g., Y = 4).\n\nBack testing and Results:\n\nAcross historical time frames beginning in 1900, 1940, 1970, 1980, and 1990, the 20/4 and 15/4 strategies consistently outperformed Buy & Hold. For example, from 1980 onward (Figure 2, image 3):\n\n\\- Buy & Hold CAGR: 9.11%\n\n\\- 20/4 Strategy CAGR: 9.67%\n\n\\- 15/4 Strategy CAGR: 9.61%\n\n\\- Great Depression modeling was done as well from 1900 - 1940 (Figure 3)\n\nWhy It Works:\n\nThe strategy is effective because it systematically avoids periods of extreme overvaluation while reinvesting during pessimistic lows. It does not require forecasting future earnings or macro conditions—only a valuation signal derived from historical behavior. The approach is both statistically grounded and operationally simple, requiring monitoring of a single residual metric derived from the Shiller PE.\n\n**Conclusion**\n\nThis model represents a practical synthesis of valuation theory and behavioral finance. By using a regression-adjusted Shiller PE residual, I normalize for historical bias and extract actionable sentiment. The resulting strategy is robust, transparent, and repeatable—making it a compelling alternative to traditional Buy & Hold for long-term investors.\n\nFigure 1:\n\n[Top graph is \\\\\"Greed\\/Fear\\\\\" residual of Shiller PE, including the \\\\\"15\\/4 Strategy\\\\\" delineations. Bottom graph is the Shiller PE historical data with its trend. The \\\\\"Greed\\/Fear\\\\\" value is derived from this.](https://preview.redd.it/iwkfrotxdvse1.png?width=3343&format=png&auto=webp&s=15b0d9c9692a51f8264387b581fdb1eb4590f410)\n\n[Figure 2](https://www.reddit.com/user/Think_Reporter_8179/comments/1jlee7w/greedfear_154_strategy_back_tested_analysis_it/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button)\n\n[Figure 3](https://www.reddit.com/user/Think_Reporter_8179/comments/1jo4ldy/greedfear_154_strategy_backtested_during_the/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button)"},"author":{"name":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","avatar":"https://styles.redditmedia.com/t5_4rlgod/styles/profileIcon_4convnvkxrjd1.jpeg"},"metadata":{"likes":25,"shares":0,"views":0,"timestamp":"2025-04-04T16:54:42.000Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/ZcHnfIUQ8X/00-image.jpg","r2Url":"https://social-archiver-api.social-archive.org/media/archives/arc/ZcHnfIUQ8X/00-image.jpg","type":"image","width":1200,"height":630}],"comments":[{"id":"mlyfwpc","content":"couple of questions:\n\n1. what occurs, for example, when one sells out when above 15, but greed/fear does not go below 4 to trigger buy back? do you hold cash in anticipation of a further fall?\n\n2. is this tracked using the S&P 500 or the DOW?","author":{"name":"oscarony","username":"oscarony","handle":"u/oscarony","url":"https://www.reddit.com/user/oscarony"},"timestamp":"2025-04-08T00:36:24.000Z","likes":2,"replies":[{"id":"mlz6l7h","content":"1. It is inevitable it will drop below 4 at some point. Even waiting the longest recorded time of 4.25 years during the Dot-Com bubble, pulling out at 15, reinvesting that withdrawn amount back at 4 GF, 4.25 years later, still resulted in a larger CAGR versus B&H. That said, the Dot-Com bubble was a wild exception of millennium euphoria (also noted in a smaller capacity in 1899, by the way) that lasted 49 months. The others have been 10, 17 and 12 months. \n\n\n2. The S&P 500.\n\nSimply put, the bigger the bubble, the harder the fall. If one does not pull out at 15 or higher, they will ultimately not have as much as a person that pulls out, even if early, and waits for the cheap time.\n\nThis also appears to be what Warren Buffet has done and is doing.","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179"},"timestamp":"2025-04-08T03:23:24.000Z","likes":2,"replies":[{"id":"mm3mlqz","content":"thank you for the explanation. next two questions \n\n1. seems like shorting the market or buying long-dated puts on overvalued, high beta stocks would be really profitable once G/F hits 15, is that what you’re currently doing? and basically planning to flip from short to long when G/F hits 4?\n\n2. is the number to hop back in (G/F = 4) SPY at 480?","author":{"name":"oscarony","username":"oscarony","handle":"u/oscarony","url":"https://www.reddit.com/user/oscarony"},"timestamp":"2025-04-08T20:51:54.000Z","likes":1,"replies":[{"id":"mm3w83g","content":"1. That could be a lucrative strategy yes, but it's not what I'm doing. I pulled out and have held onto a large chunk of cash. I'm more a Warren Buffett slow-burn type investor, but theoretically it would likely turn out well if someone did this anytime the market touched 15+ G/F. I started re-entering the market two days ago in small chunks. I added more today, and will continue at each whole G/F number until we hit ~$4500 (which is right around G/F 4, to answer your second question).\n\n2. Definitely not 480. Lol. If you meant 4800, it's more around $4500. See the chart on the right side of the raw data.","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179"},"timestamp":"2025-04-08T21:40:17.000Z","likes":1}]}]}]},{"id":"n3lbevd","content":"does this work for single equities using diluted EPS and CPI data? assuming no negative earnings…","author":{"name":"liquid_bee_3","username":"liquid_bee_3","handle":"u/liquid_bee_3","url":"https://www.reddit.com/user/liquid_bee_3"},"timestamp":"2025-07-17T07:37:41.000Z","likes":2,"replies":[{"id":"n3m3i5l","content":"No. It's based on the Shiller PE which is a behavioral measure of irrational exuberance in the market as a whole. It cannot be used to predict how humans will behave with a single equity, only how they behave with the stock market in general.","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179"},"timestamp":"2025-07-17T11:40:41.000Z","likes":2}]},{"id":"oi7t923","content":"I just found this post and I'm finding it very useful to get a perspective of where market valuations are at, especially going back through the decades. The raw excel file is very nice and it seems like it is still being updated. Is this being done by hand or do you have something setup to pull the numbers automatically?","author":{"name":"much_snark_very_wow","username":"much_snark_very_wow","handle":"u/much_snark_very_wow","url":"https://www.reddit.com/user/much_snark_very_wow"},"timestamp":"2026-04-25T15:47:57.000Z","likes":2,"replies":[{"id":"oialmtr","content":"By hand","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179"},"timestamp":"2026-04-26T00:33:12.000Z","likes":2,"replies":[{"id":"oiate3j","content":"You are the MVP. What's shocking to me is how many \"green\" periods we had that ran for decades. Now it's just all red.","author":{"name":"much_snark_very_wow","username":"much_snark_very_wow","handle":"u/much_snark_very_wow","url":"https://www.reddit.com/user/much_snark_very_wow"},"timestamp":"2026-04-26T01:20:51.000Z","likes":1}]}]},{"id":"mnkciov","content":"Interesting.\n\nWhile I agree with the importance of the Schiller PE, using a linear regression starting in 1871 will input in your investment strategy a period / economic framework that is not relevant to today's world. Maybe use another non-linear regression method that put a stronger emphasis on the last 20 or 30 years. \n\nAlso, and even if backtesting your methodology yields positive returns, a methodology where there are entire decades where you cannot invest is not practical from a human lifespan practice. Still interesting as a theoretical model though.","author":{"name":"[deleted]","username":"[deleted]"},"timestamp":"2025-04-17T11:07:52.000Z","likes":1,"replies":[{"id":"mnkjhcq","content":"This method enumerates human behavior, so the entire data set matters in that regard. Consider that the Shiller PE by itself is a measure of irrational exuberance. My model exposes a gradual increase in people's willingness to pay more over time and then compares the current prices to this ever increasing risk tolerance. Why are people willing to take on more and more risk? That is uncertain. It could be that loans are far easier to get now than in the 1800/1900's. It could be changes in laws on how companies have to report earnings, etc. Nevertheless, there is a gradual increase in human behavioral risk tolerance in investing, and this model considers this behavioral risk and then compares current trends to this ever-growing tolerance. So it is a behavioral model first and foremost. \n\nAlso, there are no periods where decades pass where one wouldn't invest. Consider withdrawing the invested account when GF hits 15+ and using excess cash to pay down debts until GF drops below 15, and then DCA with salary as usual. However do not dump the withdrawn amount back into the market until GF hits 4 or less. This DCA's when the market is below 15, while also preserving bulk growth once the market has grown irrational. The best of both worlds. 🙂","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179"},"timestamp":"2025-04-17T11:58:26.000Z","likes":1,"replies":[{"id":"mnkt3dw","content":"\\> Why are people willing to take on more and more risk? That is uncertain.\n\nI think the structurally higher PE does somewhat reflect more appetite for risk, but also more and more money in the system.","author":{"name":"[deleted]","username":"[deleted]"},"timestamp":"2025-04-17T12:59:06.000Z","likes":1,"replies":[{"id":"mnl8125","content":"Well, P/E is a ratio. Thus the expanding ratio takes into account more money in the system. People are objectively willing to pay more comparatively to earnings. The inflation is included in this ratio.","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179"},"timestamp":"2025-04-17T14:20:33.000Z","likes":1}]}]}]},{"id":"mpzek85","content":"I'm not sure if you've read lifecycle investing, but they have an equation that helps you decide how much leverage you should put into the S&P500. One of the equations that they recommend asks that you input the Shiller PE ratio. Given how historically high the Shiller PE ratio has been, the equation has essentially recommended leveraging and even buying 0% S&P500 for the past 10 years or so. \n\n\nIf you have read the book or at least heard of the idea, I'm wondering if you've come across an equation that would replace the Shiller PE ratio as there is supposedly positive drift overtime? \n\nI'm not really looking for signals to sell but looking for opportunities to buy and/or leverage based on my age, retirement savings, etc.","author":{"name":"tooclouds","username":"tooclouds","handle":"u/tooclouds","url":"https://www.reddit.com/user/tooclouds"},"timestamp":"2025-05-01T07:40:08.000Z","likes":1,"replies":[{"id":"mq055ld","content":"I'm unaware of the book you mention but the hypothetical equation you speak of is possibly the one I've shown here. It's the Residual of the Shiller PE. \n\nThe concept you speak of sounds similar to an idea I've mentioned on Reddit a few times, of something I call a \"Risk Mitigation Ladder\", which is the concept of removing earnings from the market as the Residual gets higher, and increasing as it gets lower. \n\nI haven't crunched any numbers but the concept should be sound. After all, this entire concept is based around the idea that eventually, things are just too expensive for the average investor and when that happens a bear market occurs.","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179"},"timestamp":"2025-05-01T11:53:12.000Z","likes":1}]},{"id":"mm1v1ns","content":"You going to post again when the residual drops below 4?","author":{"name":"hop_along_quixote","username":"hop_along_quixote","handle":"u/hop_along_quixote","url":"https://www.reddit.com/user/hop_along_quixote"},"timestamp":"2025-04-08T15:45:10.000Z","likes":2,"replies":[{"id":"mm22dgb","content":"Yep. And probably here and there between, as the market bobs and weaves.\n\nYou can also watch the raw data sheet itself to see what the days Greed/Fear is at EoD. I update it almost daily.","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179"},"timestamp":"2025-04-08T16:21:33.000Z","likes":1}]},{"id":"n8n5eom","content":"With the Greed/Fear Value being only .02 away from 15 what are your current thoughts?","author":{"name":"DesignerMedium8211","username":"DesignerMedium8211","handle":"u/DesignerMedium8211","url":"https://www.reddit.com/user/DesignerMedium8211"},"timestamp":"2025-08-14T12:48:12.000Z","likes":1,"replies":[{"id":"n8n7wes","content":"[https://www.reddit.com/user/Think\\_Reporter\\_8179/comments/1m960u5/if\\_the\\_market\\_holds\\_today\\_well\\_have\\_breached\\_15/?utm\\_source=share&utm\\_medium=web3x&utm\\_name=web3xcss&utm\\_term=1&utm\\_content=share\\_button](https://www.reddit.com/user/Think_Reporter_8179/comments/1m960u5/if_the_market_holds_today_well_have_breached_15/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button)","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179"},"timestamp":"2025-08-14T13:02:34.000Z","likes":1}]},{"id":"mlekyrw","content":"I grew tired of trying to point people all over old posts and historical comments I've made throughout Reddit, so I finally decided to lay out how this all works in a single \"paper\". Enjoy","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179"},"timestamp":"2025-04-04T17:11:50.000Z","likes":4,"replies":[{"id":"mlfhmkj","content":"Nice work, so buy and hold still outperforms, but if you want to get a little extra umph pile on when its low , makes sense. Sadly the shiller PE is still in the 30s even after all this carnage. I wonder if you could create a tool that flashes red green or yellow depending on if it is time to buy or not based on the signals.","author":{"name":"InterestSharp3835","username":"InterestSharp3835","handle":"u/InterestSharp3835","url":"https://www.reddit.com/user/InterestSharp3835"},"timestamp":"2025-04-04T19:57:37.000Z","likes":1,"replies":[{"id":"mlfk957","content":"Buy & Hold does not outperform. The 20/4 and 15/4 strategies beat it.\n\n\\- Buy & Hold CAGR: 9.11%\n\n\\- 20/4 Strategy CAGR: 9.67%\n\n\\- 15/4 Strategy CAGR: 9.61%","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179"},"timestamp":"2025-04-04T20:11:00.000Z","likes":2,"replies":[{"id":"mlfl518","content":"Seems like a lot of risk and effort for half a percent point. In my mind the premium over buy and hold has to be higher for me to take on the risk , especially more than 500 basis points.","author":{"name":"InterestSharp3835","username":"InterestSharp3835","handle":"u/InterestSharp3835","url":"https://www.reddit.com/user/InterestSharp3835"},"timestamp":"2025-04-04T20:15:30.000Z","likes":1,"replies":[{"id":"mlflosk","content":"That's fair. This is a new discovery and made more for large hedge fund strategy or long-term holding signals. If Greed/Fear hits 15+, sell out, wait until it hits 4, then dump back in. You win over the long term. As far as I know, nothing else beats B&H with such minimum effort. \nYou said effort, but really this is a simple calculation. Perform a linear regression on the Shiller PE, then subtract the current Shiller PE from the trend and you're done.\n\nI think the real value here is that whenever the market touches 15+ Greed/Fear, there is a bear market within 3-6 months. The quant folks could probably do a lot with that awareness.","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179"},"timestamp":"2025-04-04T20:18:18.000Z","likes":2,"replies":[{"id":"mljnqhk","content":"Would be curious to see how much it beat buy/hold since the 90s, or even since we fully came off the gold standard.","author":{"name":"Dick_Wiener","username":"Dick_Wiener","handle":"u/Dick_Wiener","url":"https://www.reddit.com/user/Dick_Wiener"},"timestamp":"2025-04-05T14:36:35.000Z","likes":1,"replies":[{"id":"mljnvdu","content":"It would be the same, since 15 has only shown up a handful of times since 1871, the most recent being last December on the 6th!","author":{"name":"Think_Reporter_8179","username":"Think_Reporter_8179","handle":"u/Think_Reporter_8179","url":"https://www.reddit.com/user/Think_Reporter_8179"},"timestamp":"2025-04-05T14:37:22.000Z","likes":1}]}]}]}]}]}]},{"id":"oggvjkv","content":"Not even fully sure how I stumbled upon your post but this is much appreciated info. Sincerely thank you. ","author":{"name":"Notable_Naps","username":"Notable_Naps","handle":"u/Notable_Naps","url":"https://www.reddit.com/user/Notable_Naps"},"timestamp":"2026-04-16T05:28:00.000Z","likes":2},{"id":"op3rad3","content":" I wonder if going right now as of June 26 on inverse Nasdaq etf is a good move. Summer months tend to average weaker returns. Also maybe trend might be negative until midterms. The AI narrative is also shifting a bit. Not sure…","author":{"name":"Voxick95","username":"Voxick95","handle":"u/Voxick95","url":"https://www.reddit.com/user/Voxick95"},"timestamp":"2026-06-01T10:47:54.000Z","likes":1}],"aiComments":[]},{"id":"web-je080n","shareId":"NDvG3AHpjc","platform":"web","url":"https://www.leadsie.com/blog/create-facebook-ad-account","title":"How to Create a Facebook Ad Account","shareMode":"full","createdAt":1786033846227,"postedAt":"2026-07-26T00:00:00.000Z","publishedDate":"2026-07-26T00:00:00.000Z","archivedAt":"2026-08-06T16:30:42.876Z","archivedDate":"2026-08-06T16:30:42.876Z","viewCount":2,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/NDvG3AHpjc","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/I19zDBnuaO/media/0.png","contentType":"article","content":{"text":"[Leadsie Blog](https://www.leadsie.com/blog) Article Content\n\nCreate a new Facebook ad account by going to [Meta Business Suite’s Settings](https://business.facebook.com/latest/settings), open ‘ **Accounts** ’, then ‘ **Ad accounts** ’, click ‘ **Add** ’, and choose ‘ **Create a new ad account** ’. Set the name, time zone, and currency, then add a payment method before you run ads.\n\nThe rest of this guide walks through each step with screenshots, and it covers the part most tutorials skip: how to avoid the one setup mistake that forces a painful rebuild later. If your ad account ends up attached to your personal profile instead of your business, you can lose it, cap your spending, and orphan your tracking, so it is worth getting it right the first time.\n\n## What is a Facebook (Meta) ad account?\n\nA Facebook ad account is the container where you build campaigns, set your billing, and see your reporting. Everything you spend and every result you measure lives inside it. You need one before you can run a single ad*.\n\nYour ad account is not the same thing as your Facebook profile or your Facebook Page. Your profile is your personal identity, your Page is your business's public presence, and your ad account is the advertising engine that sits behind them. A Meta Pixel, the small piece of code that tracks what happens on your website, also connects to your ad account.\n\n***Note:** Meta automatically creates a personal ad account for first-timers (with no prior ad account) who boost a post. However, this is tied to their personal Facebook profile.\n\n**💡Pro tip:** If you plan to advertise regularly, it is important to create a full-featured ad account under a Business Portfolio, not from your personal Facebook profile, as doing so limits your ability to collaborate with agencies, colleagues, or freelancers.\n\n### What you need before you start\n\n**Quick checklist:**\n\n1. Personal Facebook profile (for login)\n2. A Meta Business Portfolio (create one if needed, using a business email)\n3. Facebook Page, or an admin/editor/advertiser role on one\n4. Payment method (card or PayPal)\n\n## How to create a Facebook ad account (step by step)\n\n**Step 1:** In Meta [Business Suite's Settings](https://business.facebook.com/latest/settings), look under' **Accounts** ' → click ' **Ad accounts** ', or go there directly @ [https://business.facebook.com/latest/settings/ad_accounts](https://business.facebook.com/latest/settings/ad_accounts).\n\n**Step 2:** Click on either of the blue ' **+ Add** ' button.\n\n**Step 3:** From the options, select ' **Create a new ad account**.'\n\n![How to create a new Facebook or Meta ad account](https://cdn.prod.website-files.com/60c334e72012f37063378d4b/68625355d2aa99293e89469f_7.%20How%20to%20create%20a%20new%20Facebook%20or%20Meta%20Ad%20account.png)\n\n**Step 4:** Fill in details, such as ad account name, your time zone, and currency. Click ' **Next**.'\n\n**Step 5:** Follow the on-screen prompts to declare usage and review the info and terms. Then click ' **Create Ad Account** '.\n\n> *⚠️* ***Note:*** *There are ad account limits per account. Once you create an ad account that's tied to a business portfolio, you cannot delete the ad account. However, you can close it and possibly reactivate it again in future. Read more about* [*closing Meta/Facebook ad accounts*](https://www.facebook.com/business/help/190760004667059?id=420299598837059)*.*\n\n**Step 6:** Now you have a Facebook/Meta ad account, but there's just one more step before you can start using it. Add at least one payment method to your Ad account when prompted to do so.\n\nThat is the core setup. Two details deserve their own attention, and they come next: the settings you cannot easily change later, and the payment step that quietly blocks your first campaign.\n\n*🔗 Related article:* [*How to Request Access to a Facebook Ad Account*](https://www.leadsie.com/blog/request-facebook-ad-account-access)\n\n### Desktop vs mobile\n\nSet up your ad account on a desktop browser if you can. The full settings are easier to find and the menus are clearer.\n\nYou can create and manage ad accounts in the Meta Ads Manager mobile app, but the menu labels differ from the desktop version and some options are harder to reach. Use mobile for quick checks, not for first-time setup.\n\n## Choosing your name, time zone, and currency (get this right, it's permanent)\n\nChoose your currency and time zone carefully, because they are effectively locked once the ad account is created. Changing them later usually means starting a brand-new ad account, so treat these fields as permanent decisions rather than defaults to rush past.\n\n1. **Pick the currency** you will actually pay in. Your billing follows this setting, and a mismatch creates accounting headaches every month. If your business banks in one currency, match it.\n2. **Pick the time zone** you report and schedule against. Your reporting days and your ad scheduling both run on this clock. If you manage the account from a different region than your business operates in, choose the one you will actually plan around.\n3. **Name the account** so it still makes sense if you add more accounts later. A clear naming convention, such as the business name plus the market or purpose, saves confusion once you are running more than one.\n\n| Setting | What to choose | Why it matters |\n| --- | --- | --- |\n| Currency | The currency you pay in | Billing follows it and it is hard to change later |\n| Time zone | The zone you report and schedule against | Sets your reporting days and ad timing |\n| Account name | A clear, scalable convention | Keeps multiple accounts organized |\n\n## Add your payment method and billing\n\nAdd a payment method before you try to launch anything, because no payment method means no live ads. Your account can exist fully set up and still refuse to spend until billing is attached.\n\n**How to add or edit a payment method:**\n\n1. Go to [Ads Manager.](https://adsmanager.facebook.com/adsmanager/)\n2. Open ' **Billing & payments'** from the left-hand menu\n3. Click ' **Payment methods** '\n4. Under 'Ad accounts', click ' **Add payment method** ' and enter a card or PayPal.\n5. Save it, and your account is cleared to run ads.\n\nIf your first campaign will not launch, billing is the first thing to check. It is the step people most often forget, and Meta will not deliver ads without it.\n\n![Add a payment method to your ad account on Meta Business Suite](https://cdn.prod.website-files.com/60c334e72012f37063378d4b/6a5cfacdc0a6a42dbf120369_2.%20Add%20a%20payment%20method%20to%20your%20ad%20account%20on%20Meta%20Business%20Suite.png)\n\n## The #1 setup mistake: Your ad account on a personal profile\n\nThe most common and costly setup mistake is running your ad account off your personal Facebook profile instead of a Business Portfolio. It happens by accident, it creates real risk, and fixing it later is a hassle, so check for it now.\n\nHere is how it happens. Your first brush with advertising is usually boosting a post or clicking a \"create ads\" link inside your personal profile. From there, in the words of Stacy Covitz, \"Meta, Facebook just takes it upon themselves to create an ad account under your personal profile. And you end up running ads from there.\" You never chose this setup; Facebook chose it for you.\n\nWhy it is a problem comes down to security, limits, and tracking. On the security side, your advertising is tied to your personal login: \"If your account gets hacked or locked or anything like that, your whole ad account goes down with it. And there's no separation,\" Covitz explains.\n\nOn the practical side, a personal ad account carries a tiny spending limit and cannot easily take on team members. And your tracking suffers, because \"your pixel is basically sitting on your personal account. It's not named. It's not managed. It's not getting the proper data.\"\n\n**How to check if yours is set up wrong:**\n\n1. Go to and log in at [https://business.facebook.com/latest/settings/ad_accounts/](https://business.facebook.com/latest/settings/ad_accounts/)\n2. Click on your ad account.\n3. Look at the name. If it does not carry your business name and it looks like it is \"floating\" on its own, it is sitting on your personal profile.The fix is to move your advertising under a proper Business Suite. Set up a Business Portfolio if you do not have one. Your pixel cannot simply be dragged over, so if the old pixel has little data, start a fresh one inside your new Business Suite. If the orphaned pixel does hold data worth keeping, name it first so you can at least identify it while you transition.\n\n*🔗 Related article:* [*How to create a Meta business portfolio*](https://www.leadsie.com/blog/how-to-create-meta-business-manager-and-facebook-ad-account#creating-your-first-business-portfolio)\n\n### The gold-standard ad account setup (checklist)\n\nA properly built Facebook advertising setup follows a simple structure. Start with a Meta Business Suite account. Have that be the umbrella for everything. Build yours to match this checklist and you avoid nearly every problem above.\n\n- **Meta Business Suite** as the umbrella that owns everything\n- Your **Facebook Page** and **Instagram** account connected to it\n- **One ad account** (one per business, unless you genuinely run several businesses)\n- Your **domain verified**, which is not required but always helpful\n- **Two-factor authentication** turned on\n- **Agencies, admins, and ad managers** added cleanly through settings *🔗 Related article:* [*How to give access to a Facebook (Meta) Ad account*](https://www.leadsie.com/blog/grant-facebook-ad-account-access)\n\n## Troubleshooting: Cannot find 'Create a new ad account'\n\nIf the “ **Create a new ad account** \" option is missing or greyed out, it is almost always one of four reasons, and each has a fix. The button is not broken; Meta is holding it back for a specific cause.\n\nThe usual causes are that your portfolio has reached its ad account limit, your account is too new, your business is restricted or unverified, or you do not have full admin access. Work through them in that order.\n\n| Cause | What to do |\n| --- | --- |\n| Portfolio hit its ad account limit | Request an increase, or reuse an existing account |\n| Account is too new | Wait out the new-account limits, then try again |\n| Business restricted or unverified | Verify your business and email in settings |\n| You lack full admin access | Ask a portfolio admin to grant you full control |\n\nIf none of these apply and the option still will not appear, verifying your business details and email resolves most of the remaining cases.\n\nWant to learn more? Explore our [Frequently Asked Questions](#FAQ) on this topic.\n\nABOUT THE AUTHOR\n\n##### Jocelyn Ke\n\nJocelyn’s background spans UX research, marketing, content writing, and consulting. Outside of work, she enjoys reading, surfing, board games, billiards, Latin dancing, and MMORPGs.\n\n![Image](https://cdn.prod.website-files.com/60c334e62012f37bfe378d44/63b84de59a68cc59c77f3895_party-popper_1f389.png)"},"author":{"name":"Jocelyn Ke","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/1203366d0d43f7e2/avatar-73ce35aca66a.png","bio":"Create a Facebook ad account the right way: set your name, time zone, currency, and billing, and avoid the personal-profile mistake that forces a costly rebuild."},"metadata":{"timestamp":"2026-07-26T00:00:00.000Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/I19zDBnuaO/media/0.png","type":"image","width":1200,"height":771}],"aiComments":[]},{"id":"web-izzida","shareId":"2upg5yLlBh","platform":"web","url":"https://www.leadsie.com/blog/managed-meta-accounts","title":"Managed Meta Accounts: What They Are and How to Migrate Your Organization","shareMode":"full","createdAt":1786033842604,"postedAt":"2026-07-31T00:00:00.000Z","publishedDate":"2026-07-31T00:00:00.000Z","archivedAt":"2026-08-06T16:30:37.633Z","archivedDate":"2026-08-06T16:30:37.633Z","viewCount":1,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/2upg5yLlBh","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/NUDFalrpa7/media/0.png","contentType":"article","content":{"text":"[Leadsie Blog](https://www.leadsie.com/blog) Article Content\n\nMore and more organizations are starting to migrate to managed Meta accounts (MMA), but the process can be confusing if you’re encountering it for the first time. 😵💫\n\nSome people first hear the term after receiving an email asking them to sign up. Others want to migrate their organization but can’t find the option to enable it or aren’t sure where the process begins.\n\nPart of the confusion comes from how the system works.\n\nNot everyone can switch to managed Meta accounts. The process starts when an organization receives an invitation from Meta to begin the migration, after which the company's administrators can create accounts for employees and invite them to activate them.\n\nIn this guide, we’ll explain what managed Meta accounts are, why Meta introduced them, and how organizations can migrate to them. We’ll also walk through common issues teams run into during migration and how to fix them.\n\n### Key takeaways ✔️\n\n- **Managed Meta accounts (MMA)** are work-only accounts that let employees access Meta business tools without using a personal Facebook account.\n- Organizations must be **invited by Meta** before they can migrate to managed Meta accounts. Individuals cannot create them on their own.\n- Once invited, administrators set up identity systems (like SSO), create managed accounts for employees, and add the company’s Business Portfolios to the migration.\n- Employees then **activate their managed Meta account**, which creates a business user profile used to access tools like Meta Business Suite and Ads Manager.\n- After activation, employees may need to **reconnect third-party apps and integrations within 30 days** to prevent them from losing access to business assets.\n- External partners (such as agencies or freelancers) can still access business assets using **partner access in your Business Portfolio**, so they don’t need to be part of the managed Meta accounts created by your organization.\n\n## What are managed Meta accounts?\n\nManaged Meta accounts are free **work-only accounts that allow employees to access Meta’s business tools using their company credentials or single sign-on (SSO)** instead of a personal Facebook profile. This means employees no longer need a Facebook account to access Meta Business Suite or Ads Manager.\n\nTypically, anyone managing business assets on Meta, like ad accounts or Facebook Pages, needs to log in with a personal Facebook account. Even when assets are organized within a Business Portfolio, the login identity still belongs to the individual rather than the organization.\n\nFor businesses with larger teams, this can create security challenges because they have limited visibility into how those accounts interact with their business tools.\n\nManaged accounts solve this by separating personal and professional access.\n\n### How managed Meta accounts differ from personal Facebook accounts\n\nUnlike personal Facebook accounts, managed Meta accounts are designed **strictly** for business use.\n\nSome key differences include:\n\n**✔️ No consumer Facebook features**\n\nManaged Meta accounts don’t have a personal timeline or access to the Facebook News Feed. They are not meant for interacting with Facebook as an individual user and exist only to access business tools.\n\n**✔️ Accounts are created and managed by the organization**\n\nAdmins create accounts for employees and manage them centrally. They can set up accounts directly in the Admin Centre or connect an identity provider (IdP), such as Google Workspace, Okta, or Microsoft Azure AD.\n\n**✔️ Work-only access to business tools**\n\nThese accounts are used specifically to access Meta business products such as Meta Business Suite, Ads Manager, and other business assets.\n\n**✔️ Permissions must come through a business account**\n\nManaged Meta accounts cannot hold personal asset permissions. Access to Pages, ad accounts, or other assets must be granted through a Business Portfolio.\n\n**✔️ Login with work credentials**\n\nEmployees log in using their work email address or through single sign-on (SSO), rather than a personal Facebook profile.\n\n**🔗 Related article:** [Meta Business Suite vs. Meta Business Portfolio: What’s the Difference?](https://www.leadsie.com/blog/meta-business-manager-vs-meta-business-suite-differences)\n\n## Why Meta introduced managed accounts\n\nMeta introduced managed Meta accounts to give organizations more control over how employees access business tools and to support enterprise-level security.\n\nHere are some of the key reasons behind the change:\n\n**📝 Stronger security controls\n** Managed accounts support enterprise security features such as single sign-on (SSO). When Meta is connected to an organization’s identity provider (IdP), employees can log in using their work credentials while the company maintains control over authentication and security policies.\n\n**📝 Centralized account management\n** Accounts can be automatically created or deactivated when employees join or leave the company through identity provider integrations. This helps organizations keep employee access up to date and reduces the risk of outdated permissions.\n\n**📝 Better visibility and access auditing\n** Managed Meta accounts give organizations clearer visibility into who has access to business tools and assets, making it easier to track permissions and conduct internal security or compliance audits.\n\n## Who can use managed Meta accounts\n\nManaged Meta accounts are designed for larger organizations that want to manage employee access to Meta’s business tools in one place, using their own security and identity systems.\n\n❗ However, migration to managed Meta accounts is **not available to all organizations yet**. Businesses must first be eligible and receive an invitation from Meta before they can begin the migration process.\n\n![Image](https://cdn.prod.website-files.com/60c334e72012f37063378d4b/69b39a325364633903c1c35a_Invitation%20email%20to%20sign%20up%20to%20managed%20Meta%20accounts.png)\n\n### Can you prepare your organization for managed Meta accounts?\n\nMeta has not published a confirmed way to request or speed up access to managed Meta accounts. However, organizations can prepare their accounts so they’re ready if they become eligible.\n\nSome steps that may help include:\n\n- Completing **business verification**\n- Enabling **single sign-on (SSO)** through an identity provider\n- Enforcing **two-factor authentication (2FA)** for business tools\n- Consolidating assets under a **single Business Portfolio**\n- Maintaining **active ad accounts and consistent ad spend**\n- Working with a **Meta partner or account representative** While these steps don’t guarantee an invitation, they align with the infrastructure typically required for organizations migrating to managed accounts.\n\n**🔗 Related article:** [How to Create a Meta Business and Facebook Ad Account](https://www.leadsie.com/blog/how-to-create-meta-business-manager-and-facebook-ad-account)\n\n## How the managed Meta account migration works\n\nOrganizations migrate to managed accounts through a structured process that replaces employees’ personal Facebook logins with organization-managed accounts.\n\nThe transition is handled at the organization level, meaning administrators first prepare the company’s systems and Business Portfolios before employees begin activating their accounts.\n\nSeveral groups are usually involved in the process, including people with organization management task access, IT managers responsible for identity and security setup, and the employees who will activate their accounts. In some cases, agencies or external partners may also be involved.\n\nThe process typically takes place in four main stages.\n\n### Stage 1: Preparing the organization for migration\n\nThis stage is usually led by an **organization manager** (administrator), who oversees the migration and coordinates the setup process. In many cases, they act as project leads to ensure the migration runs smoothly.\n\nThe first step is to **audit who currently has access to the organization’s Business Portfolios and assets**. This helps ensure only the right employees are migrated to managed Meta accounts.\n\nOnce the right people are involved, administrators need to complete several setup tasks before migration can begin. These usually include:\n\n- Verifying the organization’s email domains\n- Connecting an identity provider (IdP)\n- Setting up single sign-on (SSO)\n- Enabling two-factor authentication (2FA)\n- Claiming the business portfolios that will be migrated\n\n![Image](https://cdn.prod.website-files.com/60c334e72012f37063378d4b/69b39afd30a614ecc0a24abc_Claim%20a%20business%20portfolio%20in%20Organizations%20Manager.png)\n\n👉 If you want a full list of tasks Meta recommends completing before migration, you can review the [**pre‑migration checklist for managed Meta accounts**](https://www.facebook.com/business/m/managed-meta-accounts/pre-migration-checklist).\n\nThese steps ensure the organization’s identity and security systems are ready to manage employee access to Meta’s business tools.\n\n**🔎 Note:** Organization managers can also **invite up to three people** to help them complete IT tasks in Organization Manager during migration. Learn how to invite them [here](https://www.facebook.com/business/help/1256722792362621?id=586399373675491).\n\n### Stage 2: Creating and inviting employee accounts\n\nOnce the organization is ready, administrators can create managed Meta accounts for employees.\n\n**🔎 Note:** Everyone who needs access to the organization’s Business Portfolios **must** have a managed Meta account created for them.\n\nAccounts can be [created in two ways](https://www.facebook.com/business/help/1559902565394669?id=586399373675491):\n\n1. **Automatically through an identity provider (IdP) ** Administrators can connect an identity provider such as Google Workspace, Microsoft Entra ID, or Okta in Admin Center. When this integration is enabled, managed Meta accounts are automatically created when employees are added to the organization’s identity directory. Similarly, removing someone from the directory will deactivate their managed Meta account.\n2. **Manually through Admin Center ** Administrators can also create accounts manually by entering an employee’s name and work email address in Admin Center. However, manually created accounts must also be managed manually; for example, administrators would need to deactivate the account if an employee leaves the organization.Once accounts are created and the relevant Business Portfolios have been added to Organization Manager, administrators can [invite employees to migrate to their managed Meta accounts](https://www.facebook.com/business/help/164957106539403).\n\n### Stage 3: Employees activate their managed Meta accounts\n\nEmployees must activate their managed Meta accounts before they can use them to access business tools.\n\nActivation can typically be completed through the invitation email or through a notification in Meta Business Suite.\n\n![Image](https://cdn.prod.website-files.com/60c334e72012f37063378d4b/69b39b2c513287933bf8544d_Activate%20meta%20managed%20account.png)\n\nDuring activation, employees may be asked to:\n\n- Verify their work email address\n- Set up authentication methods such as two-factor authentication\n- Log in using their organization’s identity provider (if SSO is enabled)\n- Confirm the business portfolios and assets they will access Once activated, a **business user profile** is created for the employee, which is used to access Meta’s business tools. They will no longer need to use their personal Facebook account to access their organization’s business portfolios or assets.\n\n**🔎 Note:** Employees must activate their account before the migration deadline set by the organization. If they miss the deadline, they may temporarily lose access to the organization’s business tools until the migration is completed.\n\n### Stage 4: Reconnecting integrations and tools\n\nAfter activating their managed Meta accounts, employees may need to reconnect third-party apps and integrations that were previously connected through their personal Facebook accounts.\n\nThis might include tools like social media management platforms, analytics tools, or other apps that had permission to access business assets such as Facebook Pages or ad accounts.\n\nBecause these integrations were originally authorized through a personal Facebook account, their permissions don’t automatically carry over to the new managed account. As a result, employees will need to reconnect these apps using their **business user profile**, which is created when the managed Meta account is activated.\n\nTo help avoid disruptions, Meta provides a **30-day grace period** during migration so users have time to reconnect their integrations.\n\n## How agencies and external partners can access assets after migration\n\nOrganizations often work with external partners such as marketing agencies, consultants, or freelancers who need access to business assets like Facebook Pages or ad accounts.\n\nThese partners **do not need a managed Meta account tied to their client’s organization**.\n\nInstead, they can be granted access through [**partner access**](https://www.leadsie.com/blog/request-facebook-ad-account-access) in the organization’s Business Portfolio. This allows them to continue using their personal Facebook accounts while working with your business assets.\n\nAlternatively, agencies can use a client onboarding tool like [**Leadsie**](https://www.leadsie.com/integrations/meta) to securely request access to Meta assets through a single access request link. Rather than guiding clients through Business Portfolio settings, clients can approve access in just a few clicks.\n\nOnce access is granted, partners can manage the assigned assets, such as Pages or ad accounts, without being added as employees in the organization’s managed Meta account system.\n\n**❗ Note:** External partners are **not connected to the organization’s identity provider**. Because of this, administrators must manually remove their access to business assets if the partnership ends.\n\n**🔗 Related article:** [Unable to assign assets in Meta Business Suite? Here are 4 reasons and how to fix them](https://www.leadsie.com/blog/unable-to-assign-assets-meta)\n\n## Common issues when using managed Meta accounts 🛠️\n\nMigrating to managed Meta accounts introduces new workflows and identity controls, which can sometimes lead to unexpected issues.\n\nBelow are some common problems organizations and employees may encounter during migration, along with possible explanations:\n\n### ❌ Migration is not available for your organization\n\nNot all organizations currently have access to managed Meta accounts.\n\nIf your organization has not received an invitation from Meta, it means migration is not yet available for your business. At this stage, all you can do is prepare your accounts and infrastructure for when migration becomes available.\n\n### ❌ Problems adding a Business Portfolio to Organization Manager\n\nOrganizations must add their Business Portfolios to Organization Manager before migration can begin. In some cases, administrators may encounter errors when trying to add a portfolio.\n\nSome common reasons include:\n\n- The **business ID entered is incorrect**\n- The portfolio **is already managed by your organization**\n- The portfolio **is already managed by another organization**\n- The portfolio **is already pending approval** In some cases, a request to add a portfolio may require **manual approval** from someone who has full control of the Business Portfolio.\n\nIf the request is not approved within **30 days**, it will expire and must be submitted again.\n\nAdditionally, Meta allows **only one request every 24 hours**, so administrators may need to wait before submitting another request.\n\n### ❌ Employees lose access to features after migration\n\nAfter activating a managed Meta account, employees may notice that certain features or products they previously accessed with their Facebook account are no longer available.\n\nThis happens because **business user profiles are designed for business tools only**, not consumer platforms.\n\nFor example, a managed Meta account cannot be used to access:\n\n- Facebook as a social platform\n- Instagram\n- Messenger However, employees can still manage business assets such as Pages or ad accounts through **Meta Business Suite**, provided those assets are part of the organization’s Business Portfolio.\n\n### ❌ Some Meta tools do not support managed Meta accounts\n\nCertain Meta tools currently do not support managed Meta accounts.\n\nAn example of this is **Meta Ads Manager for Excel**. If you need to analyze advertising data, Meta recommends exporting reports from Ads Manager or using the Ad Insights API instead.\n\n### ❌ Employees cannot access certain ad features\n\nSome advertising features require additional terms to be accepted after migration.\n\nFor example, users must accept the [**Customer List Custom Audiences Terms**](https://www.facebook.com/legal/terms/customaudience) before they can create or edit ads that use uploaded customer list audiences.\n\n### ❌ Missing invitation emails\n\nIf someone was invited to help with migration or activate a managed Meta account but cannot find the email invitation, they should check their spam folder or log in directly to Meta Business Suite to accept the invitation.\n\n## ⚡ Agency hack: Save hours every week onboarding new clients\n\nWhether you manage ad campaigns, social media, or analytics, getting clients’ accounts set up shouldn’t slow you down.\n\nWith Leadsie, you can request and receive access to all your clients’ accounts using just one secure link. 🔒\n\n![Image](https://cdn.prod.website-files.com/60c334e72012f37063378d4b/6a6cecb98f9f0e0347b2d1fa_GIF_v4_-_How_Leadsie_works_Meta_access_540px.avif)\n\n### What is Leadsie?\n\nLeadsie is a client onboarding software that simplifies requesting and giving access to marketing assets, social media, and ad accounts with one secure link. Get access to your clients’ or influencers’ Facebook, Instagram, Google, TikTok, Shopify, LinkedIn, and other accounts without sharing passwords.\n\nLeadsie handles the most time-consuming aspect of onboarding clients: managing access and adding users. It keeps permission management secure and organized as your agency scales.\n\n### Why agencies use Leadsie for client onboarding\n\n✅ Minimize frustrating chaser emails and calls for access\n\n✅ Reduces your agency's [turnaround time by over 50%](https://www.leadsie.com/blog/dashclicks-case-study)\n\n✅ Scales with your agency as you [grow beyond onboarding 5-10 new clients a week](https://www.leadsie.com/blog/ecommerce-equation-case-study)\n\n✅ Makes it possible to get access to 23+ social, marketing, and analytics platforms at once\n\n✅ Start billable work and billing cycles for your new clients without delays\n\n🎁 Try a [**free 14-day trial**](#signup-bottom) on us—no credit card needed!\n\n*P.S. It's risk-free, and you get to keep your account connections after the trial ends. 🙌*\n\nWant to learn more? Explore our [Frequently Asked Questions](#FAQ) on this topic.\n\nABOUT THE AUTHOR\n\n##### Nina Lelidou\n\nNina is an SEO content specialist with expertise in B2B SaaS. She helps businesses increase organic traffic with strategic, high-quality content. Outside of work, you’ll find her sailing somewhere in the Mediterranean.\n\n![Image](https://cdn.prod.website-files.com/60c334e62012f37bfe378d44/63b84de59a68cc59c77f3895_party-popper_1f389.png)"},"author":{"name":"Nina Lelidou","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/7eab3a441997ca50/avatar-73ce35aca66a.png","bio":"Confused about managed Meta accounts? Learn what they are, how migration works, and what your organization needs to do to get started."},"metadata":{"timestamp":"2026-07-31T00:00:00.000Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/NUDFalrpa7/media/0.png","type":"image","width":1536,"height":1024}],"aiComments":[]},{"id":"web-6cub6k","shareId":"b1swBXB8yk","platform":"web","url":"https://github.com/opendataloader-project/opendataloader-bench","title":"opendataloader-project/opendataloader-bench: OpenDataLoader Benchmark","shareMode":"full","createdAt":1786031725861,"postedAt":"2026-08-06T15:55:13.632Z","publishedDate":"2026-08-06T15:55:13.632Z","archivedAt":"2026-08-06T15:55:17.209Z","archivedDate":"2026-08-06T15:55:17.209Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/b1swBXB8yk","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/eXVeNqYhKY/media/0.png","contentType":"article","content":{"text":"## opendataloader-bench\n\n\n\n## 1. About the Project\n\nPDF documents are everywhere, but LLMs can't read them directly. Extracting structured content — headings, tables, reading order — from PDFs is essential for RAG pipelines and document processing workflows.\n\nThis benchmark evaluates document structure and layout analysis engines to help you choose the right tool.\n\n**What we measure:**\n\n- **Reading Order** — Is the text extracted in the correct sequence?\n- **Table Fidelity** — Are tables accurately reconstructed?\n- **Heading Hierarchy** — Is the document structure preserved? The evaluation pipeline is modular—add new engines, corpora, or metrics with minimal effort.\n\n\n\n## 2. Benchmark Results\n\n\n\n### Quality Comparison\n\n\n\n| Engine | Overall | Reading Order | Table | Heading | Speed (s/page) | License |\n| --- | --- | --- | --- | --- | --- | --- |\n| **opendataloader [hybrid]** | **0.907** | **0.934** | **0.928** | 0.821 | 0.463 | Apache-2.0 |\n| nutrient | 0.885 | 0.925 | 0.708 | 0.819 | **0.008** | Commercial |\n| docling | 0.882 | 0.898 | 0.887 | **0.824** | 0.762 | MIT |\n| marker | 0.861 | 0.890 | 0.808 | 0.796 | 53.932 | GPL-3.0 |\n| unstructured [hi_res] | 0.841 | 0.904 | 0.588 | 0.749 | 3.008 | Apache-2.0 |\n| edgeparse | 0.837 | 0.894 | 0.717 | 0.706 | 0.036 | Apache-2.0 |\n| opendataloader | 0.831 | 0.902 | 0.489 | 0.739 | 0.015 | Apache-2.0 |\n| mineru | 0.831 | 0.857 | 0.873 | 0.743 | 5.962 | AGPL-3.0 |\n| pymupdf4llm | 0.732 | 0.885 | 0.401 | 0.412 | 0.091 | AGPL-3.0 |\n| unstructured | 0.686 | 0.882 | 0.000 | 0.388 | 0.077 | Apache-2.0 |\n| markitdown | 0.589 | 0.844 | 0.273 | 0.000 | 0.114 | MIT |\n| liteparse | 0.576 | 0.866 | 0.000 | 0.000 | 1.061 | Apache-2.0 |\n\n\n\n> Scores are normalized to [0, 1]. Higher is better for accuracy metrics; lower is better for speed. **Bold** indicates best performance.\n\n\n\n### Visual Comparison\n\n[![Benchmark](https://github.com/opendataloader-project/opendataloader-bench/raw/main/charts/benchmark.png)](https://github.com/opendataloader-project/opendataloader-bench/blob/main/charts/benchmark.png)\n\n[![Quality Breakdown](https://github.com/opendataloader-project/opendataloader-bench/raw/main/charts/benchmark_quality.png)](https://github.com/opendataloader-project/opendataloader-bench/blob/main/charts/benchmark_quality.png)\n\nDetailed JSON outputs live alongside each engine and capture the exact metric values:\n\n- [prediction/opendataloader/evaluation.json](https://github.com/opendataloader-project/opendataloader-bench/blob/main/prediction/opendataloader/evaluation.json)\n- [prediction/opendataloader-hybrid/evaluation.json](https://github.com/opendataloader-project/opendataloader-bench/blob/main/prediction/opendataloader-hybrid/evaluation.json)\n- [prediction/docling/evaluation.json](https://github.com/opendataloader-project/opendataloader-bench/blob/main/prediction/docling/evaluation.json)\n- [prediction/marker/evaluation.json](https://github.com/opendataloader-project/opendataloader-bench/blob/main/prediction/marker/evaluation.json)\n- [prediction/edgeparse/evaluation.json](https://github.com/opendataloader-project/opendataloader-bench/blob/main/prediction/edgeparse/evaluation.json)\n- [prediction/nutrient/evaluation.json](https://github.com/opendataloader-project/opendataloader-bench/blob/main/prediction/nutrient/evaluation.json)\n- [prediction/mineru/evaluation.json](https://github.com/opendataloader-project/opendataloader-bench/blob/main/prediction/mineru/evaluation.json)\n- [prediction/pymupdf4llm/evaluation.json](https://github.com/opendataloader-project/opendataloader-bench/blob/main/prediction/pymupdf4llm/evaluation.json)\n- [prediction/unstructured/evaluation.json](https://github.com/opendataloader-project/opendataloader-bench/blob/main/prediction/unstructured/evaluation.json)\n- [prediction/unstructured-hires/evaluation.json](https://github.com/opendataloader-project/opendataloader-bench/blob/main/prediction/unstructured-hires/evaluation.json)\n- [prediction/markitdown/evaluation.json](https://github.com/opendataloader-project/opendataloader-bench/blob/main/prediction/markitdown/evaluation.json)\n- [prediction/liteparse/evaluation.json](https://github.com/opendataloader-project/opendataloader-bench/blob/main/prediction/liteparse/evaluation.json)\n\n## 3. Metrics\n\nAll scores are normalised to the `[0, 1]` range, where higher indicates a closer match to ground truth. Documents missing the artefacts required by a given metric yield `null` in per-document results and are excluded from aggregate means.\n\n\n\n### 3.1. Reading Order Similarity (NID, NID-S)\n\nThe reading order is evaluated using Normalized Indel Distance (NID), which measures the similarity between the ground truth and predicted text.\n\n$$ NID = 1 - \\frac{\\text{distance}}{\\text{len(gt)} + \\text{len(pred)}} $$\n\n- **NID**: Compares the full extracted text of the prediction against the ground truth.\n- **NID-S**: Strips tables before comparison to focus on narrative reading order.\n\n### 3.2. Table Structure Similarity (TEDS, TEDS-S)\n\nTables are evaluated using Tree Edit Distance Similarity (TEDS), comparing DOM structures with the APTED algorithm.\n\n$$ {TEDS}(T_{\\text{gt}}, T_{\\text{pred}}) = 1 - \\frac{{EditDist}(T_{\\text{gt}}, T_{\\text{pred}})}{\\max(|T_{\\text{gt}}|, |T_{\\text{pred}}|, 1)} $$\n\n- **TEDS**: Evaluates both structure and cell text.\n- **TEDS-S**: Structure-only, ignoring textual differences (e.g., OCR noise).\n\n### 3.3. Heading-Level Similarity (MHS, MHS-S)\n\nHeadings are parsed into a flat list and compared using APTED.\n\n$$ {MHS}(H_{\\text{gt}}, H_{\\text{pred}}) = 1 - \\frac{{EditDist}(H_{\\text{gt}}, H_{\\text{pred}})}{\\max(|H_{\\text{gt}}|, |H_{\\text{pred}}|, 1)} $$\n\n- **MHS**: Rewards correctly positioned headings and aligned content blocks.\n- **MHS-S**: Structure-only, isolating heading topology.\n\n### 3.4. References\n\n- Z. Chen et al. \"MDEval: Evaluating and Enhancing Markdown Awareness in Large Language Models.\" *arXiv:2501.15000*, 2025.\n- X. Zhong et al. \"Image-based Table Recognition: Data, Model, and Evaluation.\" *ECCV Workshops*, 2020.\n- M. Pawlik and N. Augsten. \"RTED: A Robust Algorithm for the Tree Edit Distance.\" *arXiv:1201.0230*, 2011.\n- Upstage AI. \"Document Parsing Benchmark (DP-Bench).\" Hugging Face, 2024.\n\n---\n\n\n\n## 4. Reproduce the Benchmark\n\nWant to run this benchmark yourself or add a new engine? Follow the steps below.\n\n\n\n### Prerequisites\n\n- Python 3.13 or higher\n- Git LFS (for PDF files)\n\n### Installation\n\n1. **Clone and set up Git LFS**: ``` git clone https://github.com/opendataloader-project/opendataloader-bench cd opendataloader-bench git lfs install git lfs pull ```\n2. **Install base dependencies** (evaluation + chart generation only): ``` uv sync ```\n3. **Install engine(s) you want to run**: ``` # Individual engines uv sync --extra opendataloader uv sync --extra docling uv sync --extra markitdown # All permissively-licensed engines at once uv sync --extra all-safe ``` AGPL/GPL engines (marker, MinerU, PyMuPDF) and commercial engines (nutrient) are not runnable from this repo — their parser code has been removed to avoid license/commercial-tier entanglement. Their `prediction/` results are preserved so the comparison charts still display them. > Don't have uv? See [installation guide](https://docs.astral.sh/uv/getting-started/installation/)\n\n### Running the Benchmark\n\n\n\n#### Quality Benchmark (default)\n\n\n\n```\n# Full pipeline: parse → evaluate → archive → chart\nuv run src/run.py\n\n# Single engine (skips engines that already have evaluation.json)\nuv run src/run.py --engine docling\n\n# Force re-run even if results exist\nuv run src/run.py --engine docling --force\n```\n\n\n\n#### Individual Stages\n\n\n\n```\n# 1. Parse PDFs\nuv run src/pdf_parser.py\n\n# 2. Evaluate predictions\nuv run src/evaluator.py\n\n# 3. Generate charts (works with existing evaluation.json data only)\nuv run src/generate_benchmark_chart.py\n\n# 4. Archive results\nuv run src/generate_history.py\n```\n\n\n\n#### Targeting Specific Engines or Documents\n\n\n\n```\n# Single engine\nuv run src/pdf_parser.py --engine opendataloader\nuv run src/evaluator.py --engine opendataloader\n\n# Single document\nuv run src/pdf_parser.py --doc-id 01030000000001\n\n# Both\nuv run src/pdf_parser.py --engine opendataloader --doc-id 01030000000001\n```\n\n\n\n### Project Structure\n\n\n\n```\n├─ charts/ # Generated benchmark charts\n├─ ground-truth/ # Reference annotations and structured ground truth\n├─ history/ # Archived evaluation results by date\n├─ pdfs/ # Input PDF corpus (200 sample documents)\n├─ prediction/ # Engine outputs grouped by engine/markdown\n├─ src/ # Conversion, evaluation, and utility scripts\n└─ pyproject.toml # Python dependencies (uv)\n```\n\n\n\n## 5. Contributing\n\n\n\n### Development Setup\n\n\n\n```\n# After following the installation steps above:\nuv sync --dev\n```\n\nThis installs development dependencies including pytest.\n\n\n\n### Running Tests\n\n\n\n```\nuv run pytest\n```\n\n\n\n### Interpreting evaluation.json\n\nEach engine produces an `evaluation.json` with:\n\n- **`summary`**: Engine name/version, hardware info, document count, runtime, date.\n- **`metrics.score`**: Mean scores (`overall_mean`, `nid_mean`, `teds_mean`, `mhs_mean`, etc.)\n- **`metrics.*_count`**: Number of documents eligible for each metric.\n- **`documents`**: Per-document scores and availability flags.\n\n## 6. References\n\n- Z. Chen, Y. Liu, L. Shi, X. Chen, Y. Zhao, and F. Ren. \"MDEval: Evaluating and Enhancing Markdown Awareness in Large Language Models.\" *arXiv preprint arXiv:2501.15000*, 2025. [https://arxiv.org/abs/2501.15000](https://arxiv.org/abs/2501.15000)\n- J. He, M. Rungta, D. Koleczek, A. Sekhon, F. X. Wang, and S. Hasan. \"Does Prompt Formatting Have Any Impact on LLM Performance?.\" *arXiv preprint arXiv:2411.10541*, 2024. [https://arxiv.org/abs/2411.10541](https://arxiv.org/abs/2411.10541)\n- D. Min, N. Hu, R. Jin, N. Lin, J. Chen, Y. Chen, Y. Li, G. Qi, Y. Li, N. Li, and Q. Wang. \"Exploring the Impact of Table-to-Text Methods on Augmenting LLM-based Question Answering with Domain Hybrid Data.\" *arXiv preprint arXiv:2402.12869*, 2024. [https://arxiv.org/abs/2402.12869](https://arxiv.org/abs/2402.12869)\n- M. Pawlik and N. Augsten. \"RTED: A Robust Algorithm for the Tree Edit Distance.\" *arXiv preprint arXiv:1201.0230*, 2011. [https://arxiv.org/abs/1201.0230](https://arxiv.org/abs/1201.0230)\n- Upstage AI. \"Document Parsing Benchmark (DP-Bench).\" Hugging Face, 2024. [https://huggingface.co/datasets/upstage/dp-bench](https://huggingface.co/datasets/upstage/dp-bench)\n- X. Zhong, J. Tang, and A. J. Yepes. \"Image-based Table Recognition: Data, Model, and Evaluation.\" *European Conference on Computer Vision Workshops*, 2020. [https://arxiv.org/abs/1911.10683](https://arxiv.org/abs/1911.10683)\n- X. Zhong, J. Tang, and A. J. Yepes. \"PubLayNet: largest dataset ever for document layout analysis.\" *International Conference on Document Analysis and Recognition*, 2019. [https://huggingface.co/datasets/jordanparker6/publaynet](https://huggingface.co/datasets/jordanparker6/publaynet)"},"author":{"name":"opendataloader-project","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/54fbd626d396f927/avatar-6a9577cd4f7f.svg","bio":"OpenDataLoader Benchmark. Contribute to opendataloader-project/opendataloader-bench development by creating an account on GitHub."},"metadata":{"timestamp":"2026-08-06T15:55:13.632Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/eXVeNqYhKY/media/0.png","type":"image","width":1200,"height":600}],"aiComments":[]},{"id":"web-njobmc","shareId":"hfAoltQ54v","platform":"web","url":"https://trending-repos.com/","title":"The market terminal for open source","shareMode":"full","createdAt":1786031263320,"postedAt":"2026-08-06T15:47:32.114Z","publishedDate":"2026-08-06T15:47:32.114Z","archivedAt":"2026-08-06T15:47:36.067Z","archivedDate":"2026-08-06T15:47:36.067Z","viewCount":1,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/hfAoltQ54v","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/yGKAUnox2Y/media/0.png","contentType":"article","content":{"text":"[Trending ReposTrending](https://trending-repos.com/)[Trending](https://trending-repos.com/)[Risers](https://trending-repos.com/risers)[Newest](https://trending-repos.com/newest)[Collections](https://trending-repos.com/collections)[Topics](https://trending-repos.com/topics)[Compare](https://trending-repos.com/compare)[Search](https://trending-repos.com/search)[Submit](https://trending-repos.com/submit)\n\n[Trending Repos](https://trending-repos.com/)The market terminal for open source — every repository quoted by momentum, re-priced every four hours. Velocity, not raw popularity.\n\nTracking 35,304 repos across 200 languages\n\n## Discover\n\n- [Trending](https://trending-repos.com/)\n- [Risers](https://trending-repos.com/risers)\n- [Newest](https://trending-repos.com/newest)\n- [Collections](https://trending-repos.com/collections)\n- [Topics](https://trending-repos.com/topics)\n\n## Tools\n\n- [Compare](https://trending-repos.com/compare)\n- [Search](https://trending-repos.com/search)\n- [Submit a repo](https://trending-repos.com/submit)\n\n## Project\n\n- [About](https://trending-repos.com/about)\n- [Stats](https://trending-repos.com/stats)\n- [Privacy](https://trending-repos.com/privacy)\n- [GitHub](https://github.com/simonrueba)\n\nMomentum-based scoring · updated every 4 hours.\n\n## Quote board\n\nmomentum-weighted · re-priced every 4h\n\nSession\n\nSector\n\nLicense\n\nFloor\n\n100 / 35,304 LISTED\n\n| RK | SYM | Name | Stars | Δ24H | Trend | Score |\n| --- | --- | --- | --- | --- | --- | --- |\n| 01 | COMP | cloudflare/computer | 4.3k | +2.4k | 1496.1 |\n| 02 | ANYD | firecrawl/anydoc | 6.4k | +3.6k | 1090.1 |\n| 03 | SKIL | mattpocock/skills | 206k | +1.7k | 1083.3 |\n| 04 | REVE | zhaoxuya520/reverse-skill | 20k | +1.2k | 1067.1 |\n| 05 | PDFI | firecrawl/pdf-inspector | 12k | +1.5k | 1020.0 |\n| 06 | CRM | trycompai/crm | 6.9k | +1.6k | 941.0 |\n| 07 | QM | yc-software/qm | 12k | +554 | 664.9 |\n| 08 | OMNI | diegosouzapw/OmniRoute | 41k | +1.1k | 620.6 |\n| 09 | AIAG | bojieli/ai-agent-book | 33k | +1.0k | 596.4 |\n| 10 | STRI | usestrix/strix | 49k | +650 | 558.8 |\n| 11 | PONY | DietrichGebert/ponytail | 97k | +853 | 551.7 |\n| 12 | DEEP | esengine/DeepSeek-Reasonix | 32k | +822 | 520.1 |\n| 13 | FIRE | firecrawl/firecrawl | 162k | +703 | 498.3 |\n| 14 | ANIM | juliangarnier/anime | 72k | +801 | 495.9 |\n| 15 | SUPE | obra/superpowers | 268k | +823 | 488.3 |\n| 16 | ENGR | nagisanzenin/engram | 1.3k | +777 | 477.1 |\n| 17 | ORCA | stablyai/orca | 39k | +719 | 471.5 |\n| 18 | AIFO | microsoft/AI-For-Beginners | 62k | +441 | 454.5 |\n| 19 | KIMI | FareedKhan-dev/kimi-k3-in-c | 2.7k | +560 | 437.8 |\n| 20 | TAST | Leonxlnx/taste-skill | 73k | +627 | 434.4 |\n| 21 | BUZZ | block/buzz | 24k | +619 | 430.4 |\n| 22 | FDET | xdash/FDE-the-Guidance-Book-of-Forward-Deployed-Engineer | 3.5k | +487 | 423.8 |\n| 23 | AGEN | Panniantong/Agent-Reach | 67k | +548 | 420.9 |\n| 24 | HERM | NousResearch/hermes-agent | 226k | +573 | 415.7 |\n| 25 | IMPE | pbakaus/impeccable | 56k | +589 | 408.3 |\n| 26 | GCMI | LiamGvchi/gc-minimal-zine-poster | 3.8k | +599 | 402.1 |\n| 27 | GLOW | charmbracelet/glow | 27k | +22 | 400.1 |\n| 28 | PI | earendil-works/pi | 85k | +672 | 398.1 |\n| 29 | GRAP | Graphify-Labs/graphify | 103k | +539 | 374.0 |\n| 30 | GENE | microsoft/generative-ai-for-beginners | 117k | +399 | 367.4 |\n\nANYD+3.6k▲COMP+2.4k▲SKIL+1.7k▲CRM+1.6k▲PDFI+1.5k▲ANYD+3.6k▲COMP+2.4k▲SKIL+1.7k▲CRM+1.6k▲PDFI+1.5k▲ANYD+3.6k▲COMP+2.4k▲SKIL+1.7k▲CRM+1.6k▲PDFI+1.5k▲ANYD+3.6k▲COMP+2.4k▲SKIL+1.7k▲CRM+1.6k▲PDFI+1.5k▲ANYD+3.6k▲COMP+2.4k▲SKIL+1.7k▲CRM+1.6k▲PDFI+1.5k▲ANYD+3.6k▲COMP+2.4k▲SKIL+1.7k▲CRM+1.6k▲PDFI+1.5k▲ANYD+3.6k▲COMP+2.4k▲SKIL+1.7k▲CRM+1.6k▲PDFI+1.5k▲ANYD+3.6k▲COMP+2.4k▲SKIL+1.7k▲CRM+1.6k▲PDFI+1.5k▲ANYD+3.6k▲COMP+2.4k▲SKIL+1.7k▲CRM+1.6k▲PDFI+1.5k▲ANYD+3.6k▲COMP+2.4k▲SKIL+1.7k▲CRM+1.6k▲PDFI+1.5k▲ANYD+3.6k▲COMP+2.4k▲SKIL+1.7k▲CRM+1.6k▲PDFI+1.5k▲ANYD+3.6k▲COMP+2.4k▲SKIL+1.7k▲CRM+1.6k▲PDFI+1.5k▲\n\n# The Market Terminal for Open Source\n\nevery GitHub repository, quoted by momentum\n\n● LiveSession 2026-08-06Listed 35,304Re-price T−–:––:––\n\nOSS-100 Composite30,708.7\n▼ −8.30% vs prev. session\n\nLeading sectorRust\n▲ +43.64% star velocity\n\nNew listings · session27\nfirst tracked this session\n\nNext re-priceT−–:––:––\nevery 4 hours\n\nToday's session\nThu, Aug 6\n[![cloudflare/computer avatar](https://avatars.githubusercontent.com/u/314135?v=4&s=128) cloudflare/computer#1TypeScriptGive your agent a computer 👾 24h delta+2.4kTotal stars](https://trending-repos.com/repositories/cloudflare/computer)\nSectors · star velocity vs prev. session\n[Python+7.2%](https://trending-repos.com/trending/Python)[TypeScript+21.5%](https://trending-repos.com/trending/TypeScript)[Rust+43.6%](https://trending-repos.com/trending/Rust)[JavaScript+21.7%](https://trending-repos.com/trending/JavaScript)[Go−3.1%](https://trending-repos.com/trending/Go)[Shell+3.4%](https://trending-repos.com/trending/Shell)\n\nTop gainers\nLast 24 hours\n\n- [1 ![firecrawl/anydoc avatar](https://avatars.githubusercontent.com/u/135057108?v=4&s=48) firecrawl/anydoc+3.6k](https://trending-repos.com/repositories/firecrawl/anydoc)\n- [2 ![cloudflare/computer avatar](https://avatars.githubusercontent.com/u/314135?v=4&s=48) cloudflare/computer+2.4k](https://trending-repos.com/repositories/cloudflare/computer)\n- [3 ![mattpocock/skills avatar](https://avatars.githubusercontent.com/u/28293365?v=4&s=48) mattpocock/skills+1.7k](https://trending-repos.com/repositories/mattpocock/skills)\n- [4 ![trycompai/crm avatar](https://avatars.githubusercontent.com/u/195194844?v=4&s=48) trycompai/crm+1.6k](https://trending-repos.com/repositories/trycompai/crm)\n\n## Discover by theme\n\n[All collections](https://trending-repos.com/collections)\n[AI & LLMs ![diegosouzapw/OmniRoute avatar](https://avatars.githubusercontent.com/u/8016841?v=4&s=32) diegosouzapw/OmniRoute41.3k ![bojieli/ai-agent-book avatar](https://avatars.githubusercontent.com/u/1421793?v=4&s=32) bojieli/ai-agent-book33.4k ![usestrix/strix avatar](https://avatars.githubusercontent.com/u/187630752?v=4&s=32) usestrix/strix49.2kTypeScript on top](https://trending-repos.com/collections/ai)[Web frameworks ![Leonxlnx/taste-skill avatar](https://avatars.githubusercontent.com/u/219127460?v=4&s=32) Leonxlnx/taste-skill72.9k](https://trending-repos.com/collections/web)\n\nTrending Repos quotes the momentum of 35,304 GitHub repositories — re-priced every four hours from EMA-smoothed star and fork velocity, so you see what's moving, not just what's big. Daily, weekly, and monthly sessions run side-by-side with persistent rank history. Free, for everyone.\n\nFilter by sector or license, drill into any ticker's rank history, and put a self-updating medal badge in your README. See the [about page](https://trending-repos.com/about) for the scoring formula and data sources.\n\n● LIVELAST RE-PRICE 12:09 UTC35,304 LISTEDDATA: GITHUB STARS & FORKS · EMA-SMOOTHEDTHE MARKET TERMINAL FOR OPEN SOURCE\n\n4.3k\n\nDaily score\n1496.1\n\n7-day momentum\n\n[5 ![firecrawl/pdf-inspector avatar](https://avatars.githubusercontent.com/u/135057108?v=4&s=48) firecrawl/pdf-inspector+1.5k](https://trending-repos.com/repositories/firecrawl/pdf-inspector)\n[See all](https://trending-repos.com/risers)\nNew listings\nCreated in 90 days\n\n- [1 ![Binaryify/open-kimi-ppt-skill avatar](https://avatars.githubusercontent.com/u/12221718?v=4&s=48) Binaryify/open-kimi-ppt-skill1d ago](https://trending-repos.com/repositories/Binaryify/open-kimi-ppt-skill)\n- [2 ![KKKKhazix/human-writing avatar](https://avatars.githubusercontent.com/u/239590580?v=4&s=48) KKKKhazix/human-writing1d ago](https://trending-repos.com/repositories/KKKKhazix/human-writing)\n- [3 ![mikiarlo3/awesome-growth-hacking-skills avatar](https://avatars.githubusercontent.com/u/1715109?v=4&s=48) mikiarlo3/awesome-growth-hacking-skills1d ago](https://trending-repos.com/repositories/mikiarlo3/awesome-growth-hacking-skills)\n- [4 ![cristicretu/diri avatar](https://avatars.githubusercontent.com/u/45521157?v=4&s=48) cristicretu/diri2d ago](https://trending-repos.com/repositories/cristicretu/diri)\n- [5 ![ZzzLc0405/photo-abstract-editorial avatar](https://avatars.githubusercontent.com/u/207724921?v=4&s=48) ZzzLc0405/photo-abstract-editorial2d ago](https://trending-repos.com/repositories/ZzzLc0405/photo-abstract-editorial)[See all](https://trending-repos.com/newest?window=90)\n\nHolding the top\nTop this month\n\n- [1 ![hasaneyldrm/exercises-dataset avatar](https://avatars.githubusercontent.com/u/28005450?v=4&s=48) hasaneyldrm/exercises-dataset14.9k★](https://trending-repos.com/repositories/hasaneyldrm/exercises-dataset)\n- [2 ![DigitalPlatDev/FreeDomain avatar](https://avatars.githubusercontent.com/u/126394654?v=4&s=48) DigitalPlatDev/FreeDomain191.2k★](https://trending-repos.com/repositories/DigitalPlatDev/FreeDomain)\n- [3 ![OpenByteInc/QuantDinger avatar](https://avatars.githubusercontent.com/u/306676008?v=4&s=48) OpenByteInc/QuantDinger10.2k★](https://trending-repos.com/repositories/OpenByteInc/QuantDinger)\n- [4 ![openai/whisper avatar](https://avatars.githubusercontent.com/u/14957082?v=4&s=48) openai/whisper106.7k★](https://trending-repos.com/repositories/openai/whisper)\n- [5 ![modem-dev/hunk avatar](https://avatars.githubusercontent.com/u/207912732?v=4&s=48) modem-dev/hunk8.1k★](https://trending-repos.com/repositories/modem-dev/hunk)[See all](https://trending-repos.com/?period=monthly)\n\n![nextlevelbuilder/ui-ux-pro-max-skill avatar](https://avatars.githubusercontent.com/u/246974152?v=4&s=32)\n\nnextlevelbuilder/ui-ux-pro-max-skill\n114.0k\n\n![heygen-com/hyperframes avatar](https://avatars.githubusercontent.com/u/65394575?v=4&s=32)\n\nheygen-com/hyperframes39.7k\nJavaScript on top\n\n[Developer tools ![DietrichGebert/ponytail avatar](https://avatars.githubusercontent.com/u/137048761?v=4&s=32) DietrichGebert/ponytail97.1k ![esengine/DeepSeek-Reasonix avatar](https://avatars.githubusercontent.com/u/18465053?v=4&s=32) esengine/DeepSeek-Reasonix32.1k ![stablyai/orca avatar](https://avatars.githubusercontent.com/u/127256420?v=4&s=32) stablyai/orca38.6kJavaScript on top](https://trending-repos.com/collections/dev-tools)\n[Databases ![opengeos/GeoLibre avatar](https://avatars.githubusercontent.com/u/129896036?v=4&s=32) opengeos/GeoLibre5.5k ![Pelski/ytzero avatar](https://avatars.githubusercontent.com/u/6849315?v=4&s=32) Pelski/ytzero440 ![thedotmack/claude-mem avatar](https://avatars.githubusercontent.com/u/683968?v=4&s=32) thedotmack/claude-mem89.8kTypeScript on top](https://trending-repos.com/collections/databases)"},"author":{"name":"Trending Repos","bio":"The market terminal for open source — every GitHub repository quoted by momentum, re-priced every four hours from star and fork velocity."},"metadata":{"timestamp":"2026-08-06T15:47:32.114Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/yGKAUnox2Y/media/0.png","type":"image","width":1200,"height":630}],"aiComments":[]},{"id":"web-p970go","shareId":"XysT8bAnWU","platform":"web","url":"https://arrufat.github.io/zignal/","title":"Zig Documentation","shareMode":"full","createdAt":1786030315153,"postedAt":"2026-08-06T15:31:49.616Z","publishedDate":"2026-08-06T15:31:49.616Z","archivedAt":"2026-08-06T15:31:51.787Z","archivedDate":"2026-08-06T15:31:51.787Z","viewCount":2,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/XysT8bAnWU","contentType":"article","content":{"text":"Loading...\n\n## [src]\n\n## Parameters\n\n## Errors\n\nanyerror means the error set is known only at runtime.\n\n## Search Results\n\n## No Results Found\n\nPress escape to exit search and then '?' to see more options.\n\n## Fields\n\n## Types\n\n## Namespaces\n\n## Global Variables\n\n## Values\n\n## Functions\n\n## Error Sets\n\n## Example Usage\n\n## Source Code\n\n## Keyboard Shortcuts\n\n?Show this help dialog"},"author":{"name":"arrufat.github.io","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/aca5caead7305eb6/avatar-77f0a9606759.svg"},"metadata":{"timestamp":"2026-08-06T15:31:49.616Z"},"media":[],"aiComments":[]},{"id":"web-ro4pbv","shareId":"cEyU7BDk0H","platform":"web","url":"https://playground.foliopdf.dev/","title":"Folio Playground — HTML to PDF in your browser","shareMode":"full","createdAt":1786030243839,"postedAt":"2026-08-06T15:30:31.380Z","publishedDate":"2026-08-06T15:30:31.380Z","archivedAt":"2026-08-06T15:30:34.066Z","archivedDate":"2026-08-06T15:30:34.066Z","viewCount":2,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/cEyU7BDk0H","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/uZNk87usHn/media/0.png","contentType":"article","content":{"text":" "},"author":{"name":"playground.foliopdf.dev","bio":"Convert HTML to PDF instantly. No server, no uploads. Open source, Apache 2.0."},"metadata":{"timestamp":"2026-08-06T15:30:31.380Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/uZNk87usHn/media/0.png","type":"image","width":3024,"height":1900}],"aiComments":[]},{"id":"web-b7lfij","shareId":"nNBS89eWbu","platform":"web","url":"https://croftanalytics.com/","title":"Croft Analytics, Marketing Tools, Search Tool, Search Trends, Share of Search, Share of Searching, Marketing Consultancy, Marketing, Brand, Data Science, Branding, How Brands Grow, Growing Brands, Marketing Effectiveness, Marketing ROI, Advertising, Frank Harrison","shareMode":"full","createdAt":1786029709893,"postedAt":"2026-08-06T15:21:42.194Z","publishedDate":"2026-08-06T15:21:42.194Z","archivedAt":"2026-08-06T15:21:45.363Z","archivedDate":"2026-08-06T15:21:45.363Z","viewCount":1,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/nNBS89eWbu","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/4Grnn1BQGF/media/0.webp","contentType":"article","content":{"text":"## ABOUT\n\n#### Croft Analytics\n\nCroft Analytics provides apps and advice for marketers and agencies:\n\nGlobal apps that track trends across social and search platforms - for example see [Share of Searching](https://www.shareofsearching.com/)\n\nAdvice, projects, and reports on marketing and media topics.\n\nMarketing, media, and consumer desk research.\n\n[![Image](https://img1.wsimg.com/isteam/ip/10ab9f80-7651-45a5-b821-244016eea05e/FRANK%20HARRISON.jpg/:/rs=w:365,h:365,cg:true,m/cr=w:365,h:365)](https://www.linkedin.com/in/frharrison/)\n\n#### Frank Harrison\n\nI founded Croft Analytics in 2020 following many years in senior R&D roles at Publicis Groupe companies.\n\nCroft Analytics provides data-driven apps, such as [Share of Searching](https://www.shareofsearching.com/), for tracking brands online.\n\nPreviously I was Global Research Lead at Publicis Media where I worked with agency teams and clients across many categories and count\n\nI founded Croft Analytics in 2020 following many years in senior R&D roles at Publicis Groupe companies.\n\nCroft Analytics provides data-driven apps, such as [Share of Searching](https://www.shareofsearching.com/), for tracking brands online.\n\nPreviously I was Global Research Lead at Publicis Media where I worked with agency teams and clients across many categories and countries.\n\nSince 1996 I have been a Fellow of the UK’s Institute of Practitioners in Advertising (IPA).\n\n## SERVICES\n\n![Croft Analytics Services](data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=)\n\n#### APPS FOR MARKETERS AND AGENCIES\n\nGlobal web tracking tools that analyse and show trends across social and search platforms - see Share of Searching at [https://www.shareofsearching.com](https://www.shareofsearching.com/)\n\n#### ADVICE\n\n- Scientific rules for brand growth\n- Applying brand growth rules to media strategies and executions\n- Creating, using, measuring distinctive assets\n- Maximising physical and mental availability\n- Measuring advertising return on investment\n\n#### RESEARCH AND REPORTS\n\nDesk and primary research projects.\n\n#### SUPPORT\n\nQuick answers to marketing and media questions.\n\n#### SHARE OF SEARCHING\n\nShare of Searching is a global app that charts search trends across Google, YouTube, Bing, and Amazon. Users can view trends in search volumes and % share of search for entered lists of search terms with data back to 2004. Examine search trends in any country or worldwide for brands, companies, events, celebrities, topics etc.\n\nMarketers can compare trends in search interest for all brands in their categories. In many categories a brand’s share of category search can be used to predict its market share. Share of Searching also reveals the search terms related to a brand (or other search term) and the trend in search interest for all related terms.\n\nEnter search terms (such as a list of brands) to see charts of trends in search volumes and % share of search. Filter the data by country and date range. Export charts to PowerPoint and data to Excel.\n\nChart search volumes and share of search trends for terms that are related to an entered search term (for example a brand or topic).\n\n**The value of share of search trends for marketers**\n\nAnalysis of Google search and market share data has shown that, for brands in many categories, a brand’s share of category search volume can be used to predict its market share. The use of share of search data to predict market shares particularly applies where search is a major activity in the process of deciding what to buy. For example in (but not limited to) categories such as airlines, automotive, finance, movies, retail, travel, and electronic goods.\n\n**To start using the app click on the link below**\n\n## ENDORSEMENTS\n\n#### Anne Austin, Business and Non-Fiction Editing Specialist\n\n#### Steve Hyde, CEO & Global Talent Lead, 360xec Executive Search\n\n#### Steve Hyde, CEO & Global Talent Lead, 360xec Executive Search\n\n![Image](data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=)\n\nFrank is one of those people who is just bubbling over with ideas all the time. That mixture of enormous creative energy with a sharp analytical mind is what makes him so good at what he does, and why he's so inventive. Over the years I worked at Zenith, I think I must have lost count of the number of innovations he introduced in terms of data analysis and insights which led to the creation of very valuable proprietary tools for the company. To this, I feel moved to add that he is the very epitome of bonhomie. A delightful fellow with impeccable manners and a sunny demeanour. Who wouldn't want to work with someone like that?\n\n*October 27, 2020*\n\n*Publications &* [*Global Intelligence Manager*](https://www.linkedin.com/in/annejvaustin/)\n\n[*Z*](https://www.linkedin.com/in/annejvaustin/) *enith*\n\n[*2*](https://www.linkedin.com/in/annejvaustin/) *011-2020*\n\n#### Steve Hyde, CEO & Global Talent Lead, 360xec Executive Search\n\n#### Steve Hyde, CEO & Global Talent Lead, 360xec Executive Search\n\n#### Steve Hyde, CEO & Global Talent Lead, 360xec Executive Search\n\n![Image](data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=)\n\nHaving worked with Frank for many years and experienced so much change over that time, Frank remains one of the most knowledgeable and capable executives across the marketing and communications industry. His input has consistently been regarded most highly by Clients we have served and he is probably responsible for more new business wins and more business retention than anyone else I know. His analytical mind and shrewd vision combined with an encyclopaedic knowledge makes him an enormously valuable asset to any business be it as a senior employee or executive consultant. I cannot recommend Frank too highly.\n\n*September 4, 2020*\n\n[*CEO & Global Talent Lead*](https://www.linkedin.com/in/stevehyde1/)\n\n[*360xec Executive Search Ltd.*](https://www.linkedin.com/in/stevehyde1/)\n\n[*2011 – Present*](https://www.linkedin.com/in/stevehyde1/)\n\n#### Madeline Condron, Business Director EMEA, Starcom\n\n#### Steve Hyde, CEO & Global Talent Lead, 360xec Executive Search\n\n#### Neil Ascher, Managing Partner, Midas Exchange, WPP, USA\n\n![Image](data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=)\n\n#### Antony Young, Co-Founder, The Digital Cafe, New Zealand\n\n#### Neil Ascher, Managing Partner, Midas Exchange, WPP, USA\n\n#### Antony Young, Co-Founder, The Digital Cafe, New Zealand\n\n![Image](data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=)\n\nFrank Harrison is a genius. He has been the architect behind ZOOM, MediaDNA and Touchpoints... communication insight and analytic innovations that have helped to deliver a competitive advantage to the ZenithOptimedia Worldwide network. In addition to being wonderfully strategic, he has that rare quality to be able to present highly complex and technical material into simply, commercial and vibrant ideas. He's does this without an ego or political bone in his body. I hugely valued what he brought to our agency when he reported to me, and he has continued to bring to our Group since stepping into his global role.\n\n*March 23, 2010,*\n\n[*CEO*](https://www.linkedin.com/in/antonyyoung8/)\n\n[*Optimedia International US Inc.*](https://www.linkedin.com/in/antonyyoung8/)\n\n[*2006 – 2011*](https://www.linkedin.com/in/antonyyoung8/)\n\n#### Terence Chan, Principal, Project Oxygen, Singapore\n\n#### Neil Ascher, Managing Partner, Midas Exchange, WPP, USA\n\n#### Antony Young, Co-Founder, The Digital Cafe, New Zealand\n\n![Image](data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=)\n\nFrank \"Propeller Head\" Harrison was the amazing Brit who carved a bedrock foundation of excellence for Zenithmedia (and ZenithOptimedia), not just in UK, but for the rest of us all over the world. A pioneer of the modern day Media Agency, he pushed, and continues to push, the limits for the media industry in many areas way ahead of his time and peers. His inspired work lives on in all of us fortunate to be touched by it.\n\n*April 12, 2009*\n\n[*Chief Operations Officer*](https://www.linkedin.com/in/terencechan/)\n\n[*Zenith Media Singapore*](https://www.linkedin.com/in/terencechan/)\n\n[*1999 – 2009*](https://www.linkedin.com/in/terencechan/)"},"author":{"name":"Croft Analytics","bio":"Croft Analytics provides brand tracking tools for marketers, including Share of Searching, a search trends tool charting search volumes and % share of search"},"metadata":{"timestamp":"2026-08-06T15:21:42.194Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/4Grnn1BQGF/media/0.webp","type":"image","width":2560,"height":1094}],"aiComments":[]},{"id":"web-t9qwi","shareId":"tpdJw5xTvw","platform":"web","url":"https://www.shareofsearching.com/","title":"Share of Searching – Track Share of Search Trends on Google, YouTube & Amazon","shareMode":"full","createdAt":1786029352716,"postedAt":"2026-08-06T15:20:36.420Z","publishedDate":"2026-08-06T15:20:36.420Z","archivedAt":"2026-08-06T15:15:48.762Z","archivedDate":"2026-08-06T15:15:48.762Z","viewCount":2,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/tpdJw5xTvw","contentType":"article","content":{"text":"“Share of Searching is a fantastic tool that has enabled me to mature the organic search capability for the organisation. It has helped me to discover trends with competitors so we could apply some of this logic to predict what could happen with our brands, post merger. It has been instrumental in measuring brand awareness and organic share of search in our category. I’ve been very impressed with how receptive and responsive the team at SOS are to feedback and they’ve always been able to resolve any issues in a timely manner.”\n\nMona Doncevska — Digital Growth Marketing Manager – Organic Search\n\nAustralian Retirement Trust\n\n“Share of search is a valuable tool for Tempur to evaluate our brand health and make informed decisions about marketing strategies and investments. By tracking our share of search over time, we can get a sense of how our brand is performing relative to our competitors and whether we are gaining or losing mindshare among our audience. We use the Croft Analytics tools to make crucial decisions to continue our media spend or pull back if it does not have the desired effect.”\n\nBen Wilkes — International Marketing Manager\n\nTempur Sealy International\n\n“I use Share of search for market share, product launches, competitor and trend analysis and much more. It has helped me tremendously in taking data driven decisions.”\n\nDaniel Sandvik — CCO\n\nVitamail\n\n“Share of Searching enables us to accelerate time consuming calculations for brand marketing.Share of Searching is not just an important tool, but a valuable witness of our ups and downs.”\n\nMykhailo Ivonin — Head of Brand\n\nTK Services International\n\n“We use Share of Search as one of our key KPIs as there’s more to gaining customer share of mind and consideration than just ad share of voice, the strong relationship to market share in many cases demonstrates this.”\n\nJonathon Quirk — Group Consumer Planning & Insights\n\nInchcape Australia\n\n“We’ve been using the Share of Searching tool for a couple of years now and it has fed many of our strategies, pitches, and client arguments when it comes to how we should approach our media strategy not only in terms of digital but offline as well.The very intuitive and friendly interface, the fact that we can use a lot more queries to compare versus Google Trends, the clear overview of seasonality and the new addition of the YouTube search feature, makes it one of our go - to platforms for research, analysis, and insights.Great work!”\n\nAndrea Andrus — Digital Strategy & New Business Romania\n\nEssenceMediacom\n\n“Share of Searching is a useful tool that allows us to know more about categories or industries.Once the connection between Share Of Search and Share Of Market is established, you could use SOS as a proxy(SOM) to recommend a budget.Since SOM is a metric that takes time to have.”\n\nCarolina Garcia — Senior Data Analyst\n\nPublicis Groupe\n\nWhy Share of Search Matters\n\n### Search behaviour reveals market momentum before sales data does.\n\nShare of Search has become a leading indicator used by marketers, agencies and analysts to understand brand growth, competitive pressure and future market share.\n\nTrusted By\n\nMarketers, Agencies & Researchers\n\nUsed globally to track brand demand, identify emerging competitors and benchmark market momentum."},"author":{"name":"shareofsearching.com","bio":"Visualize and compare brand share of search across Google, YouTube, and Amazon. Share of Searching is your tool for tracking search trends globally"},"metadata":{"timestamp":"2026-08-06T15:20:36.420Z"},"media":[],"aiComments":[]},{"id":"web-o1efs3","shareId":"vvH3Wg4X2h","platform":"web","url":"https://passion.digital/","title":"Digital Marketing Agency London, UK","shareMode":"full","createdAt":1786029337893,"postedAt":"2024-08-13T15:29:50.000Z","publishedDate":"2024-08-13T15:29:50.000Z","archivedAt":"2026-08-06T15:15:31.596Z","archivedDate":"2026-08-06T15:15:31.596Z","viewCount":1,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/vvH3Wg4X2h","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/MHGQqCGFl9/media/0.png","contentType":"article","content":{"text":"## Search has changed and we have changed with it.\n\nYour customers are no longer just searching Google — they’re searching LLMs, social platforms, marketplaces and AI-powered discovery tools. As a search-led digital marketing agency in London, we help ambitious brands show up wherever that discovery happens.\n\n**Full Funnel Performance**\n\nWhen critical thinking, creative thinking and genuine passion come together, problems get solved. Our search expertise spans SEO, PPC, content marketing, paid social, GEO and data analytics — and we bring both rigour and fresh thinking to every one of them, ensuring your brand attracts, engages and converts the right audience at every stage of their journey.\n\nWe help ambitious brands get found, chosen and remembered — wherever discovery happens.\n\n![Image](https://passion.digital/app/uploads/2026/05/problem-solving-1557-x-726-px-1557-x-726-px.jpg)\n\n## Why work with us?\n\nBehind every standout campaign is a team of marketing experts and strategists who live and breathe digital marketing. Great campaigns are powered by great people, their experience, insight and ability to adapt to any challenge. That’s why we don’t just offer services. We are a digital marketing agency in London that builds long term partnerships, and work as an extension of your team to craft digital strategies that drive real business growth.\n\nFull-Funnel Performance\n\nWe don't just do search — we think in full funnels. From search and discovery to final conversion, we connect the dots across all digital marketing channels so your brand performs at every stage of the customer journey.\n\nBuilt to Retain\n\nWe measure success by what we keep. An 8.5 NPS, multi-year retainers, and team tenure well above industry standard — we grow by keeping what matters: our clients and our people.\n\nIndependent care, network scale\n\nMost clients can't have both. We can. As part of Stellar — the AI-native performance network powered by Pixis AI — we bring network-level technology and innovation with the senior attention of an independent digital marketing agency.\n\n## Digital Marketing Services.\n\nWe like to work with ambitious brands who are looking for a digital marketing agency in London with a growth mindset and a passion for making a difference. We offer a range of services designed to work together to accelerate growth and drive results.\n\n**Paid Search**\n\nMake every click count. Google Ads and Microsoft Ads work harder by targeting the right keywords, audiences and intent. Get in front of high-intent searchers on Google, Bing and other paid search platforms with data-led [PPC campaigns](https://passion.digital/services/ppc-agency/) that drive clicks, conversions and revenue.\n\n**SEO**\n\n[SEO](https://passion.digital/services/seo-agency/) is more than just rankings; it’s about visibility, authority, and growth. From technical optimisation to content strategy and GEO, we fine-tune every element to ensure your brand stands out in search and LLMS, drives organic traffic, and reaches the right audience at the right time.\n\n**Generative Engine Optimisation (GEO)**\n\nWith **60% of searches** now ending without a click, your customers are finding answers in AI overviews, ChatGPT, and Perplexity – not only on your website. We ensure your brand appears in both traditional search results and AI-powered answers with [Generative Engine Optimisation (GEO)](https://passion.digital/services/ai-search/).\n\n**Paid Social**\n\nEngage with your target audience on popular [social media platforms](https://passion.digital/services/paid-media/social-media-advertising/), amplifying your brand awareness and driving high-quality leads through targeted ads.\n\n**Content Marketing**\n\nGreat [content](https://passion.digital/services/seo-agency/content-marketing/) isn’t just seen. It’s remembered. From blogs and landing pages to social, digital PR, infographics and social media, we create content that fuels SEO, engages audiences and builds brand authority. Every piece is crafted with search intent, user behaviour, and platform trends in mind.\n\n**Programmatic**\n\nSmarter ads, bigger impact with [progammatic](https://passion.digital/services/paid-media/display-advertising/). AI-driven digital advertising ensures brands stay visible across display networks, native ads, connected TV and digital out-of-home (DOOH). Automated bidding, audience segmentation and real-time optimisation put the right message in front of the right people at scale.\n\n**Conversion Rate Optimisation**\n\nImprove your website’s performance and increase sales by optimising user experience and streamlining the customer journey.\n\n**Amazon Advertising**\n\nIncrease product visibility and sales on the world’s largest e-commerce platform, effectively targeting ready-to-buy customers.\n\n**Retail Media**\n\nMaximise your brand’s presence within leading online retail environments, driving both online and offline sales with highly targeted ads.\n\n**Connected TV**\n\nCaptivate a modern audience with engaging ads on smart TVs, combining the reach of traditional TV with the precision of digital marketing.\n\n## Our Clients.\n\n- **View all:**\n- [Case studies](https://passion.digital/case-studies/)\n[Securing 15 Featured Snippets & 21 AI Overviews Shoosmiths Serious Injury See how we did it](https://passion.digital/case-studies/shoosmiths-serious-injury-seo-case-study/)\n\n[Increasing lead volume by +1,420% See how we did it](https://passion.digital/case-studies/knight-frank-vendor-paid-media/)\n\n[A 201% increase in organic generic clicks & 425% increase in paid leads See how we did it](https://passion.digital/case-studies/cloud-gateway-seo-and-paid-media-case-study/)\n\nPassion put so much time and effort into understanding the business**,** the tone of voice and our position in the market**,** they've provided a unique ability to marry a numbers-focused strategy with a content plan**.** I haven't experienced that with another digital marketing agency**.**\n\nThe Thinking Traveller"},"author":{"name":"Passion Digital®","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/538dae7a99f29cac/avatar-04c806e65c16.png","bio":"Digital Marketing Agency based in London. Award-winners in Search Marketing: SEO, PPC, Social, Data & Analytics"},"metadata":{"timestamp":"2024-08-13T15:29:50.000Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/MHGQqCGFl9/media/0.png","type":"image","width":400,"height":217}],"aiComments":[]},{"id":"web-pj3051","shareId":"ciVlv0OihQ","platform":"web","url":"https://open-design.ai/","title":"Best Open Source Claude Design Alternative","shareMode":"full","createdAt":1786029045960,"postedAt":"2026-08-06T15:10:37.106Z","publishedDate":"2026-08-06T15:10:37.106Z","archivedAt":"2026-08-06T15:10:39.677Z","archivedDate":"2026-08-06T15:10:39.677Z","viewCount":2,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/ciVlv0OihQ","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/I53IaFL5z7/media/0.png","contentType":"article","content":{"text":"## Open Design is the open-source, agentic vibe design workspace — it turns the coding agent you already run into a design engine whose output you fully own. When an LLM first proved it can truly design — real design work, not just copy — that capability arrived closed, hosted, and model-locked. Open Design opens it up: local, BYOK, Apache-2.0.\n\n![Design happens on the desktop. Local files, Figma exports, and code repos are directly readable, and the agent has full terminal-execution power.](https://open-design.ai/about/desktop-native.webp)\n\nDesign happens on the desktop.\nLocal files, Figma exports, and code repos are directly readable, and the agent has full terminal-execution power.\n\n![The Claude Code / Codex / Cursor on your machine are already strong enough. Open Design wires them into a complete design workflow.](https://open-design.ai/about/access-agent.webp)\n\nThe Claude Code / Codex / Cursor on your machine are already strong enough.\nOpen Design wires them into a complete design workflow.\n\n![Every choice settles into a design system, preferences, and memory, so the next generation lands closer to what you want.](https://open-design.ai/about/self-evolution.webp?v=4)\n\nEvery choice settles into a design system, preferences, and memory, so the next generation lands closer to what you want.\n\n## From idea to prototype, web, slides, and HTML video\n\nBrief → Template → Visual direction → Artifact → Memory\n\n1. 01Choose a starting point\n2. 02Set the visual direction\n3. 03Generate the artifact\n4. 04Deliver or make a video\n\n![Image](https://open-design.ai/step-cards/step-1.webp?v=8)\n\nDescribe your goal in one line, or start from a template / plugin.\n\n![Image](https://open-design.ai/step-cards/step-2.webp?v=8)\n\nOnce a direction is set, palette, type, and spacing flow into generation automatically.\n\n![Image](https://open-design.ai/step-cards/step-3.webp?v=7)\n\nThe agent reads all context, produces real runnable files, and previews and edits them live in a sandbox.\n\n![Image](https://open-design.ai/step-cards/step-4.webp?v=9)\n\nExport it to engineering to keep building, or turn it into a marketing video with HyperFrames.\n\n## What can you make with Open Design?\n\nPrototypes, landing pages, slide decks, dashboards, brand and design systems — even HTML video. Open Design turns each into real, runnable files, driven by your own coding agent and ready to ship or hand off to engineering.\n\n[Prototype](https://open-design.ai/plugins/templates/prototype/) [Live Artifact](https://open-design.ai/plugins/templates/live-artifact/) [Slides](https://open-design.ai/plugins/templates/deck/) [Image](https://open-design.ai/plugins/templates/image/) [HyperFrames](https://open-design.ai/plugins/templates/hyperframes/) [Video](https://open-design.ai/plugins/templates/video/)\n\n## Plug in 21+ coding agents, zero config\n\nEvery stage is iterative, visual, and research-driven — composable files, not opaque prompts.\n\n![Devin](https://open-design.ai/agent-icons/devin.png)\n\n![Aider](https://open-design.ai/agent-icons/aider.png)\n\n![Trae](https://open-design.ai/agent-icons/trae-cli.png)\n\n![21+ Coding Agent](https://open-design.ai/method-coding-agent.png)\n\n## From around the world, 389 contributors are building Open Design together\n\n## Open Design FAQ — open source, local-first, and Claude Design alternative\n\n84.1K+ stars · Apache-2.0 · Free\n\n1. 01What is Open Design?Open Design is the official open-source AI design workspace from the nexu-io/open-design project. It turns a local coding agent — Claude Code, Codex, Cursor, Gemini CLI, OpenCode, or Qwen — into a design engine driven by composable skills and portable DESIGN.md systems.\n2. 02Is Open Design official?Yes. The canonical project lives at https://open-design.ai/ and the source is on GitHub at https://github.com/nexu-io/open-design. \"Open Design\", \"OpenDesign\", \"open-design\", and \"Open Design AI\" all refer to this same project.\n3. 03How is Open Design different from Claude Design?Claude Design is a hosted product tied to a single vendor. Open Design is local-first, open source under Apache-2.0, and BYOK: you bring your own agent, credentials, and DESIGN.md system.\n4. 04Is Open Design an open-source Claude Design alternative?Yes — Open Design is the open-source, local-first Claude Design alternative. Where Claude Design is closed, hosted, and locked to Anthropic models, Open Design is Apache-2.0, runs on your own machine, and is BYOK, so you drive it with Claude Code, Codex, Cursor, Gemini, OpenCode, or Qwen and keep every artifact as files you own. [Learn more →](https://open-design.ai/alternatives/claude-design/)\n5. 05What is a vibe design workspace?A vibe design workspace is where you design by describing intent to an AI agent — from prompt to prototype, web page, slides, or HTML video — instead of hand-placing every element. Open Design is an open-source, agent-native vibe design workspace: it wires the coding agent you already run into a full design workflow, so one tool takes you from a rough idea to production-ready output you own. [Learn more →](https://open-design.ai/blog/what-is-vibe-design/)\n6. 06Does Open Design run locally?Yes. The desktop app, daemon, and skill runtime run on your machine. Generated artifacts land in your project directory instead of being forced through a vendor cloud.\n7. 07Which coding agents does Open Design support?Open Design ships 17 first-party BYOK adapters out of the box: Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot CLI, Grok, Hermes, Kimi, Devin for Terminal, OpenCode, Qwen, DeepSeek, Pi, Mistral Vibe, Kiro, Kilo, and Qoder. Any adapter that speaks the same skill protocol works — switching agents is a config change, not a redesign.\n8. 08Can I self-host or fork it?Yes. The code is Apache-2.0. You can fork the repo, edit skills, add your own DESIGN.md systems, or run the daemon on your own machines.\n9. 09Is my data sent to Anthropic, OpenAI, or Google?Only your prompt and skill context goes to whichever provider you bring keys for (BYOK). Open Design has no server of its own — the daemon talks to your provider directly. Generated artifacts land as files in your project directory, not in any vendor cloud.\n10. 10Can I run Open Design without installing the CLI or desktop app?Not today. Open Design is local-first by design — the minimum is a local daemon plus an agent (Claude Code, Codex, Cursor, Gemini CLI, or one of the 17 supported adapters). A hosted sandbox is on the roadmap but not the priority: artifacts in your repo beat documents in someone else's database.\n11. 11How much does Open Design cost?The product is free and Apache-2.0 — there is no Open Design subscription. You pay the API costs of whichever provider you use (Anthropic, OpenAI, Google, Mistral, xAI, Moonshot, etc.), billed directly to your account. BYOK keeps both the credentials and the spend on your side of the line.\n12. 12Can I self-host Open Design on Vercel, Cloudflare, or my own server?Yes. The daemon runs anywhere Node 24 runs, and the landing page is a static Astro build that deploys to Cloudflare Pages, Vercel, or Netlify as-is. Teams running shared deployments typically pin the daemon to a machine inside their network and point each developer's CLI at it.\n13. 13How do I move my brand into Open Design?Drop a screenshot or a Figma export into the web UI and ask your agent to extract a brand into a DESIGN.md file. Save that file under design-systems// in your repo; every skill then renders in that brand without re-prompting. /alternatives/claude-design/ describes the same flow in step form.\n14. 14Can I switch agents without redoing my work?Yes. Skills and DESIGN.md systems are agent-agnostic — the same SKILL.md file renders against Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, Grok, Hermes, Qwen, or any other supported adapter. Switching agents is a config change in the daemon, not a redesign.\n15. 15What's on the Open Design roadmap?The live roadmap is at docs/roadmap.md in the GitHub repo, and weekly release notes ship through GitHub Releases. Major themes for the next quarter: more agent adapters, richer template families (3D, video, audio), and an optional shared-daemon mode for design teams."},"author":{"name":"Open Design","bio":"Open-source vibe design workspace & Claude Design alternative — build prototypes, landing pages, dashboards, slides & HTML video with your own coding agent."},"metadata":{"timestamp":"2026-08-06T15:10:37.106Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/I53IaFL5z7/media/0.png","type":"image","width":1200,"height":630}],"aiComments":[]},{"id":"web-mea7is","shareId":"dKFooGxprS","platform":"web","url":"https://ccswitch.io/en/changelog","title":"CC Switch 官方网站 - AI 编程 CLI 统一管理工具","shareMode":"full","createdAt":1786028752219,"postedAt":"2026-08-06T15:05:46.851Z","publishedDate":"2026-08-06T15:05:46.851Z","archivedAt":"2026-08-06T15:05:48.894Z","archivedDate":"2026-08-06T15:05:48.894Z","viewCount":6,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/dKFooGxprS","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/i8fD0l92D6/media/0.png","contentType":"article","content":{"text":"## CC Switch 官方网站\n\nCC Switch 是开源的 AI 编程 CLI 统一管理工具，支持 Claude Code、Codex、Gemini CLI、OpenCode、OpenClaw 和 Hermes Agent。\n\n[GitHub 官方仓库](https://github.com/farion1231/cc-switch) · [官方文档](https://ccswitch.io/zh/docs) · [更新日志](https://ccswitch.io/zh/changelog)"},"author":{"name":"CC Switch Team","bio":"统一管理 Claude Code、Codex、Gemini CLI、OpenCode、OpenClaw 和 Hermes Agent 的供应商配置、本地路由、MCP、Skills、会话与用量统计。"},"metadata":{"timestamp":"2026-08-06T15:05:46.851Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/i8fD0l92D6/media/0.png","type":"image","width":1200,"height":630}],"aiComments":[]},{"id":"web-pj7raw","shareId":"QSraCgmCH9","platform":"web","url":"https://github.com/EcoPasteHub/EcoPaste","title":"EcoPasteHub/EcoPaste: 🎉跨平台的剪贴板管理工具 | Cross-platform clipboard management tool","shareMode":"full","createdAt":1786028390665,"postedAt":"2026-08-06T14:59:44.211Z","publishedDate":"2026-08-06T14:59:44.211Z","archivedAt":"2026-08-06T14:59:46.768Z","archivedDate":"2026-08-06T14:59:46.768Z","viewCount":1,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/QSraCgmCH9","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/C8iNNyUn2z/media/0.png","contentType":"article","content":{"text":"[![EcoPaste](https://github.com/EcoPasteHub/EcoPaste/raw/master/public/logo.png)](https://github.com/EcoPasteHub/EcoPaste/blob/master/public/logo.png)\n\n## EcoPaste\n\n**A local-first clipboard manager for macOS and Windows.**\n\nEnglish | [简体中文](https://github.com/EcoPasteHub/EcoPaste/blob/master/README.zh-CN.md)\n\n[![Tauri v2](https://camo.githubusercontent.com/a4da00fc25acb305ecdde62191c55534d580236470932a83625aca384805eb49/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f54617572692d76322d3234633864623f7374796c653d666c61742d737175617265)](https://camo.githubusercontent.com/a4da00fc25acb305ecdde62191c55534d580236470932a83625aca384805eb49/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f54617572692d76322d3234633864623f7374796c653d666c61742d737175617265) [![Rust first](https://camo.githubusercontent.com/3a42e549f44704423b36898fe924c0c26299382d366a66c01d01c9b8256ec971/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f527573742d66697273742d6237343130653f7374796c653d666c61742d737175617265)](https://camo.githubusercontent.com/3a42e549f44704423b36898fe924c0c26299382d366a66c01d01c9b8256ec971/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f527573742d66697273742d6237343130653f7374796c653d666c61742d737175617265) [![React 19](https://camo.githubusercontent.com/0a5a72e2d162a8554bea2c5a421e182239ea54e068627e99274bdc99145dd960/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f52656163742d31392d3631646166623f7374796c653d666c61742d737175617265)](https://camo.githubusercontent.com/0a5a72e2d162a8554bea2c5a421e182239ea54e068627e99274bdc99145dd960/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f52656163742d31392d3631646166623f7374796c653d666c61742d737175617265) [![macOS](https://camo.githubusercontent.com/7ce59ab3ed4ee825112b749d6af6b36054cb75abd668c9c26117ef470d875325/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f6d61634f532d737570706f727465642d3030303030303f7374796c653d666c61742d737175617265266c6f676f3d6170706c65266c6f676f436f6c6f723d7768697465)](https://camo.githubusercontent.com/7ce59ab3ed4ee825112b749d6af6b36054cb75abd668c9c26117ef470d875325/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f6d61634f532d737570706f727465642d3030303030303f7374796c653d666c61742d737175617265266c6f676f3d6170706c65266c6f676f436f6c6f723d7768697465) [![Windows](https://camo.githubusercontent.com/266620c2b31434191ed05909035c4902dd6c257dc789544444841bd02d746ca7/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f57696e646f77732d737570706f727465642d3030373864343f7374796c653d666c61742d737175617265266c6f676f3d77696e646f7773266c6f676f436f6c6f723d7768697465)](https://camo.githubusercontent.com/266620c2b31434191ed05909035c4902dd6c257dc789544444841bd02d746ca7/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f57696e646f77732d737570706f727465642d3030373864343f7374796c653d666c61742d737175617265266c6f676f3d77696e646f7773266c6f676f436f6c6f723d7768697465)\n\n## About\n\nEcoPaste is an open-source desktop clipboard manager built with a Rust-first Tauri architecture: durable behavior lives in Rust, while the React frontend focuses on rendering and interaction.\n\nThe app is designed to be fast, lightweight, and maintainable, with local storage, SQLite search, native shortcuts, tray integration, backup support, and a focused cross-platform surface for macOS and Windows.\n\n## Features\n\n- Capture clipboard history for plain text, HTML, RTF, images, files, and folders.\n- Search clipboard content and notes with SQLite FTS5.\n- Filter history by source application and content type.\n- Protect sensitive content by skipping high-confidence secrets such as private keys, service tokens, AWS keys, and JWTs.\n- Preview text, images, and files in a dedicated preview window.\n- Paste, copy, copy as plain text, reveal files, open links, add notes, pin, favorite, delete, and drag items out to other apps.\n- Organize history with favorites, pinned items, notes, custom groups, and configurable item actions.\n- Tune capture order, size limits, retention, display density, list sorting, and window behavior.\n- Export and import `.ecopastebak` backups, including encrypted backup containers.\n- Keep clipboard data, resources, and settings local to your machine.\n\n## Contributing\n\nDevelopment setup, architecture notes, quality checks, and contribution expectations live in the [contribution guide](https://github.com/EcoPasteHub/EcoPaste/blob/master/CONTRIBUTING.md).\n\n## License\n\nEcoPaste is licensed under the [Apache License 2.0](https://github.com/EcoPasteHub/EcoPaste/blob/master/LICENSE)."},"author":{"name":"EcoPasteHub","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/703f220225baa5bc/avatar-6a9577cd4f7f.svg","bio":"🎉跨平台的剪贴板管理工具 | Cross-platform clipboard management tool - EcoPasteHub/EcoPaste"},"metadata":{"timestamp":"2026-08-06T14:59:44.211Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/C8iNNyUn2z/media/0.png","type":"image"}],"aiComments":[]},{"id":"web-esaweh","shareId":"T8DA3zPrMh","platform":"web","url":"https://github.com/OpenCoworkAI/open-codesign","title":"OpenCoworkAI/open-codesign: Open-source Claude Design alternative. One-click import your Claude Code / Codex API key. Prompt → prototype / slides / PDF. Multi-model (Claude, GPT, Gemini, Kimi, GLM, Ollama). BYOK, local-first, MIT.","shareMode":"full","createdAt":1786028385422,"postedAt":"2026-08-06T14:59:35.977Z","publishedDate":"2026-08-06T14:59:35.977Z","archivedAt":"2026-08-06T14:59:40.118Z","archivedDate":"2026-08-06T14:59:40.118Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/T8DA3zPrMh","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/7HIe3478aa/media/0.png","contentType":"article","content":{"text":"## Open CoDesign\n\n**简体中文**: [README.zh-CN.md](https://github.com/OpenCoworkAI/open-codesign/blob/main/README.zh-CN.md)\n\n\n\n> Your prompts. Your model. Your laptop. Turn prompts into polished artifacts — locally, openly, and with whichever model you already pay for.\n\n[Website](https://opencoworkai.github.io/open-codesign/) · [Quickstart](#quickstart) · [What's new](https://github.com/OpenCoworkAI/open-codesign/releases) · [Changelog](https://github.com/OpenCoworkAI/open-codesign/blob/main/CHANGELOG.md) · [Discussions](https://github.com/OpenCoworkAI/open-codesign/discussions) · [Docs](https://opencoworkai.github.io/open-codesign/quickstart) · [Contributing](https://github.com/OpenCoworkAI/open-codesign/blob/main/CONTRIBUTING.md) · [Security](https://github.com/OpenCoworkAI/open-codesign/blob/main/SECURITY.md)\n\n**Open-source alternative to:** [Claude Design](https://opencoworkai.github.io/open-codesign/claude-design-alternative) · [v0 by Vercel](https://opencoworkai.github.io/open-codesign/v0-alternative) · [Lovable](https://opencoworkai.github.io/open-codesign/lovable-alternative) · [Bolt.new](https://opencoworkai.github.io/open-codesign/bolt-alternative) · [Figma AI](https://opencoworkai.github.io/open-codesign/figma-ai-alternative)\n\n[![Open CoDesign — prompt on the left, live artifact on the right](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/screenshots/product-hero.png)](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/screenshots/product-hero.png)\n\n[![GitHub release](https://camo.githubusercontent.com/3c1084543d2cf93659568f6edeed7a880d3f67617769beef7f6bccc192337c0e/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f762f72656c656173652f4f70656e436f776f726b41492f6f70656e2d636f64657369676e3f6c6162656c3d72656c6561736526636f6c6f723d633936343432)](https://github.com/OpenCoworkAI/open-codesign/releases) [![License](https://camo.githubusercontent.com/b8cadaa967891081f8f165695470689986c028821dd8a040132f6e661795dc0d/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f6c6963656e73652d4d49542d626c7565)](https://github.com/OpenCoworkAI/open-codesign/blob/main/LICENSE) [![CI](https://camo.githubusercontent.com/a144ee3138a9f895f780933205db0983e67903d7da20eaba4d527c72a562f7f8/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f616374696f6e732f776f726b666c6f772f7374617475732f4f70656e436f776f726b41492f6f70656e2d636f64657369676e2f63692e796d6c3f6c6162656c3d4349)](https://github.com/OpenCoworkAI/open-codesign/actions) [![Stars](https://camo.githubusercontent.com/d51ed738e22de84aa5dff5b3ca160850adc7bd13de83d84453f6ef9eeb764b43/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f4f70656e436f776f726b41492f6f70656e2d636f64657369676e3f7374796c653d736f6369616c)](https://github.com/OpenCoworkAI/open-codesign/stargazers) [![WeChat Group](https://camo.githubusercontent.com/de28abebc807f18bfaef6d860fee91aa4a51c022032ce52686c3fc2a8405b8b2/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f5765436861742d47726f75702d3037433136303f6c6f676f3d776563686174266c6f676f436f6c6f723d7768697465)](#community)\n\n[![Last commit](https://camo.githubusercontent.com/9e75a55958514feba993243e6156ef8e21ec46c6e44523c85e5668ee32f19cdc/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f6c6173742d636f6d6d69742f4f70656e436f776f726b41492f6f70656e2d636f64657369676e3f6c6162656c3d6c617374253230636f6d6d697426636f6c6f723d343062346131)](https://github.com/OpenCoworkAI/open-codesign/commits/main) [![Commit activity](https://camo.githubusercontent.com/88e9b98190ddf2d08ad340ec867f4ce463be68c5211b34c75de2556e2d997606/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f636f6d6d69742d61637469766974792f6d2f4f70656e436f776f726b41492f6f70656e2d636f64657369676e3f6c6162656c3d636f6d6d6974732532466d6f6e7468)](https://github.com/OpenCoworkAI/open-codesign/pulse) [![Contributors](https://camo.githubusercontent.com/34e76e792ee9adce3e95d56b47ddda75c594aa8ee1f1922fede47d1a49b38485/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f636f6e7472696275746f72732f4f70656e436f776f726b41492f6f70656e2d636f64657369676e)](https://github.com/OpenCoworkAI/open-codesign/graphs/contributors) [![Downloads](https://camo.githubusercontent.com/2131faa23b97469e19ffef35f27553cbe0ce8133a7b405a738a80f6149ff7bfa/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f646f776e6c6f6164732f4f70656e436f776f726b41492f6f70656e2d636f64657369676e2f746f74616c3f6c6162656c3d646f776e6c6f61647326636f6c6f723d366335636537)](https://github.com/OpenCoworkAI/open-codesign/releases)\n\n`claude-code` · `claude-design-alternative` · `v0-alternative` · `bolt-alternative` · `lovable-alternative` · `figma-alternative` · `ai-design` · `design-to-code` · `prompt-to-design` · `ai-prototyping` · `desktop-design-tool` · `byok` · `local-first` · `multi-model` · `electron`\n\n\n\n---\n\n\n\n## What's new\n\n- **`feat/decompose-to-ui-kit`** *(branch)* — Image -> componentized `ui_kits//` bundle for coding-agent handoff · Boolean-per-dimension visual parity judge (12 standard checks) · Verify-and-iterate loop · Per-decompose cost row · See [BENCHMARKS.md](https://github.com/OpenCoworkAI/open-codesign/blob/main/BENCHMARKS.md). Refs [#225](https://github.com/OpenCoworkAI/open-codesign/issues/225).\n- **v0.2.0** *(2026-05-09)* — Agentic Design: workspace-backed sessions · permissioned local tools · Files panel upgrades · provider diagnostics · security hardening · `DESIGN.md` design systems\n- **v0.1.4** *(2026-04-23)* — AI image generation · ChatGPT Plus/Codex subscription support · CLIProxyAPI one-click import · API config hardening\n- **v0.1.3** *(2026-04-21)* — Gemini `models/` prefix fix · OpenAI-compatible relay \"instructions required\" fix · third-party relay SSE-truncation hint\n- **v0.1.2** *(2026-04-21)* — Release pipeline · Homebrew / winget / Scoop packaging manifests [Full release history →](https://github.com/OpenCoworkAI/open-codesign/releases) · [Changelog →](https://github.com/OpenCoworkAI/open-codesign/blob/main/CHANGELOG.md)\n\n\n\n---\n\n\n\n## What it is\n\nTurn a prompt into a polished prototype, slide deck, or marketing asset, locally, with the model you already use.\n\n**Open CoDesign is the open-source Claude Design alternative** — built for people who want the speed of AI-native design tools without subscription lock-in, cloud-only workflows, or being forced onto a single provider. An MIT-licensed desktop app, local-first from day one, with BYOK for any model (Claude, GPT, Gemini, DeepSeek, Kimi, GLM, Ollama, or any OpenAI-compatible endpoint) plus direct ChatGPT Plus / Pro / Team subscription sign-in for Codex models. One-click import of existing Claude Code or Codex provider configs, or one-click ChatGPT sign-in, gets you running in under 90 seconds.\n\n\n\n---\n\n\n\n## See it generate\n\nFrom a blank prompt to a finished artifact, the agent plans, writes, self-checks, and ships something with hover states, tabs, and empty states already wired up:\n\n[![Generate a design from scratch](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/demos/generate-from-scratch.gif)](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/demos/generate-from-scratch.gif)\n\n\n\n---\n\n\n\n## Why people star it\n\n- **Runs on your laptop** — no mandatory cloud workspace\n- **Works with your model** — Claude, GPT, Gemini, Ollama, OpenRouter, and more\n- **Exports real files** — HTML, PDF, PPTX, ZIP, Markdown\n- **Shows its work** — live agent activity, visible tool calls, interruptible generation\n\n---\n\n\n\n## Why Open CoDesign?\n\nOpen source, desktop-native, and built for people who do not want their design workflow locked to one model or one cloud.\n\n\n\n| **Open CoDesign** | Claude Design | v0 by Vercel | Lovable |\n| --- | --- | --- | --- |\n| Open source | ✅ MIT | ❌ Closed | ❌ Closed | ❌ Closed |\n| Desktop native | ✅ Electron | ❌ Web only | ❌ Web only | ❌ Web only |\n| Bring your own key | ✅ Any provider | ❌ Anthropic only | ❌ Vercel only | ⚠️ Limited |\n| Local / offline | ✅ Fully local app | ❌ Cloud | ❌ Cloud | ❌ Cloud |\n| Models | ✅ 20+ (Claude, GPT, Gemini, Ollama…) | Claude only | GPT-4o | Multi-LLM |\n| Version history | ✅ Local sessions + workspace files | ❌ | ❌ | ❌ |\n| Data privacy | ✅ On-device app state | ❌ Cloud-processed | ❌ Cloud | ❌ Cloud |\n| Editable export | ✅ HTML, PDF, PPTX, ZIP, Markdown | ⚠️ Limited | ⚠️ Limited | ⚠️ Limited |\n| Price | ✅ Free app, provider/subscription cost only | 💳 Subscription | 💳 Subscription | 💳 Subscription |\n\n\n\n---\n\n\n\n## Highlights\n\n\n\n| ![Click any element, leave a pin, let the model rewrite that region](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/screenshots/comment-mode.png) **Comment, don’t retype.** Click any element, drop a pin, and let the model rewrite only that region. | ![AI-emitted tweaks panel with color pickers and RGB inputs](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/screenshots/tweaks-sliders.png) **AI-tuned sliders.** The model surfaces the parameters worth tweaking, so you can refine color, spacing, and typography without another full prompt. |\n| --- | --- |\n| ![Your Designs hub, filled with real generated artifacts](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/screenshots/hub-your-designs.png) **Every iteration, kept.** Designs are saved locally, with instant switching between recent versions. | ![Live agent panel showing todos and streaming tool calls](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/screenshots/agent-panel.png) **Watch the agent work.** Todos, tool calls, and live progress stay visible and interruptible throughout generation. |\n\n\n\n---\n\n\n\n## Quickstart\n\n**Time to first artifact:** about 3 minutes\n\n**Requires:** one API key, ChatGPT subscription sign-in, or local Ollama\n\n**Runs on:** macOS 12+ (Monterey or later), Windows 10+, Linux (glibc ≥ 2.31)\n\n\n\n### 1. Install\n\n**Package manager** (recommended):\n\n\n\n```\n# macOS\nbrew install --cask opencoworkai/tap/open-codesign\n\n# Windows — Scoop\nscoop bucket add opencoworkai https://github.com/OpenCoworkAI/scoop-bucket\nscoop install opencoworkai/open-codesign\n```\n\n**Or direct download** from the [v0.2.0 GitHub Release](https://github.com/OpenCoworkAI/open-codesign/releases/tag/v0.2.0):\n\n\n\n| Platform | File |\n| --- | --- |\n| macOS (Apple Silicon) | `open-codesign-*-arm64.dmg` |\n| macOS (Intel) | `open-codesign-*-x64.dmg` |\n| Windows (x64) | `open-codesign-*-x64-setup.exe` |\n| Windows (ARM64) | `open-codesign-*-arm64-setup.exe` |\n| Linux (x64, AppImage) | `open-codesign-*-x64.AppImage` |\n| Linux (x64, Debian/Ubuntu) | `open-codesign-*-x64.deb` |\n| Linux (x64, Fedora/RHEL) | `open-codesign-*-x64.rpm` |\n\nEach release ships with `SHA256SUMS.txt` and a CycloneDX SBOM (`*-sbom.cdx.json`) so you can verify what you downloaded.\n\n**More package managers**\n\n| Manager | Command | Status |\n| --- | --- | --- |\n| Homebrew Cask (macOS) | `brew install --cask opencoworkai/tap/open-codesign` | 🟢 Live |\n| Scoop (Windows) | `scoop bucket add opencoworkai https://github.com/OpenCoworkAI/scoop-bucket && scoop install opencoworkai/open-codesign` | 🟢 Live |\n| winget (Windows) | `winget install OpenCoworkAI.OpenCoDesign` | 🟡 PR submitted; waiting for Microsoft review |\n| Flathub (Linux) | `flatpak install flathub ai.opencowork.codesign` | ⏸ Deferred; needs signed build + AppStream metadata |\n| Snap (Linux) | `snap install --dangerous open-codesign-*.snap` | 🟡 Attached to releases best-effort; Snap Store publish not yet wired |\n\nAfter each stable tag push, CI syncs SHAs back into `packaging/` and publishes downstream Homebrew/Scoop updates when the repo secrets are configured. The first winget submission is in review; once Microsoft accepts the package, future winget bumps can be automated from the release workflow. Every `packaging/*/README.md` documents its own channel.\n\n\n\n> **Unsigned installer note:** installers are not notarized or Authenticode-signed yet. On **macOS Sequoia 15+** right-click → Open no longer bypasses Gatekeeper, and \"Open Anyway\" in System Settings often fails. Reliable one-liner: ``` xattr -cr \"/Applications/Open CoDesign.app\" ``` Then double-click normally. (Older 0.1.x builds are installed as `/Applications/open-codesign.app`.) On **Windows**: SmartScreen → More info → Run anyway. Want a verified build? Compile from source — see [CONTRIBUTING.md](https://github.com/OpenCoworkAI/open-codesign/blob/main/CONTRIBUTING.md).\n\n\n\n### 2. Add a provider\n\nOn first launch, Open CoDesign opens the Settings page. Pick the path that matches how you already use models:\n\n- **ChatGPT subscription** — sign in with ChatGPT to use Codex models without pasting an API key.\n- **API key** — paste Anthropic (`sk-ant-...`), OpenAI (`sk-...`), Google Gemini, OpenRouter, SiliconFlow, DeepSeek, or another supported provider key.\n- **Local / keyless** — use Ollama or an IP-allowlisted OpenAI-compatible gateway. Credentials stay in `~/.config/open-codesign/config.toml` and the ChatGPT OAuth token store under the app config directory. Nothing leaves your machine unless your chosen model route requires it.\n\n\n\n### 3. Type your first prompt\n\nPick one of **fifteen built-in demos** — landing page, dashboard, pitch slide, pricing, mobile app, chat UI, event calendar, blog article, receipt/invoice, portfolio, settings panel, and more — or describe your own. A sandboxed prototype appears in seconds.\n\n\n\n---\n\n\n\n## Bring your stack\n\nAlready using Claude Code or Codex? API-key provider configs import in one click, with no copy-paste and no need to re-enter settings. If you use Codex through ChatGPT subscription login, sign in directly from Settings:\n\n[![Import from Claude Code or Codex in one click](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/demos/claude-code-import.gif)](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/demos/claude-code-import.gif)\n\n\n\n---\n\n\n\n## Built-in taste\n\nGeneric AI tools tend to produce generic output. Open CoDesign ships with **twelve built-in design skill modules** — slide decks, dashboards, landing pages, SVG charts, glassmorphism, editorial typography, heroes, pricing, footers, chat UIs, data tables, and calendars — plus a built-in taste layer that steers the model toward considered typography, purposeful whitespace, and meaningful color.\n\nEvery skill is available in every generation. Before the model writes a line of CSS, it selects the skills that fit the brief and reasons through layout intent, design-system coherence, and contrast, bringing higher-quality design behavior to whichever model you choose.\n\nAdd a `SKILL.md` to any project to teach the model your own taste.\n\n\n\n---\n\n\n\n## What you get\n\n\n\n### Models and providers\n\n- **Unified provider model** — Anthropic, OpenAI, Gemini, DeepSeek, OpenRouter, SiliconFlow, local Ollama, or any OpenAI-compatible relay; keyless (IP-allowlisted) proxies supported\n- **One-click import and sign-in** — bring Claude Code / Codex API-key provider configs across, or sign in with ChatGPT subscription for Codex models\n- **Dynamic model picker** — every provider exposes its real model catalogue, not a hardcoded shortlist\n\n### Generation and editing\n\n- **Prompt → HTML or JSX/React component** prototype, rendered in a sandboxed iframe (vendored React 18 + Babel on-device)\n- **Fifteen built-in demos + twelve design skill modules** — ready-to-edit starting points for common design briefs\n- **Live agent panel** — watch tool calls stream in real time as the model edits files\n- **AI image generation** — opt-in bitmap assets for heroes, product shots, backgrounds, and illustrations via OpenAI, OpenRouter, or signed-in ChatGPT subscription\n- **AI-generated sliders** — the model emits the parameters worth tweaking (color, spacing, font)\n- **Comment mode** — click any element in the preview to drop a pin, leave a note, and let the model rewrite only that region\n- **Decompose to UI Kit** — one click in the chat sidebar emits a `ui_kits//` folder (`index.html` + `components/*.tsx` + `tokens.css` + `manifest.json` + `README.md`) shaped for coding-agent handoff. Built-in deterministic + vision verifiers self-check parity using a 12-question boolean rubric (no floating-point arbitrary scores) and re-iterate on gaps. Per-decompose cost surfaces inline as a toast. See [BENCHMARKS.md](https://github.com/OpenCoworkAI/open-codesign/blob/main/BENCHMARKS.md). [![Decompose to UI Kit — source image vs agent-emitted ui_kit, side-by-side parity check](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/screenshots/decompose-to-ui-kit.png)](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/screenshots/decompose-to-ui-kit.png) Source image (gpt-image input) on the left, agent-emitted `ui_kit` rendered headlessly on the right. Parity score and status are derived deterministically — `parityScore = passCount / totalChecks` — from the 12-check boolean rubric. Numbers are from a real `e2e-opus-final` run, not a mock. [![Iter-0 → iter-1 reconcile loop with honest score drift](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/demos/decompose-iter-reel.gif)](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/demos/decompose-iter-reel.gif) 4-frame reel from the `e2e-nodebench-iter` run: source → iter-0 (parityScore 0.82, 6 gaps) → iter-1 (parityScore 0.78, 5 gaps) → honest verdict. The agent fixed some gaps and introduced new layout drift; the boolean rubric exposes the regression instead of hiding it. [MP4 version](https://raw.githubusercontent.com/OpenCoworkAI/open-codesign/main/website/public/demos/decompose-iter-reel.mp4).\n- **Generation cancellation** — stop mid-stream without losing prior turns\n\n### Preview and workflow\n\n- **Phone / tablet / desktop preview** — true responsive frames, switch with one click\n- **Files panel** — inspect multi-file artifacts (HTML, CSS, JS) before export\n- **Instant design switching** — the last five designs keep their preview iframes alive, so Hub ↔ Workspace and sidebar navigation stay zero-delay\n- **Connection diagnostic panel** — one-click test for any provider, with actionable errors\n- **Per-generation token counter** — see exactly how many tokens each run cost in the sidebar\n- **Settings with four tabs** — Models, Appearance, Storage, and Advanced\n- **Light + dark themes**, **EN + 简体中文 UI** with live toggle\n\n### Export and packaging\n\n- **Five export formats** — HTML (inlined CSS), PDF (local Chrome), PPTX, ZIP, Markdown\n- **GitHub Release pipeline** — unsigned DMG (macOS), EXE (Windows), AppImage (Linux). Code-signing lands in v0.5 along with opt-in auto-update\n\n---\n\n\n\n## Roadmap\n\nCurrent release: v0.2.0. The current release theme is **Agentic Design**.\n\n\n\n### Now — v0.2.0 shipped\n\nv0.2 turns Open CoDesign from a one-shot generator into a local design agent with a real workspace:\n\n- **Design as session** — every design is a pi session with JSONL history and a workspace folder on disk\n- **Permissioned agent loop** — pi built-ins for read, write, edit, bash, grep, find, and ls, gated by Open CoDesign's permission UI\n- **Design tools on demand** — `ask`, `scaffold`, `skill`, `preview`, `gen_image`, `tweaks`, `todos`, and `done`\n- **`DESIGN.md` as shared memory** — brand tokens and design-system decisions become editable files, not model memory\n- **v0.1 migration path** — existing SQLite designs migrate into workspaces and session history\n\n### Previous — v0.1.4\n\n- **AI image generation** — opt-in bitmap assets through OpenAI image models or OpenRouter image models\n- **ChatGPT Plus / Codex subscription login** — one-click OAuth for users who do not want to paste an API key\n- **CLIProxyAPI one-click import** — auto-detect a running local proxy and bring it into Settings\n- **API config hardening** — clearer relay diagnostics for timeouts, SSE truncation, missing `/models`, and incompatible Messages APIs\n\n### Later — v0.2.x and beyond\n\n- Renderer polish for the new `ask`, `preview`, tweaks, and process-management surfaces\n- Cost transparency — pre-generation estimate + weekly budget (per-generation token count already shipped)\n- Version snapshots + side-by-side diff\n- Three-style parallel exploration\n- Codebase → design system (token extraction)\n- Code-signing (Apple ID + Authenticode) + opt-in auto-update — v0.5\n- Figma layer export — post-1.0 Have a different priority in mind? [Open an issue](https://github.com/OpenCoworkAI/open-codesign/issues/new/choose) or 👍 an existing one — we do read them.\n\n\n\n---\n\n\n\n## Star History\n\n[![Star History Chart](https://camo.githubusercontent.com/c9004eda4e74fe950e8f158b122ebb652bc220a034750c1f380f768e88356b74/68747470733a2f2f6170692e737461722d686973746f72792e636f6d2f696d6167653f7265706f733d4f70656e436f776f726b41492f6f70656e2d636f64657369676e26747970653d44617465)](https://star-history.com/#OpenCoworkAI/open-codesign&Date)\n\n\n\n---\n\n\n\n## Built on\n\n- Electron + React 19 + Vite 6 + Tailwind v4\n- `@mariozechner/pi-ai` and `pi-coding-agent` (model/provider and agent-loop primitives)\n- `electron-builder`\n\n## Reporting issues\n\nFound a bug or have a feature request?"},"author":{"name":"OpenCoworkAI","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/9533e0cc6a2ff1ce/avatar-6a9577cd4f7f.svg","bio":"Open-source Claude Design alternative. One-click import your Claude Code / Codex API key. Prompt → prototype / slides / PDF. Multi-model (Claude, GPT, Gemini, Kimi, GLM, Ollama). BYOK, local-first,..."},"metadata":{"timestamp":"2026-08-06T14:59:35.977Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/7HIe3478aa/media/0.png","type":"image","width":1280,"height":640}],"aiComments":[]},{"id":"web-wk23ry","shareId":"9QzB4A1Cb9","platform":"web","url":"https://github.com/ai-shifu/ChatALL","title":"ai-shifu/ChatALL: Concurrently chat with ChatGPT, Bing Chat, Bard, Alpaca, Vicuna, Claude, ChatGLM, MOSS, 讯飞星火, 文心一言 and more, discover the best answers","shareMode":"full","createdAt":1786028350733,"postedAt":"2026-08-06T14:59:03.753Z","publishedDate":"2026-08-06T14:59:03.753Z","archivedAt":"2026-08-06T14:59:06.427Z","archivedDate":"2026-08-06T14:59:06.427Z","viewCount":1,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/9QzB4A1Cb9","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/0un2PTfUS9/media/0.png","contentType":"article","content":{"text":"[![Image](https://github.com/ai-shifu/ChatALL/raw/main/src/assets/logo-cover.png)](https://github.com/ai-shifu/ChatALL/blob/main/src/assets/logo-cover.png) **Chat with ALL AI Bots Concurrently, Discover the Best**\n\n[Deutsch](https://github.com/ai-shifu/ChatALL/blob/main/README_DE-DE.md) | English | [Español](https://github.com/ai-shifu/ChatALL/blob/main/README_ES-ES.md) | [Français](https://github.com/ai-shifu/ChatALL/blob/main/README_FR-FR.md) | [Italian](https://github.com/ai-shifu/ChatALL/blob/main/README_IT-IT.md) | [日本語](https://github.com/ai-shifu/ChatALL/blob/main/README_JA-JP.md) | [한국어](https://github.com/ai-shifu/ChatALL/blob/main/README_KO-KR.md) | [Русский](https://github.com/ai-shifu/ChatALL/blob/main/README_RU-RU.md) | [Tiếng Việt](https://github.com/ai-shifu/ChatALL/blob/main/README_VI-VN.md) | [简体中文](https://github.com/ai-shifu/ChatALL/blob/main/README_ZH-CN.md)\n\nhttps://codespaces.new/ai-shifu/ChatALL\n\n\n\n\n## Screenshots\n\n[![Screenshot](https://github.com/ai-shifu/ChatALL/raw/main/screenshots/screenshot-1.png?raw=true)](https://github.com/ai-shifu/ChatALL/blob/main/screenshots/screenshot-1.png?raw=true)\n\n\n\n## Features\n\nLarge Language Models (LLMs) based AI bots are amazing. However, their behavior can be random and different bots excel at different tasks. If you want the best experience, don't try them one by one. ChatALL (Chinese name: 齐叨) can send prompt to several AI bots concurrently, help you to discover the best results. All you need to do is [download, install](https://github.com/ai-shifu/ChatALL/releases) and ask.\n\n\n\n### Is this you?\n\nTypical users of ChatALL are:\n\n- 🤠 **Gurus of LLMs**, who want to find the best answers or creations from LLMs.\n- 🤓 **Researchers of LLMs**, who want to intuitively compare the strengths and weaknesses of various LLMs in different fields.\n- 😎 **Developers of LLM applications**, who want to quickly debug prompts and find the best-performing foundation models.\n\n### Supported bots\n\n\n\n| AI Bots | Web Access | API | Notes |\n| --- | --- | --- | --- |\n| 360 AI Brain | Yes | No API |\n| Baidu ERNIE | No | Yes |\n| Character.AI | Yes | No API |\n| ChatGLM2 6B & 130B | Yes | No API | No Login required |\n| ChatGPT | Yes | Yes | Web Browsing, Azure OpenAI service included |\n| Claude | Yes | Yes |\n| Code Llama | Yes | No API |\n| Cohere Aya 23 | No | Yes |\n| Cohere Command R Models | No | Yes |\n| Copilot | Yes | No API |\n| Dedao Learning Assistant | Coming soon | No API |\n| Falcon 180B | Yes | No API |\n| Gemini | Yes | Yes |\n| Gemma 2B & 7B | Yes | No API |\n| Gradio | Yes | No API | For Hugging Face space/self-deployed models |\n| Groq Cloud | No | Yes |\n| HuggingChat | Yes | No API |\n| iFLYTEK SPARK | Yes | Coming soon |\n| Kimi | Yes | No API |\n| Llama 2 13B & 70B | Yes | No API |\n| MOSS | Yes | No API |\n| Perplexity | Yes | No API |\n| Phind | Yes | No API |\n| Pi | Yes | No API |\n| Poe | Yes | Coming soon |\n| SkyWork | Yes | Coming soon |\n| Tongyi Qianwen | Yes | Coming soon |\n| Vicuna 13B & 33B | Yes | No API | No Login required |\n| WizardLM 70B | Yes | No API |\n| xAI Grok | No | Yes |\n| YouChat | Yes | No API |\n| You | Yes | No API |\n| Zephyr | Yes | No API |\n\nMore is coming. Upvote your favorite bots in [these issues](https://github.com/ai-shifu/ChatALL/labels/more%20LLMs).\n\n\n\n### Note on Web-connected Bot Reliability\n\nWeb-connected AI bots (those marked with \"Web Access\") are inherently less reliable and frequently face stability issues, as service providers regularly update their web interfaces and security measures. These web-based connections rely on reverse engineering and are difficult to maintain, often breaking unexpectedly. For a dependable experience, we strongly recommend using bots that offer API access whenever possible.\n\n\n\n### Other features\n\n- Quick-prompt mode: send the next prompt without waiting for the previous request to complete\n- Save chat history locally, protect your privacy\n- Highlight the response you like, delete the bad\n- Enable/disable any bots at any time\n- Switch between one, two, or three-column view\n- Auto update to the latest version\n- Dark mode (contributed by @tanchekwei)\n- Short keys. Press Ctrl + / to know all of them (contributed by @tanchekwei)\n- Multiple chats (contributed by @tanchekwei)\n- Proxy setting (contributed by @msaong)\n- Prompt management (contributed by @tanchekwei)\n- Supports multiple languages (Chinese, English, German, French, Russian, Vietnamese, Korean, Japanese, Spanish, Italian)\n- Supports Windows, macOS and Linux Planned features:\n\nYou are welcome to contribute to these features.\n\n- Deploy front-end to GitHub Pages\n\n## Privacy\n\nAll chat history, settings and login data are saved locally on your computer.\n\nChatALL collects anonymous usage data to help us improve the product. Including:\n\n- Which AI bots are prompted and how long the prompt is. Not including the prompt content.\n- How long the response is, and which response is deleted/highlighted. Not including the response content.\n\n## Prerequisites\n\nChatALL is a client, not a proxy. Therefore, you must:\n\n1. Have working accounts and/or API tokens for the bots.\n2. Have reliable network connections to the bots.\n\n## Download / Install\n\nDownload from [https://github.com/ai-shifu/ChatALL/releases](https://github.com/ai-shifu/ChatALL/releases)\n\n\n\n### On Windows\n\nJust download the *-win.exe file and proceed with the setup.\n\n\n\n### On macOS\n\nFor Apple Silicon Mac (M1, M2 CPU), download the *-mac-arm64.dmg file.\n\nFor other Macs, download *-mac-x64.dmg file.\n\nIf you are using [Homebrew](https://brew.sh/), you can also install it with:\n\n\n\n```\nbrew install --cask chatall\n```\n\n\n\n### On Linux\n\nDebian-based Distributions: Download the.deb file, double click it and install the software. Arch-based Distributions: You can clone ChatALL from the AUR [here](https://aur.archlinux.org/packages/chatall-bin). You can install it manually or using an AUR helper like yay or paru. Other Distributions: Download the.AppImage file, make it executable, and enjoy the click-to-run experience. You can also use [AppimageLauncher](https://github.com/TheAssassin/AppImageLauncher).\n\n\n\n## Troubleshooting\n\nIf you encounter any problems while using ChatALL, you can try the following methods to resolve them:\n\n1. **Refresh** - press Ctrl + R or ⌘ + R.\n2. **Restart** - exit ChatALL and run it again.\n3. **Re-login** - click the settings button in the upper right corner, then click the corresponding login/logout link to relogin the website.\n4. **Create a new chat** - click the `New Chat` button and send prompt again. If none of the above methods work, you can try **resetting ChatALL**. Note that this will delete all your settings and message history.\n\nYou can reset ChatALL by deleting the following directories:\n\n- Windows: `C:\\Users\\\\AppData\\Roaming\\chatall\\`\n- Linux: `/home//.config/chatall/`\n- macOS: `/Users//Library/Application Support/chatall/` If the problem persists, please [submit an issue](https://github.com/ai-shifu/ChatALL/issues).\n\n\n\n## For developers\n\n\n\n### Contribute a Bot\n\n[The guide](https://github.com/ai-shifu/ChatALL/wiki/%E5%A6%82%E4%BD%95%E6%B7%BB%E5%8A%A0%E4%B8%80%E4%B8%AA%E6%96%B0%E7%9A%84-AI-%E5%AF%B9%E8%AF%9D%E6%9C%BA%E5%99%A8%E4%BA%BA) may help you.\n\n\n\n### Run\n\n\n\n```\nnpm install\nnpm run electron:serve\n```\n\n\n\n### Build\n\nBuild for your current platform:\n\n\n\n```\nnpm run electron:build\n```\n\nBuild for all platforms:\n\n\n\n```\nnpm run electron:build -- -wml --x64 --arm64\n```\n\n\n\n## Credits\n\n\n\n### Contributors\n\n[![Image](https://camo.githubusercontent.com/e7c642f091fb66a5c431181a4459730f0123bc67073e10643b990a108fa3de50/68747470733a2f2f636f6e747269622e726f636b732f696d6167653f7265706f3d61692d73686966752f43686174414c4c)](https://github.com/ai-shifu/ChatALL/graphs/contributors)\n\n### Others\n\n- GPT-4 contributed much of the code\n- ChatGPT, Copilot and Google provide many solutions (ranked in order)\n- Inspired by [ChatHub](https://github.com/chathub-dev/chathub). Respect!\n\n## Sponsor\n\nIf you like this project, please consider:\n\n[![ko-fi](https://camo.githubusercontent.com/201ef269611db7eb6b5d08e9f756ab8980df3014b64492770bdf13a6ed924641/68747470733a2f2f6b6f2d66692e636f6d2f696d672f676974687562627574746f6e5f736d2e737667)](https://ko-fi.com/F1F8KZJGJ)"},"author":{"name":"ai-shifu","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/6767febb76999024/avatar-6a9577cd4f7f.svg","bio":"Concurrently chat with ChatGPT, Bing Chat, Bard, Alpaca, Vicuna, Claude, ChatGLM, MOSS, 讯飞星火, 文心一言 and more, discover the best answers - ai-shifu/ChatALL"},"metadata":{"timestamp":"2026-08-06T14:59:03.753Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/0un2PTfUS9/media/0.png","type":"image","width":1200,"height":600}],"aiComments":[]},{"id":"web-og28zw","shareId":"uk9J63NuZG","platform":"web","url":"https://github.com/farion1231/cc-switch","title":"farion1231/cc-switch: A cross-platform desktop All-in-One assistant for Claude Code, Codex, OpenCode, OpenClaw, Grok Build & Hermes Agent. Only official website: ccswitch.io","shareMode":"full","createdAt":1786028311117,"postedAt":"2026-08-06T14:58:23.014Z","publishedDate":"2026-08-06T14:58:23.014Z","archivedAt":"2026-08-06T14:58:26.774Z","archivedDate":"2026-08-06T14:58:26.774Z","viewCount":1,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/uk9J63NuZG","thumbnail":"https://opengraph.githubassets.com/80d53778c5d36f4ca90f9630ab717e5935cbbeceb539bbad9bf8757895ddb0dd/farion1231/cc-switch","contentType":"article","content":{"text":"## CC Switch\n\n\n\n### The All-in-One Manager for Claude Code, Claude Desktop, Codex, Gemini CLI, Grok Build, OpenCode, OpenClaw & Hermes Agent\n\n[![Version](https://camo.githubusercontent.com/6a03fb0fe8bf5fa77f1c916fae4300268924adf146f25e81cbed1f06b8e0f173/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f762f72656c656173652f666172696f6e313233312f63632d7377697463683f636f6c6f723d626c7565266c6162656c3d76657273696f6e)](https://github.com/farion1231/cc-switch/releases) [![Platform](https://camo.githubusercontent.com/1e93b866da33d7e3e202cb3127e9e94e902aa550dee535c19ff793c82f7f7706/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f706c6174666f726d2d57696e646f77732532302537432532306d61634f532532302537432532304c696e75782d6c69676874677265792e737667)](https://github.com/farion1231/cc-switch/releases) [![Built with Tauri](https://camo.githubusercontent.com/6949c837a0f280762fb0e33ef90dc5787e2a576490e6b78ffa78fc0e5c8541a7/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f6275696c74253230776974682d5461757269253230322d6f72616e67652e737667)](https://tauri.app/) [![Downloads](https://camo.githubusercontent.com/8f72a8802ac400686c753ad3112dd2a9f39d11c9dbf14b3ad363e6c0009085ce/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f646f776e6c6f6164732f666172696f6e313233312f63632d7377697463682f746f74616c)](https://github.com/farion1231/cc-switch/releases/latest)\n\n[![farion1231%2Fcc-switch | Trendshift](https://camo.githubusercontent.com/cea2a498060a4538801356a1fbcfd83ad1bc9eecfd6bb6b7f63d8796f71079d6/68747470733a2f2f7472656e6473686966742e696f2f6170692f62616467652f7265706f7369746f726965732f3135333732)](https://trendshift.io/repositories/15372) [![Star History Rank](https://camo.githubusercontent.com/b0615792ce2dd3c0a97267acc42d4110bad0be097d0c816f0bd50da97348e0ca/68747470733a2f2f6170692e737461722d686973746f72792e636f6d2f62616467653f7265706f3d666172696f6e313233312f63632d737769746368)](https://www.star-history.com/#farion1231/cc-switch&Date)\n\n\n\n### 🌐 The Only Official Website: ccswitch.io\n\nEnglish | [中文](https://github.com/farion1231/cc-switch/blob/main/README_ZH.md) | [日本語](https://github.com/farion1231/cc-switch/blob/main/README_JA.md) | [Deutsch](https://github.com/farion1231/cc-switch/blob/main/README_DE.md) | [Changelog](https://github.com/farion1231/cc-switch/blob/main/CHANGELOG.md)\n\n\n\n## ❤️Sponsor\n\n\n\n> [Want to appear here?](mailto:farion1231@gmail.com)\n\nClick to collapse [![Kimi K2.7 Code](https://camo.githubusercontent.com/77272eac5cadedcb59f6942e0a4510cce3546086b6d95f56a14eea65752faa90/68747470733a2f2f6763646e2e6d6f6f6e73686f742e636e2f67726f7774682d63646e2f73706f6e736f722f6b696d692d656e2e706e67)](https://platform.kimi.ai/?track_id=track-20d65732f0aa45dcb1df9691a15610af&aff=cc-switch)\n\nKimi K3 is Moonshot AI's most capable model and the world's first open 3T-class model. With 2.8 trillion parameters, native vision, and a 1-million-token context window, K3 delivers frontier performance across long-horizon coding, knowledge work, and reasoning. CC Switch makes it easy to configure and switch to Kimi across agentic tools. **[Click here to start using Kimi](https://platform.kimi.ai/?track_id=track-20d65732f0aa45dcb1df9691a15610af&aff=cc-switch)**\n\n**New user top-up bonus**: register via [this link](https://platform.kimi.ai/?track_id=track-20d65732f0aa45dcb1df9691a15610af&aff=cc-switch) and complete your first top-up to receive 10% of the amount as bonus API credit, up to CNY ¥1,000.\n\nDoing mostly coding work? Try the **[Kimi Code subscription](https://www.kimi.com/code/?aff=cc-switch)**.\n\n\n\n---\n\n\n\n| ![PackyCode](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/packycode.png) | Thanks to PackyCode for sponsoring this project! PackyCode is a reliable and efficient API relay service provider, offering relay services for Claude Code, Codex, Gemini, and more. PackyCode provides special discounts for our software users: register using this link and enter the \"cc-switch\" promo code during first recharge to get 10% off. |\n| --- | --- |\n| ![ZetaAPI](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/zetaapi-banner.png) | Thanks to ZetaAPI for sponsoring this project! ZetaAPI focuses on real model fidelity, no watered-down responses, no quality degradation, and pricing as low as 35% of official rates. The platform does not mix traffic, secretly replace models with lower-quality alternatives, or use fake model routing. It supports Claude Code, Codex, Gemini, ChatGPT, and other mainstream AI models, helping users significantly reduce API costs while maintaining reliable model quality. At the same time, ZetaAPI provides enterprise-grade SLA-backed stability, standard API compatibility, one API key for multiple models, fast integration, and pay-as-you-go billing, making it suitable for AI products, coding agents, internal business tools, customer service systems, content generation, and automation workflows. If any model is verified to be inconsistent with its stated quality, ZetaAPI backs it with a 10x compensation guarantee, giving users a more stable, transparent, and trustworthy experience. Register via this link and use the promo code CC-SWITCH during your first recharge to enjoy an exclusive 10% discount on your first top-up, just for CC Switch users! |\n| ![APINebula](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/apinebula_banner.png) | Thanks to APINEBULA for sponsoring this project! APINEBULA, an enterprise-grade AI aggregation platform under Galaxy Video Bureau, leverages extensive platform resources to provide developers, teams, and enterprises with stable, cost-effective access to large language model APIs. The platform integrates leading, full-powered models like Claude, GPT, and Gemini, allowing you to connect to the world's top AI models through a single API, with prices starting as low as 10% of the original cost. Designed for AI programming, Agent development, and business system integration, APINEBULA supports enterprise-grade high concurrency, formal contracts, corporate bank transfers, and invoicing services. APINEBULA provides special discounts for our software users: register using this link and enter the **\"ccswitch\"** promo code during your first recharge to get **10% off**. |\n| ![AICodeMirror](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/aicodemirror.jpg) | Thanks to AICodeMirror for sponsoring this project! AICodeMirror provides official high-stability relay services for Claude Code / Codex / Gemini CLI, with enterprise-grade concurrency, fast invoicing, and 24/7 dedicated technical support. Claude Code / Codex / Gemini official channels at 38% / 2% / 9% of original price, with extra discounts on top-ups! AICodeMirror offers special benefits for CC Switch users: register via this link to enjoy 20% off your first top-up, and enterprise customers can get up to 25% off! |\n| ![PatewayAI](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/pateway.png) | Thanks to PatewayAI for sponsoring this project! PatewayAI is an API relay service provider built for heavy AI developers, focused on directly relaying official high-quality model APIs. It offers the full Claude lineup and the Codex series, 100% sourced from official channels — no dilution, no fakes, verification welcome. Billing is transparent and every token-level invoice can be audited line by line. It also supports enterprise-grade concurrency and provides a dedicated management platform for enterprise customers — formal contracts and invoicing are available; visit the official website for contact details. Register now via this link to receive $3 in trial credit. Top-ups go as low as 60% of the original price, with a two-way referral bonus of up to $150! |\n| ![Fenno.ai](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/fenno-banner.png) | Thanks to Fenno.ai for sponsoring this project! Fenno.ai is a stable and efficient API relay service provider, currently focused on Codex relay. It is compatible with the OpenAI and Anthropic protocols and can be flexibly used from Codex, Claude Code, OpenCode, and other mainstream coding tools. It reliably supports enterprise-grade workloads of hundreds of billions of tokens per day, with corporate (B2B) settlement and invoicing for both domestic and overseas entities. Fenno.ai offers an exclusive benefit for CC Switch users: subscribe via this link to the incredible ¥9.9 Coding Plan worth $150 in credits, and earn up to 20% in referral rewards — invite more, earn more! |\n| ![RunAPI](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/runapi.jpg) | Thanks to RunAPI for sponsoring this project! RunAPI is a high-performance and reliable AI model API gateway — one API key gives you access to 150+ mainstream models including OpenAI, Claude, Gemini, DeepSeek, and Grok, with prices as low as 10% of the official rate and excellent stability. It works seamlessly with Claude Code, OpenClaw, and other tools. Exclusive benefit for CC Switch users: register via this link and enjoy a 10% discount on your first top-up! |\n| ![Shengsuanyun](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/shengsuanyun.png) | Thanks to Shengsuanyun for sponsoring this project! Shengsuanyun is a super factory serving AI Native Teams — an industrial-grade AI task parallel execution platform. Its model marketplace aggregates Claude, ChatGPT, Gemini, and other domestic and international LLM and multimedia model capabilities with direct supply. Absolutely no reverse engineering or dilution — platform-wide model SLA availability reaches 99.7%, with monitoring dashboards showing green across the board. It also offers enterprise-grade custom gateways for fine-grained team cost and permission management, smart routing, security protection, and BYOK (Bring Your Own Key) hosting. The platform charges on a pay-per-use and tokens plan (coming soon) basis, with invoicing available. Register via this link as a new user to receive ¥10 in credits plus a 10% bonus on your first top-up. |\n| ![AIGoCode](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/aigocode.png) | Thanks to AIGoCode for sponsoring this project! AIGoCode is an all-in-one platform that integrates Claude Code, Codex, and the latest Gemini models, providing you with stable, efficient, and highly cost-effective AI coding services. The platform offers flexible subscription plans, zero risk of account suspension, direct access with no VPN required, and lightning-fast responses. AIGoCode has prepared a special benefit for CC Switch users: if you register via this link, you'll receive an extra 10% bonus credit on your first top-up! |\n| ![AICoding](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/aicoding.jpg) | Thanks to AICoding for sponsoring this project! AICoding — Global AI Model API Relay Service at Unbeatable Prices! Claude Code at 19% of original price, GPT at just 1%! Trusted by hundreds of enterprises for cost-effective AI services. Supports Claude Code, GPT, Gemini and major domestic models, with enterprise-grade high concurrency, fast invoicing, and 24/7 dedicated technical support. CC Switch users who register via this link get 10% off their first top-up! |\n| ![SubRouter](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/subrouter-banner.png) | Thanks to SubRouter for sponsoring this project! SubRouter is a marketplace and smart routing platform for AI service operators. Merchants can launch operating sites, publish packages, manage users, models, and pricing, while users discover services and access reliable AI models through one unified API. Register via this link! |\n| ![APIKEY.FUN](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/apikey_banner.png) | Thanks to APIKEY.FUN for sponsoring this project! APIKEY.FUN is a professional enterprise-grade AI relay platform dedicated to providing stable, efficient, and low-cost AI model API access for enterprises and individual developers. The platform supports popular mainstream models such as Claude, OpenAI, and Gemini, with prices as low as 7% of official rates. Register through this project's exclusive link to enjoy an exclusive offer of up to **permanent 5% off top-ups**. |\n| ![ClaudeAPI](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/claudeapi.png) | This project is sponsored by Claude API. Direct Claude API access — connect Claude Code and Agent apps in 3 minutes. New users can claim a free trial credit.Powered by official Anthropic API keys + AWS Bedrock official channels. No reverse engineering, no model degradation. Full support for Opus / Sonnet / Haiku model lineup, with official capabilities preserved including Tool Use, 1M context window, and more. Built for Claude Code power users, Agent engineers, and enterprise engineering teams. Invoicing and dedicated team support available. Click here to register! |\n| ![code0.ai](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/code0.png) | Thanks to code0.ai for sponsoring this project! code0.ai is an AI coding service platform built for developers, supporting Claude Code, Codex, Gemini, and other mainstream AI coding capabilities. It helps individual developers and teams use AI Agents more stably and efficiently for coding, debugging, refactoring, and automation workflows. ccswitch users can contact customer support via the code0.ai website to claim test credits and experience a reliable AI coding service. |\n| ![TeamoRouter](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/TeamoRouter-banner.png) | Thanks to TeamoRouter for sponsoring this project! TeamoRouter is an enterprise-grade Agentic LLM gateway built for developers, AI teams, and businesses. Without requiring any subscriptions, it lets you access Claude Code, Codex, Gemini CLI, OpenAI Codex, and other popular AI agents through a single unified API, while offering API pricing at discounts of up to 90%. Unlike typical API relay services, TeamoRouter aggregates hundreds of official model providers and trusted infrastructure partners, including OpenAI, Anthropic, Vertex, Azure, and AWS bedrock. Every provider is verified for 100% Agent protocol compatibility, cache performance, and request traceability, ensuring stable quality instead of reverse-engineered or diluted endpoints. The platform delivers near-official TTFT, 99.6% SLA, enterprise-scale throughput up to 5,000 QPM, and industry-leading cache hit rates that dramatically reduce token costs for long-running agent workflows. TeamoRouter also offers enterprise features including centralized billing, team management, BYOK, smart routing, usage analytics, dynamic provider optimization, and dedicated support. For an even simpler experience, Teamo Desktop lets you use Claude Code, Codex, Gemini CLI, and other popular AI agents with one-click setup—no API key management or manual gateway configuration required. Register via this link as a new user to receive 10% off your first top-up. |\n| ![new-api](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/newapi-banner.png) | Thanks to the open-source AI infrastructure project new-api for its strong support of this project! new-api is an open-source AI infrastructure project from QuantumNous and one of the leading unified LLM access-and-distribution projects by activity and adoption, focused on helping developers, teams, and enterprises build manageable, scalable AI service platforms at lower cost. As a fellow project rooted in the open-source ecosystem, new-api hopes to sponsor and support the continued growth of more outstanding open-source projects. 🌟 Star new-api to show your support: https://github.com/QuantumNous/new-api. Website: https://www.newapi.ai/. |\n| ![ClaudeCN](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/claudecn.jpg) | Thanks to ClaudeCN for sponsoring this project! ClaudeCN is an enterprise-grade AI gateway platform operated by a registered company. It delivers high-availability commercial API access to popular models including Claude, GPT, and DeepSeek, and is built around formal enterprise procurement workflows — corporate bank transfers, signed contracts, and full compliance. Register via this link! |\n| ![BytePlus](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/byteplus.png) | Thanks to Dola seed for sponsoring this project! Dola Seed 2.0 is a full‑modal general large model independently developed by ByteDance for the global market. Built on a unified multimodal architecture, it supports joint understanding and generation of text, images, audio, and video. It natively enables agent collaboration, with strong reasoning, long‑task execution, tool integration, and coding capabilities. It is widely applicable to smart cockpits, personal assistants, education, customer support, marketing, retail, and other scenarios. It excels in multimodal perception, end‑to‑end complex task delivery, stable interaction, and data security, and is readily accessible and deployable via the ModelArk platform.Register via this link to get 500,000 tokens of free inference quota per model. >>中国大陆地区的开发者请点击这里 |\n| ![SiliconFlow](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/silicon_en.jpg) | Thanks to SiliconFlow for sponsoring this project! SiliconFlow is a high-performance AI infrastructure and model API platform, providing fast and reliable access to language, speech, image, and video models in one place. With pay-as-you-go billing, broad multimodal model support, high-speed inference, and enterprise-grade stability, SiliconFlow helps developers and teams build and scale AI applications more efficiently. Register via this link and complete real-name verification to receive ¥16 in bonus credit, usable across models on the platform. SiliconFlow is also now compatible with OpenClaw, allowing users to connect a SiliconFlow API key and call major AI models for free. |\n| ![A6API](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/a6-banner-en.jpg) | Thanks to A6API for sponsoring this project! A6API is a one-stop AI model API aggregation platform covering Claude, GPT, Gemini, Codex, and other mainstream models. Multiple vendors can list their supply on the platform, so the same model can be quoted competitively by several upstream providers. Smart routing automatically picks the more stable, lower-priced route available and fails over automatically, helping you reduce failed requests, cut costs, and improve stability. Whether you are an individual developer, an AI product team, or a studio, you can integrate quickly through a unified interface — compatible with all formats, with low migration cost. New users who register via this link receive free trial credits: try it first, then use it at a low price. |\n| ![Atlas Cloud](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/atlascloud_banner.png) | Atlas Cloud is a full-modal AI inference platform that gives developers a single AI API to access video generation, image generation, and LLM APIs. Instead of managing multiple vendor integrations, you connect once and get unified access to 300+ curated models across all modalities. Check out Atlas Cloud's new coding plan promotion for more budget-friendly API access! |\n| ![Compshare](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/ucloud.png) | Thanks to Compshare for sponsoring this project! Compshare is UCloud's AI cloud platform, providing stable and comprehensive domestic and international model APIs with just one key. Featuring cost-effective monthly and per-use domestic-model Coding Plan packages, alongside stable officially-relayed overseas models. Supports Claude Code, Codex, and API access. Enterprise-grade high concurrency, 24/7 technical support, and self-service invoicing. Users who register via this link will receive a free 5 CNY platform trial credit! |\n| Thanks to CCSub for sponsoring this project! CCSub is a stable, affordable AI API relay platform — your drop-in replacement for a Claude.ai subscription. One API key gives you access to Claude Opus 4.8, Sonnet, Haiku, GPT-5, Gemini, and DeepSeek at roughly 30% of direct API cost, with no VPN required from anywhere in the world. Compatible with Claude Code, Codex, Cursor, Cline, Continue, Windsurf, and all major AI coding tools. Register via this link and get $5 free credit on sign-up. |\n| ![SSSAiCode](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/sssaicode.png) | Thanks to SSSAiCode for sponsoring this project! SSSAiCode is a stable and reliable API relay service, dedicated to providing stable, reliable, and affordable Claude and Codex model services, with same-day fast invoicing. SSSAiCode offers a special deal for CC Switch users: register via this link to enjoy $10 extra credit on every top-up! |\n| Thanks to Micu API for sponsoring this project! Micu API is a global LLM relay service provider dedicated to delivering the best cost-performance ratio with high stability. Backed by a registered enterprise for core assurance, eliminating any risk of service discontinuation, with fast official invoicing support! We champion \"zero cost to try\": top up from as low as ¥1 with no minimum, and get fee-free refunds anytime! Micu API offers an exclusive deal for CC Switch users: register via this link and enter promo code \"ccswitch\" when topping up to enjoy a **10% discount**! |\n| ![RightCode](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/rightcode.jpg) | Thank you to Right Code for sponsoring this project! Right Code reliably provides routing services for models such as Claude Code, Codex, and Gemini, with both pay-as-you-go and monthly subscription billing options available. Invoices are available upon top-up, and enterprise and team users can receive dedicated one-on-one support. Right Code also offers an exclusive discount for CC Switch users: register via this link, and with every top-up you will receive pay-as-you-go credit equivalent to 5% of the amount paid. |\n| ![ETok](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/etok.png) | Thanks to ETok.ai for sponsoring this project! ETok.ai is dedicated to building a one-stop AI programming tool service platform. We offer professional Claude Code packages and technical community services, with support for Google Gemini and OpenAI Codex. Through carefully designed plans and a professional tech community, we provide developers with reliable service guarantees and continuous technical support, making AI-assisted programming a true productivity tool. Click here to register! |\n| ![Cubence](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/cubence.png) | Thanks to Cubence for sponsoring this project! Cubence is a reliable and efficient API relay service provider, offering relay services for Claude Code, Codex, Gemini, and more with flexible billing options including pay-as-you-go and monthly plans. Cubence provides special discounts for CC Switch users: register using this link and enter the \"CCSWITCH\" promo code during recharge to get 10% off every top-up! |\n| ![Crazyrouter](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/crazyrouter.png) | Thanks to Crazyrouter for sponsoring this project! Crazyrouter is a high-performance AI API aggregation platform — one API key for 300+ models including Claude Code, Codex, Gemini CLI, and more. All models at 55% of official pricing with auto-failover, smart routing, and unlimited concurrency. Crazyrouter offers an exclusive deal for CC Switch users: register via this link and contact customer support to claim **$2 free credit**, plus enter promo code `CCSWITCH` on your first top-up for an extra **30% bonus credit**! |\n| ![DMXAPI](https://github.com/farion1231/cc-switch/raw/main/assets/partners/logos/dmx-en.jpg) | Thanks to DMXAPI for sponsoring this project! DMXAPI provides global large model API services to 200+ enterprise users. One API key for all global models. Features include: instant invoicing, unlimited concurrency, starting from $0.15, 24/7 technical support. GPT/Claude/Gemini all at 32% off, domestic models 20-50% off, Claude Code exclusive models at 66% off! Register here |\n\n\n\n## Why CC Switch?\n\nModern AI-powered coding relies on tools like Claude Code, Claude Desktop, Codex, Gemini CLI, Grok Build, OpenCode, OpenClaw, and Hermes — but each has its own configuration format. Switching API providers means manually editing JSON, TOML, or `.env` files, and there is no unified way to manage MCP and Skills across multiple tools.\n\n**CC Switch** gives you a single desktop app to manage all supported AI tools. Instead of editing config files by hand, you get a visual interface to import providers with one click, switch between them instantly, with 50+ built-in provider presets, unified MCP and Skills management, and system tray quick switching — all backed by a reliable SQLite database with atomic writes that protect your configs from corruption.\n\n- **One App, Eight Tools** — Manage Claude Code, Claude Desktop, Codex, Gemini CLI, Grok Build, OpenCode, OpenClaw, and Hermes from a single interface\n- **No More Manual Editing** — 50+ provider presets including AWS Bedrock, NVIDIA NIM, and community relays; just pick and switch\n- **Unified MCP & Skills Management** — One panel to manage MCP servers and Skills across Claude, Codex, Gemini, Grok Build, OpenCode, and Hermes with bidirectional sync\n- **System Tray Quick Switch** — Switch providers instantly from the tray menu, no need to open the full app\n- **Cloud Sync** — Sync provider data across devices via Dropbox, OneDrive, iCloud, or WebDAV servers\n- **Cross-Platform** — Native desktop app for Windows, macOS, and Linux, built with Tauri 2\n- **Built-in Utilities** — Includes various utilities for first-launch login confirmation, signature bypass, plugin extension sync, and more\n\n## Screenshots\n\n\n\n| Main Interface | Add Provider |\n| --- | --- |\n| ![Main Interface](https://github.com/farion1231/cc-switch/raw/main/assets/screenshots/main-en.png) | ![Add Provider](https://github.com/farion1231/cc-switch/raw/main/assets/screenshots/add-en.png) |\n\n\n\n## Features\n\n[Full Changelog](https://github.com/farion1231/cc-switch/blob/main/CHANGELOG.md) | [Release Notes](https://github.com/farion1231/cc-switch/blob/main/docs/release-notes/v3.16.1-en.md)\n\n\n\n### Provider Management\n\n- **8 supported tools, 50+ presets** — Claude Code, Claude Desktop, Codex, Gemini CLI, Grok Build, OpenCode, OpenClaw, Hermes; copy your key and import with one click\n- **Universal providers** — One config syncs to Claude Code, Codex, and Gemini CLI\n- One-click switching, system tray quick access, drag-and-drop sorting, import/export\n\n### Proxy & Failover\n\n- **Local proxy with hot-switching** — Format conversion, auto-failover, circuit breaker, provider health monitoring, and request rectifier\n- **App-level takeover** — Independently proxy Claude, Codex, Gemini, or Grok Build, down to individual providers\n\n### MCP, Prompts & Skills\n\n- **Unified MCP panel** — Manage MCP servers across Claude, Codex, Gemini, Grok Build, OpenCode, and Hermes with bidirectional sync and Deep Link import\n- **Prompts** — Markdown editor with cross-app sync (CLAUDE.md / AGENTS.md / GEMINI.md) and backfill protection\n- **Skills** — One-click install from GitHub repos or ZIP files, custom repository management, with symlink and file copy support\n\n### Usage & Cost Tracking\n\n- **Usage dashboard** — Track spending, requests, and tokens with trend charts, detailed request logs, and custom per-model pricing\n\n### Session Manager & Workspace\n\n- Browse, search, and restore conversation history across supported session sources\n- **Workspace editor** (OpenClaw) — Edit agent files (AGENTS.md, SOUL.md, etc.) with Markdown preview\n\n### System & Platform\n\n- **Cloud sync** — Custom config directory (Dropbox, OneDrive, iCloud, NAS) and WebDAV server sync\n- **Deep Link** (`ccswitch://`) — Import providers, MCP servers, prompts, and skills via URL\n- Dark / Light / System theme, auto-launch, auto-updater, atomic writes, auto-backups, i18n (zh/zh-TW/en/ja)\n\n## FAQ\n\n**Which AI tools does CC Switch support?** CC Switch supports eight tools: **Claude Code**, **Claude Desktop**, **Codex**, **Gemini CLI**, **Grok Build**, **OpenCode**, **OpenClaw**, and **Hermes**. Each tool has dedicated provider presets and configuration management.\n\n**Do I need to restart the terminal after switching providers?** For most tools, yes — restart your terminal or the CLI tool for changes to take effect. The exception is **Claude Code**, which currently supports hot-switching of provider data without a restart.\n\n**My plugin configuration disappeared after switching providers — what happened?** CC Switch provides a \"Shared Config Snippet\" feature to pass common data (beyond API keys and endpoints) between providers. Go to \"Edit Provider\" → \"Shared Config Panel\" → click \"Extract from Current Provider\" to save all common data. When creating a new provider, check \"Write Shared Config\" (enabled by default) to include plugin data in the new provider. All your configuration items are preserved in the default provider imported when you first launched the app.\n\n**macOS installation** CC Switch for macOS is code-signed and notarized by Apple. You can download and install it directly — no extra steps needed. We recommend using the `.dmg` installer.\n\n**Why can't I delete the currently active provider?** CC Switch follows a \"minimal intrusion\" design principle — even if you uninstall the app, your CLI tools will continue to work normally. The system always keeps one active configuration, because deleting all configurations would make the corresponding CLI tool unusable. If you rarely use a specific CLI tool, you can hide it in Settings. To switch back to official login, see the next question.\n\n**How do I switch back to official login?** Add an official provider from the preset list. After switching to it, run the Log out / Log in flow, and then you can freely switch between the official provider and third-party providers. Codex supports switching between different official providers, making it easy to switch between multiple Plus or Team accounts.\n\n**Where is my data stored?** - **Database**: `~/.cc-switch/cc-switch.db` (SQLite — providers, MCP, prompts, skills)\n- **Local settings**: `~/.cc-switch/settings.json` (device-level UI preferences)\n- **Backups**: `~/.cc-switch/backups/` (auto-rotated, keeps 10 most recent)\n- **Skills**: `~/.cc-switch/skills/` (symlinked to corresponding apps by default)\n- **Skill Backups**: `~/.cc-switch/skill-backups/` (created automatically before uninstall, keeps 20 most recent) **Linux (Wayland + NVIDIA): clicks don't register and the window black-screens on resize** The AppImage forces `GDK_BACKEND=x11` (XWayland) to avoid a historical native-Wayland crash. On newer Wayland + NVIDIA setups this can leave the web content area unclickable (the title-bar buttons still work) and black-screen on resize. Launch with the opt-in escape hatch to switch back to native Wayland:\n\n\n\n```\nCC_SWITCH_GDK_BACKEND=wayland ./CC-Switch-*.AppImage\n```\n\nIf you launch from a desktop icon, add it to the `.desktop` `Exec=` line (e.g. `env CC_SWITCH_GDK_BACKEND=wayland /path/to/AppImage`) or set it in your session environment. The variable is generic: on tiling Wayland compositors (sway/Hyprland) where clicks don't register, try `CC_SWITCH_GDK_BACKEND=x11` instead. Leaving it unset keeps the default behavior.\n\n\n\n## Documentation\n\nFor detailed guides on every feature, check out the **[User Manual](https://github.com/farion1231/cc-switch/blob/main/docs/user-manual/en/README.md)** — covering provider management, MCP/Prompts/Skills, proxy & failover, and more.\n\n\n\n## Quick Start\n\n\n\n### Basic Usage\n\n1. **Add Provider**: Click \"Add Provider\" → Choose a preset or create custom configuration\n2. **Switch Provider**: - Main UI: Select provider → Click \"Enable\" - System Tray: Click provider name directly (instant effect)\n3. **Takes Effect**: Restart your terminal or the corresponding CLI tool to apply changes (Claude Code does not require a restart)\n4. **Back to Official**: Add an \"Official Login\" preset, restart the CLI tool, then follow its login/OAuth flow\n\n### MCP, Prompts, Skills & Sessions\n\n- **MCP**: Click the \"MCP\" button → Add servers via templates or custom config → Toggle per-app sync\n- **Prompts**: Click \"Prompts\" → Create presets with Markdown editor → Activate to sync to live files\n- **Skills**: Click \"Skills\" → Browse GitHub repos → One-click install to supported apps\n- **Sessions**: Click \"Sessions\" → Browse, search, and restore conversation history across supported session sources\n\n> **Note**: On first launch, you can manually import existing CLI tool configs as the default provider.\n\n\n\n## Download & Installation\n\n\n\n### System Requirements\n\n- **Windows**: Windows 10 and above\n- **macOS**: macOS 12 (Monterey) and above\n- **Linux**: Ubuntu 22.04+ / Debian 11+ / Fedora 34+ and other mainstream distributions\n\n### Windows Users\n\nDownload the latest `CC-Switch-v{version}-Windows.msi` installer or `CC-Switch-v{version}-Windows-Portable.zip` portable version from the [Releases](https://github.com/farion1231/cc-switch/releases) page.\n\n\n\n### macOS Users\n\n**Method 1: Install via Homebrew (Recommended)**\n\n\n\n```\nbrew install --cask cc-switch\n```\n\nUpdate:\n\n\n\n```\nbrew upgrade --cask cc-switch\n```\n\n**Method 2: Manual Download**\n\nDownload `CC-Switch-v{version}-macOS.dmg` (recommended) or `.zip` from the [Releases](https://github.com/farion1231/cc-switch/releases) page.\n\n\n\n> **Note**: CC Switch for macOS is code-signed and notarized by Apple. You can install and open it directly.\n\n\n\n### Arch Linux Users\n\n**Install via paru (Recommended)**\n\n\n\n```\nparu -S cc-switch-bin\n```\n\n\n\n### Linux Users\n\nDownload the latest Linux build from the [Releases](https://github.com/farion1231/cc-switch/releases) page:\n\n- `CC-Switch-v{version}-Linux.deb` (Debian/Ubuntu)\n- `CC-Switch-v{version}-Linux.rpm` (Fedora/RHEL/openSUSE)\n- `CC-Switch-v{version}-Linux.AppImage` (Universal)\n\n> **Flatpak**: Not included in official releases. You can build it yourself from the `.deb` — see [`flatpak/README.md`](https://github.com/farion1231/cc-switch/blob/main/flatpak/README.md) for instructions.\n\n**Architecture Overview**\n\n### Design Principles\n\n\n\n```\n┌─────────────────────────────────────────────────────────────┐\n│ Frontend (React + TS) │\n│ ┌─────────────┐ ┌──────────────┐ ┌──────────────────┐ │\n│ │ Components │ │ Hooks │ │ TanStack Query │ │\n│ │ (UI) │──│ (Bus. Logic) │──│ (Cache/Sync) │ │\n│ └─────────────┘ └──────────────┘ └──────────────────┘ │\n└────────────────────────┬────────────────────────────────────┘\n│ Tauri IPC\n┌────────────────────────▼────────────────────────────────────┐\n│ Backend (Tauri + Rust) │\n│ ┌─────────────┐ ┌──────────────┐ ┌──────────────────┐ │\n│ │ Commands │ │ Services │ │ Models/Config │ │\n│ │ (API Layer) │──│ (Bus. Layer) │──│ (Data) │ │\n│ └─────────────┘ └──────────────┘ └──────────────────┘ │\n└─────────────────────────────────────────────────────────────┘\n```\n\n**Core Design Patterns**\n\n- **SSOT** (Single Source of Truth): All data stored in `~/.cc-switch/cc-switch.db` (SQLite)\n- **Dual-layer Storage**: SQLite for syncable data, JSON for device-level settings\n- **Dual-way Sync**: Write to live files on switch, backfill from live when editing active provider\n- **Atomic Writes**: Temp file + rename pattern prevents config corruption\n- **Concurrency Safe**: Mutex-protected database connection avoids race conditions\n- **Layered Architecture**: Clear separation (Commands → Services → DAO → Database) **Key Components**\n\n- **ProviderService**: Provider CRUD, switching, backfill, sorting\n- **McpService**: MCP server management, import/export, live file sync\n- **ProxyService**: Local proxy mode with hot-switching and format conversion\n- **SessionManager**: Conversation history browsing across supported session sources\n- **ConfigService**: Config import/export, backup rotation\n- **SpeedtestService**: API endpoint latency measurement **Development Guide**\n\n### Environment Requirements\n\n- Node.js 18+\n- pnpm 8+\n- Rust 1.85+\n- Tauri CLI 2.8+\n\n### Development Commands\n\n\n\n```\n# Install dependencies\npnpm install\n\n# Dev mode (hot reload)\npnpm dev\n\n# Type check\npnpm typecheck\n\n# Format code\npnpm format\n\n# Check code format\npnpm format:check\n\n# Run frontend unit tests\npnpm test:unit\n\n# Run tests in watch mode (recommended for development)\npnpm test:unit:watch\n\n# Build application\npnpm build\n\n# Build debug version\npnpm tauri build --debug\n```\n\n\n\n### Rust Backend Development\n\n\n\n```\ncd src-tauri\n\n# Format Rust code\ncargo fmt\n\n# Run clippy checks\ncargo clippy\n\n# Run backend tests\ncargo test\n\n# Run specific tests\ncargo test test_name\n\n# Run tests with test-hooks feature\ncargo test --features test-hooks\n```\n\n\n\n### Testing Guide\n\n**Frontend Testing**:\n\n- Uses **vitest** as test framework\n- Uses **MSW (Mock Service Worker)** to mock Tauri API calls\n- Uses **@testing-library/react** for component testing **Running Tests**:\n\n\n\n```\n# Run all tests\npnpm test:unit\n\n# Watch mode (auto re-run)\npnpm test:unit:watch\n\n# With coverage report\npnpm test:unit --coverage\n```\n\n\n\n### Tech Stack\n\n**Frontend**: React 18 · TypeScript · Vite · TailwindCSS 3.4 · TanStack Query v5 · react-i18next · react-hook-form · zod · shadcn/ui · @dnd-kit\n\n**Backend**: Tauri 2.8 · Rust · serde · tokio · thiserror · tauri-plugin-updater/process/dialog/store/log\n\n**Testing**: vitest · MSW · @testing-library/react\n\n**Project Structure**\n\n```\n├── src/ # Frontend (React + TypeScript)\n│ ├── components/\n│ │ ├── providers/ # Provider management\n│ │ ├── mcp/ # MCP panel\n│ │ ├── prompts/ # Prompts management\n│ │ ├── skills/ # Skills management\n│ │ ├── sessions/ # Session Manager\n│ │ ├── proxy/ # Proxy mode panel\n│ │ ├── openclaw/ # OpenClaw config panels\n│ │ ├── settings/ # Settings (Terminal/Backup/About)\n│ │ ├── deeplink/ # Deep Link import\n│ │ ├── env/ # Environment variable management\n│ │ ├── universal/ # Cross-app configuration\n│ │ ├── usage/ # Usage statistics\n│ │ └── ui/ # shadcn/ui component library\n│ ├── hooks/ # Custom hooks (business logic)\n│ ├── lib/\n│ │ ├── api/ # Tauri API wrapper (type-safe)\n│ │ └── query/ # TanStack Query config\n│ ├── locales/ # Translations (zh/zh-TW/en/ja)\n│ ├── config/ # Presets (providers/mcp)\n│ └── types/ # TypeScript definitions\n├── src-tauri/ # Backend (Rust)\n│ └── src/\n│ ├── commands/ # Tauri command layer (by domain)\n│ ├── services/ # Business logic layer\n│ ├── database/ # SQLite DAO layer\n│ ├── proxy/ # Proxy module\n│ ├── session_manager/ # Session management\n│ ├── deeplink/ # Deep Link handling\n│ └── mcp/ # MCP sync module\n├── tests/ # Frontend tests\n└── assets/ # Screenshots & partner resources\n```\n\n\n\n## Contributing\n\nIssues and suggestions are welcome!\n\nBefore submitting PRs, please ensure:\n\n- Pass type check: `pnpm typecheck`\n- Pass format check: `pnpm format:check`\n- Pass unit tests: `pnpm test:unit` For new features, please open an issue for discussion before submitting a PR. PRs for features that are not a good fit for the project may be closed.\n\n\n\n## Star History\n\n[![Star History Chart](https://camo.githubusercontent.com/488cc4b3723f1b202c5860d8d3a094177a67ceb1ee1cab0f96344d60d61f76c6/68747470733a2f2f6170692e737461722d686973746f72792e636f6d2f7376673f7265706f733d666172696f6e313233312f63632d73776974636826747970653d44617465)](https://www.star-history.com/#farion1231/cc-switch&Date)\n\n\n\n## License\n\nMIT © Jason Young"},"author":{"name":"farion1231","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/89d676c4f846ddb0/avatar-6a9577cd4f7f.svg","bio":"A cross-platform desktop All-in-One assistant for Claude Code, Codex, OpenCode, OpenClaw, Grok Build & Hermes Agent. Only official website: ccswitch.io - farion1231/cc-switch"},"metadata":{"timestamp":"2026-08-06T14:58:23.014Z"},"media":[{"url":"https://opengraph.githubassets.com/80d53778c5d36f4ca90f9630ab717e5935cbbeceb539bbad9bf8757895ddb0dd/farion1231/cc-switch","type":"image"}],"aiComments":[]},{"id":"web-bpvnbt","shareId":"brnX7PFczN","platform":"web","url":"https://github.com/nexu-io/open-design","title":"nexu-io/open-design: 🎨 The open-source Claude Design alternative. 🖥️ Local-first desktop app. 🖼️ Your coding agent becomes the design engine: prototypes, landing pages, dashboards, slides, images & video — real files, HTML/PDF/PPTX/MP4 export. 🤖 Claude Code / Codex / Cursor / Gemini / OpenCode / Qwen & 20+ CLIs via BYOK.","shareMode":"full","createdAt":1786028310704,"postedAt":"2026-08-06T14:58:14.516Z","publishedDate":"2026-08-06T14:58:14.516Z","archivedAt":"2026-08-06T14:58:20.362Z","archivedDate":"2026-08-06T14:58:20.362Z","viewCount":4,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/brnX7PFczN","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/DeFTjf0yb9/media/0.png","contentType":"article","content":{"text":"## Open Design: The open-source Claude Design alternative\n\n\n\n> ⚡ **Open Design Cloud — the official model service.** One recharge to use GPT, Claude, Gemini, and DeepSeek inside Open Design: 20+ flagship models, zero config, billed by real token usage. [Try Open Design Cloud](https://open-design.ai/cloud/?utm_source=github&utm_medium=referral&utm_content=readme_try_cloud) 🏅 **The Open Design Fellow program is now open.** If you also believe design should be open — become an Open Design Fellow, shape the product alongside the core team, and help more people take part in defining the future of design. Details → [`MAINTAINERS.md`](https://github.com/nexu-io/open-design/blob/main/MAINTAINERS.md) and [Discord](https://discord.gg/mHAjSMV6gz).\n\n[![Open Design hero banner — the headline \"The open-source Claude Design alternative\" over a classical scene of columns and robed figures on a digital-code backdrop, with stat cards for design systems, plugins, coding agents, and media providers](https://camo.githubusercontent.com/03e623b9a0a74798e7adb26dc51a3b9110e55fd881d0e7d51c2dc38ae3db287a/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f6865726f2e706e67)](https://camo.githubusercontent.com/03e623b9a0a74798e7adb26dc51a3b9110e55fd881d0e7d51c2dc38ae3db287a/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f6865726f2e706e67)\n\n[Website](https://open-design.ai/?utm_source=github&utm_medium=referral&utm_content=readme_website) · [Download](https://open-design.ai/?utm_source=github&utm_medium=referral&utm_content=readme_download) · [Open Design Cloud](https://open-design.ai/cloud/?utm_source=github&utm_medium=referral&utm_content=readme_cloud) · [Discord](https://discord.gg/mHAjSMV6gz) · [Follow @OpenDesignHQ](https://x.com/OpenDesignHQ)\n\n[![release](https://camo.githubusercontent.com/2f8d34ccb8aa74962ca4b5d253f866f95253eb12e1fa35eb5d30056c17c0ba02/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f762f72656c656173652f6e6578752d696f2f6f70656e2d64657369676e3f7374796c653d666c617426636f6c6f723d626c756576696f6c6574266c6162656c3d72656c6561736526696e636c7564655f70726572656c656173657326646973706c61795f6e616d653d746167)](https://github.com/nexu-io/open-design/releases) [![license](https://camo.githubusercontent.com/006dcfcb1a27dc3394e9b13ffec1730a47ab67029ba386414c44bf19b74b11a7/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f6c6963656e73652d417061636865253230322e302d626c75652e7376673f7374796c653d666c6174)](https://github.com/nexu-io/open-design/blob/main/LICENSE) [![discord](https://camo.githubusercontent.com/bc59127014638fd331e797d8a7fc64bf529032db634e5cce31a0c1b045574736/68747470733a2f2f696d672e736869656c64732e696f2f646973636f72642f313437393030323438353034303438303236363f7374796c653d666c6174266c6f676f3d646973636f7264266c6f676f436f6c6f723d7768697465266c6162656c3d646973636f726426636f6c6f723d3538363546322663616368655365636f6e64733d33363030)](https://discord.gg/mHAjSMV6gz) [![quickstart](https://camo.githubusercontent.com/293472573e20a1c9db20886e0704f9cc4c4f3a994a2932e14b84f3f02ce0259e/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f717569636b73746172742d33253230636f6d6d616e64732d677265656e3f7374796c653d666c6174)](https://github.com/nexu-io/open-design/blob/main/QUICKSTART.md)\n\n**English** · [Español](https://github.com/nexu-io/open-design/blob/main/docs/i18n/README.es.md) · [Português](https://github.com/nexu-io/open-design/blob/main/docs/i18n/README.pt-BR.md) · [Deutsch](https://github.com/nexu-io/open-design/blob/main/docs/i18n/README.de.md) · [Français](https://github.com/nexu-io/open-design/blob/main/docs/i18n/README.fr.md) · [简体中文](https://github.com/nexu-io/open-design/blob/main/docs/i18n/README.zh-CN.md) · [繁體中文](https://github.com/nexu-io/open-design/blob/main/docs/i18n/README.zh-TW.md) · [한국어](https://github.com/nexu-io/open-design/blob/main/docs/i18n/README.ko.md) · [日本語](https://github.com/nexu-io/open-design/blob/main/docs/i18n/README.ja-JP.md) · [العربية](https://github.com/nexu-io/open-design/blob/main/docs/i18n/README.ar.md) · [Русский](https://github.com/nexu-io/open-design/blob/main/docs/i18n/README.ru.md) · [Українська](https://github.com/nexu-io/open-design/blob/main/docs/i18n/README.uk.md) · [Türkçe](https://github.com/nexu-io/open-design/blob/main/docs/i18n/README.tr.md) · [ภาษาไทย](https://github.com/nexu-io/open-design/blob/main/docs/i18n/README.th.md)\n\n\n\n---\n\n\n\n## What is Open Design\n\n🎨 **The open-source Claude Design alternative.** 🖥️ **Local-first native desktop app for macOS and Windows.** ⚡ **Composable skills, brand-grade `DESIGN.md` design systems, and ready-to-use plugins.** 🖼️ Generates **web · desktop · mobile prototypes**, **live dashboards / artifacts**, **decks**, **images**, **video**, plus **HyperFrames** motion graphics. 🔒 Sandboxed iframe preview · HTML / PDF / PPTX / MP4 export. 🤖 **Runs on Claude Code · OpenClaw · Codex · Cursor · OpenCode · Qwen · Copilot · Amp · Hermes · Kimi · Antigravity and 25 distinct local CLI executables**, or any OpenAI-compatible endpoint via BYOK.\n\nOpen Design is what you get when the **agent-native** loop Anthropic shipped with Claude Design — discover the brief, lock the direction, stream the artifact, critique, deliver — stops being closed and becomes a **filesystem of functional skills, rendering design templates, design systems, and plugins** that the coding agents already on your laptop can read, write, and remix. Your CLI becomes the design engine, your laptop becomes the studio, and your team's `DESIGN.md` becomes the brand contract.\n\nIt's also the **Figma alternative for the agent era** — instead of pushing pixels on a canvas, it delivers single-page artifacts in real CSS, real fonts, real components, exported straight to HTML / PDF / PPTX / MP4 — already shaped by your design system, already runnable inside the agent you use every day.\n\n\n\n---\n\n\n\n## Product tour\n\nA quick look at what Open Design is and what it does. Start from **Home**, orchestrate repeat workflows with **Automation**, distill a brand contract in **Design System**, and extend with **Plugins** and **integrations**; inside any project's **Studio**, the same design system streams out prototypes, live artifacts, HyperFrames, decks, and images.\n\n\n\n### Core pages\n\n[![Home page](https://camo.githubusercontent.com/df9488e882b012f422ce712abe5c418ef191b99f508e4aef64f2ab0b260e0fb0/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f70726f647563742f686f6d652e706e67)](https://camo.githubusercontent.com/df9488e882b012f422ce712abe5c418ef191b99f508e4aef64f2ab0b260e0fb0/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f70726f647563742f686f6d652e706e67)\n**Home** — the overview entry point. Pick a skill and a design system, type the brief, and kick off everything from one place.\n\n\n\n| ![Automation page](https://camo.githubusercontent.com/40cfc870f0bc994e882ebbbb49e319b185af3f2a5887e5e1c9e82a9fca8d5082/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f70726f647563742f6175746f6d6174696f6e2e706e67) **Automation** — orchestrate repetitive design workflows into reusable, schedulable automations. | ![Design System page](https://camo.githubusercontent.com/067387f94221c8148b75072f8cc94b9f92656c0c895fc5fba6f888400a650c24/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f70726f647563742f64657369676e2d73797374656d2e706e67) **Design System** — distill your team's `DESIGN.md` into a brand contract that shapes every output. |\n| --- | --- |\n| ![Plugin page](https://camo.githubusercontent.com/9aa4a1a137470e05ce509977317d63ec0b87ca4e812f17b189730ac2ba7a313e/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f70726f647563742f706c7567696e2e706e67) **Plugin** — browse, install, and distribute workflow plugins to extend generation on demand. | ![Integrations page](https://camo.githubusercontent.com/98b533fad41e0f891e7825e971377718dfb4f0944280f6af7ffbb31cd1ed61fc/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f70726f647563742f696e746567726174696f6e732e706e67) **Integrations** — connect external systems and MCP tools, and use Open Design from any IDE, script, or automation. |\n\n\n\n### Studio — many artifact types in one project\n\nInside a project's Studio, the same design system streams out multiple artifact types:\n\n\n\n| ![Prototype](https://camo.githubusercontent.com/bf1079c78f50a2df4de7e9e877adebd3ff54380ebacdf3fb25c28aa317dc4cad/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f70726f647563742f73747564696f2d70726f746f747970652e706e67) **Prototype** — single-page HTML artifacts that read your design system and render in a sandboxed iframe, previewable instantly and downloadable as source. | ![HyperFrame](https://camo.githubusercontent.com/67ad8f124579cc4ad5c17fe5d6ec43e0a03081c75712a97049724eb5a3e60d1b/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f70726f647563742f73747564696f2d68797065726672616d652e706e67) **HyperFrame** — programmatic motion and animated graphics, rendered to a real MP4 (e.g. 1920×1080 · 30fps). |\n| --- | --- |\n| ![Deck](https://camo.githubusercontent.com/79db650ac6ebf80df081958704044461d2e1e6c11934f3ea89087dfcf8bcb706/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f70726f647563742f73747564696f2d7070742e706e67) **Deck** — pitch decks you can page through, navigate by keyboard, and export to PPTX / PDF. | ![Image](https://camo.githubusercontent.com/1b5c222fefebb9e23d9cde3eeea3f6f0494bae5fb18c38229700ceda666ffb3b/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f70726f647563742f73747564696f2d696d6167652e706e67) **Image** — brand-grade images and visual assets, with high-resolution generation and download. |\n\n\n\n---\n\n\n\n## Platform Compatibility\n\n\n\n> Open Design ships as **skills, a CLI, and an MCP server** that mainstream coding agents consume natively. Once OD is installed, a single `od mcp install ` wires the MCP server into that agent's config, and you call the same tools from inside any agent.\n\n\n\n| Coding agent / platform | Status | One-line MCP server install |\n| --- | --- | --- |\n| Claude Code | ✅ Supported | `od mcp install claude` |\n| Codex CLI | ✅ Supported | `od mcp install codex` |\n| DeepSeek Reasonix | ✅ Supported | `od mcp install reasonix` |\n| Raven | ✅ Supported | `od mcp install raven` |\n| Cursor | ✅ Supported | `od mcp install cursor` |\n| VS Code + GitHub Copilot | ✅ Supported | `od mcp install copilot` |\n| GitHub Copilot CLI | ✅ Supported | `od mcp install copilot` |\n| OpenCode | ✅ Supported | `od mcp install opencode` |\n| OpenClaw | ✅ Supported | `od mcp install openclaw` |\n| Antigravity | ✅ Supported | `od mcp install antigravity` |\n| Cline | ✅ Supported | `od mcp install cline` |\n| Trae | ✅ Supported | `od mcp install trae` |\n| Kimi CLI | ✅ Supported | `od mcp install kimi` |\n| Kiro | ✅ Supported | `od mcp install kiro` |\n| Pi Agent | ✅ Supported | `od mcp install pi` |\n| Mistral Vibe CLI | ✅ Supported | `od mcp install vibe` |\n| Hermes Agent | ✅ Supported | `od mcp install hermes` |\n\n`od mcp install --print` for a dry-run preview · `--uninstall` to remove · full list with `od mcp install --help`.\n\n[![The 25 coding-agent CLIs Open Design supports — Claude Code · Codex · OpenCode · Hermes · Antigravity · Vela · Grok Build · Kimi · Cursor Agent · Qwen · Qoder · GitHub Copilot · Pi · Kiro · Kilo · Mistral Vibe · DeepSeek · Reasonix · Aider · Amp · CodeBuddy · Mimo · AtomCode · Devin · Trae](https://camo.githubusercontent.com/67e5284a287c972b89b8e205f8f3a1c7ea5b104bc9ff178f5549e4010de5366d/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f636f64696e672d6167656e74732e706e67)](https://camo.githubusercontent.com/67e5284a287c972b89b8e205f8f3a1c7ea5b104bc9ff178f5549e4010de5366d/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f636f64696e672d6167656e74732e706e67)\n\n**No CLI installed?** The BYOK proxy at `POST /api/proxy/{anthropic,openai,azure,google,ollama,senseaudio}/stream` gives you the same loop (no process spawn) — paste `baseUrl` + `apiKey` + `model`, with presets for OpenAI, Atlas Cloud, Anthropic, Azure OpenAI, Google Gemini, Ollama, LM Studio, vLLM, or any OpenAI-compatible endpoint. Atlas Cloud uses `https://api.atlascloud.ai/v1` with your own key and OpenAI-compatible model ids such as `qwen/qwen3.5-flash`. Per-target SSRF protection blocks internal IPs / link-local / CGNAT at the daemon edge.\n\nRuntime definitions live in [`apps/daemon/src/runtimes/defs/`](https://github.com/nexu-io/open-design/blob/main/apps/daemon/src/runtimes/defs), with registration and shared stream handling under [`apps/daemon/src/runtimes/`](https://github.com/nexu-io/open-design/blob/main/apps/daemon/src/runtimes). See [`docs/agent-adapters.md`](https://github.com/nexu-io/open-design/blob/main/docs/agent-adapters.md) for the adapter contract.\n\n\n\n---\n\n\n\n## Demo\n\nFour core product categories, all rendered by a coding agent running on your laptop. Click a thumbnail to see the real example.\n\n\n\n### 1 · Prototypes — web · desktop · mobile\n\nThe default output surface. Single-page HTML artifacts that read your `DESIGN.md` and render in a sandboxed iframe.\n\n\n\n| ![Entry view](https://github.com/nexu-io/open-design/raw/main/docs/screenshots/01-entry-view.png) **Entry view** — pick a skill, pick a design system, type the brief. One surface for prototypes, dashboards, decks, mobile apps, magazine pages. | ![Mobile onboarding](https://github.com/nexu-io/open-design/raw/main/docs/screenshots/skills/mobile-onboarding.png) **Mobile prototype** — pixel-accurate iPhone 15 Pro chrome, multi-screen flows. The agent never redraws the phone frame; shared device frames live in `assets/frames/`. |\n| --- | --- |\n| ![Web prototype dating-web](https://github.com/nexu-io/open-design/raw/main/docs/screenshots/skills/dating-web.png) **Web prototype** — an editorial dashboard with scrollbars, KPIs, and charts. Rendered straight from `design-templates/dating-web/`. | ![Gamified app](https://github.com/nexu-io/open-design/raw/main/docs/screenshots/skills/gamified-app.png) **Mobile app prototype** — a three-screen gamified flow with XP ribbons and quest detail. Hand off straight to Cursor / Codex / Claude Code to turn into React/Next/Vue. |\n\n\n\n### 2 · Live artifacts & dashboards\n\nLive dashboards, decision rooms, KPI walls — single-page artifacts that pull data through a tweaks panel and stay editable in place.\n\n\n\n| ![Live dashboard](https://github.com/nexu-io/open-design/raw/main/docs/screenshots/skills/live-dashboard.png) **Live dashboard** — an editable KPI wall whose tweaks panel surfaces the parameters worth nudging. The agent emits a manifest, and the iframe re-renders without a reload. | ![Decision room](https://github.com/nexu-io/open-design/raw/main/docs/screenshots/skills/research-decision-room.png) **Decision room** — a multi-source briefing artifact for product / research / ops meetings. |\n| --- | --- |\n| ![GitHub dashboard](https://github.com/nexu-io/open-design/raw/main/docs/screenshots/skills/github-dashboard.png) **GitHub-style dashboard** — repo metrics presented as a live artifact. | ![Flow live dashboard](https://github.com/nexu-io/open-design/raw/main/docs/screenshots/skills/flowai-live-dashboard-template.png) **Flow live-dashboard template** — a domain-specific KPI template, branded through the active `DESIGN.md`. |\n\n\n\n### 3 · Decks — magazine decks, weekly updates, pitches\n\n\n\n| ![Magazine deck (guizang-ppt)](https://github.com/nexu-io/open-design/raw/main/docs/screenshots/07-magazine-deck.png) **Deck mode (guizang-ppt)** — magazine layouts, WebGL hero, P0/P1/P2 checklists. Bundled verbatim from `op7418/guizang-ppt-skill` with its original license preserved. | ![Swiss deck](https://github.com/nexu-io/open-design/raw/main/docs/screenshots/skills/deck-swiss-international.png) **Swiss International-style deck** — grid-anchored, monochrome accents. One of **15 deck templates** and **36 themes** under `design-templates/html-ppt-*/`. |\n| --- | --- |\n\nEvery deck exports to **HTML** (single file, inlined assets), **PDF** (browser print, deck-aware), **PPTX** (agent-driven skill), **ZIP** (archive), or **Markdown**.\n\n\n\n### 4 · Images — gpt-image-2, ImageRouter, custom API\n\n\n\n| ![Illustrated city food map](https://camo.githubusercontent.com/6fa657a2d3ff5fe5a1b4b5cdb76991e7da052682209188e4a5b7dcb88bef8507/68747470733a2f2f636d732d6173736574732e796f756d696e642e636f6d2f6d656469612f313737363636323637333031345f6e66307461775f4847524d4e447962734141474738382e6a7067) **Illustrated city food map** Hand-drawn editorial travel poster | ![Cinematic elevator scene](https://camo.githubusercontent.com/b6f878fd0c45ebc3abbc2835309136eab2e0d500c36c69bdb86ccbce8dbf899e/68747470733a2f2f636d732d6173736574732e796f756d696e642e636f6d2f6d656469612f313737373435333134393032365f6764326b35305f4848435376796d626f4141567363632e6a7067) **Cinematic elevator scene** Single-frame editorial still | ![Cyberpunk anime portrait](https://camo.githubusercontent.com/f0a2c32e49e2f38c4d2ee066b15027add5a7c45f8eda96dc1ba90c1082b76b20/68747470733a2f2f636d732d6173736574732e796f756d696e642e636f6d2f6d656469612f313737373435333136343939335f6d74356236395f4848446f57666561554145413656742e6a7067) **Cyberpunk portrait** Profile avatar — neon face text | ![3D stone staircase evolution](https://camo.githubusercontent.com/de40e76a0d0a5f6f4b819a326d66ab0d4f70d7cd86e3a2fa321de1e41cd1d0c2/68747470733a2f2f636d732d6173736574732e796f756d696e642e636f6d2f6d656469612f313737363636313936383430345f386135666c6d5f484751635f4b4f614d4141327674302e6a7067) **3D stone staircase** Hewn-stone infographic | ![Glamorous portrait](https://camo.githubusercontent.com/0c8920ba286e3bf2402267a01a13923e6e84a2cebae1d46fdb2c875efa2b8ba1/68747470733a2f2f636d732d6173736574732e796f756d696e642e636f6d2f6d656469612f313737373435333138343235375f76623968766c5f48473974416b4f613441417552726e2e6a7067) **Glamorous portrait** Editorial studio shot |\n| --- | --- | --- | --- | --- |\n\n**93 ready-to-replicate prompts** live in [`prompt-templates/`](https://github.com/nexu-io/open-design/blob/main/prompt-templates) — preview thumbnails, full prompt body, target model, aspect ratio, and source attribution. One click drops a brief into the composer.\n\n\n\n### 5 · Video & HyperFrames — agent-native motion graphics\n\n**[HyperFrames](https://github.com/heygen-com/hyperframes)** is HeyGen's open-source, agent-native video framework, integrated as a first-class citizen in Open Design. The agent writes HTML + CSS + GSAP, and HyperFrames renders it to a deterministic MP4 via headless Chrome + FFmpeg. Pair it with **Seedance 2.0** for cinematic t2v / i2v, **Veo 3 / Sora 2 / Kling 2** for routed model variants, and **Suno v5 / Lyria 2** for the audio layer.\n\n\n\n| ![SaaS promo](https://camo.githubusercontent.com/f2c5d04db433ad932047df28524eb1f60df7618993aaa0b7cb9b983bd9c70acd/68747470733a2f2f7374617469632e68657967656e2e61692f68797065726672616d65732d6f73732f646f63732f696d616765732f636174616c6f672f626c6f636b732f6170702d73686f77636173652e706e67) **30s SaaS product promo** · 16:9 · UI 3D reveals | ![TikTok karaoke](https://camo.githubusercontent.com/93aad44a79d01dda8529c4617382393b9b7b5f2b8293f090b6d0c8cd5b22e0e7/68747470733a2f2f7374617469632e68657967656e2e61692f68797065726672616d65732d6f73732f646f63732f696d616765732f636174616c6f672f626c6f636b732f74696b746f6b2d666f6c6c6f772e706e67) **TikTok karaoke talking-head** · 9:16 · TTS + word-synced captions | ![Brand sizzle reel](https://camo.githubusercontent.com/fe1d571773e4b15e1cbd70ce2e2c5cfeb0fa263a69987b398bac971548d9c69b/68747470733a2f2f7374617469632e68657967656e2e61692f68797065726672616d65732d6f73732f646f63732f696d616765732f636174616c6f672f626c6f636b732f6c6f676f2d6f7574726f2e706e67) **30s brand sizzle reel** · 16:9 · audio-reactive kinetic type | ![Bar chart race](https://camo.githubusercontent.com/d7da203e0ca7f0b7622415d6cb0ca5d6efa412e2357fa265a18930535f46288b/68747470733a2f2f7374617469632e68657967656e2e61692f68797065726672616d65732d6f73732f646f63732f696d616765732f636174616c6f672f626c6f636b732f646174612d63686172742e706e67) **Bar chart race** · 16:9 · NYT-style data infographic |\n| --- | --- | --- | --- |\n| ![Flight map](https://camo.githubusercontent.com/4d44d940fad71478f44cd985225f8e2db1f03d6c737eeb8ad2fe076e988078fb/68747470733a2f2f7374617469632e68657967656e2e61692f68797065726672616d65732d6f73732f646f63732f696d616765732f636174616c6f672f626c6f636b732f6e79632d70617269732d666c696768742e706e67) **Flight map** · 16:9 · Apple-style route reveal | ![Logo outro](https://camo.githubusercontent.com/fe1d571773e4b15e1cbd70ce2e2c5cfeb0fa263a69987b398bac971548d9c69b/68747470733a2f2f7374617469632e68657967656e2e61692f68797065726672616d65732d6f73732f646f63732f696d616765732f636174616c6f672f626c6f636b732f6c6f676f2d6f7574726f2e706e67) **4s cinematic logo outro** · 16:9 · piece-by-piece assembly + bloom | ![Money counter](https://camo.githubusercontent.com/8ead3506fef8c686feb719d94063c58ec669e799117229239ce96c7a4bf70432/68747470733a2f2f7374617469632e68657967656e2e61692f68797065726672616d65732d6f73732f646f63732f696d616765732f636174616c6f672f626c6f636b732f6170706c652d6d6f6e65792d636f756e742e706e67) **$0 → $10K money counter** · 9:16 · Apple-style hype | ![Website to video](https://camo.githubusercontent.com/0d12d94c829897cc96d253ceb41dfdfdb4dac4fcaa2215afd8f0abeb4bd9a112/68747470733a2f2f7374617469632e68657967656e2e61692f68797065726672616d65732d6f73732f646f63732f696d616765732f636174616c6f672f626c6f636b732f696e7374616772616d2d666f6c6c6f772e706e67) **Website-to-video** · 16:9 · captures the site at 3 viewports |\n\n11 HyperFrames templates + 39 Seedance prompts ship with the repo. Catalog thumbnails © HeyGen; the framework is Apache-2.0. The OD-specific render workflow (composition cache, sandbox-exec workaround, MP4-as-chip) is detailed in [`design-templates/hyperframes/`](https://github.com/nexu-io/open-design/blob/main/design-templates/hyperframes).\n\n\n\n---\n\n\n\n## Why Open Design\n\n\n\n> **In April 2026, Anthropic released Claude Design — the first time an LLM stopped writing prose and started delivering design artifacts directly.** It went viral. But it stayed closed-source, paid-only, cloud-only, locked to Anthropic's model, Anthropic's skills, Anthropic's surface. No checkout, no self-host, no Vercel deploy, no swap-in-your-own-agent.\n\nOpen Design (OD) is the open-source alternative. Same loop, same artifact-first mental model, none of the lock-in:\n\n- 🤖 **Agent-native, model-agnostic.** We don't ship an agent. The `claude` / `codex` / `cursor-agent` / `copilot` / `hermes` / `kimi` already on your `PATH` are the design engine. Swap with one click.\n- 🧠 **Brand-grade by default.** Every render reads the active package's `DESIGN.md` as the core brand contract. 151 design-system packages ship with the repo; legacy packages may be `DESIGN.md` -only, while newer packages can add `manifest.json`, `tokens.css`, components, assets, and provenance. Drop a folder in, the picker finds it.\n- 🖥️ **Local-first, BYOK at every layer.** Native desktop apps for macOS (Apple Silicon + Intel) and Windows (x64). Linux AppImage on the optional release lane. Product analytics and session replay are consent-gated; scrubbed safety and reliability telemetry is always on. Before describing daemon data paths, contributors and operators MUST read `AGENTS.md` → **Daemon data directory contract**. This README MUST NOT restate it.\n- 🌍 **Composable on four planes.** **Plugins** carry runnable workflows · functional **skills** carry agent behavior · **design templates** carry rendering blueprints · **design systems** carry the brand. All four use portable, versionable directories that anyone can author and publish.\n- 🔁 **Refresh an existing codebase.** Hand a `git` repo + `DESIGN.md` to the agent and it refactors your real components to the brand spec. Dedicated plugins migrate Figma / Pencil workflows into React / Next.js / Vue code.\n- 🔒 **Privacy by conviction.** Everything runs where your data lives — your laptop, your team's server, your Vercel project. When the network is needed, the BYOK proxy is SSRF-guarded.\n\n### Comparison\n\n\n\n| Claude Design | Figma | Lovable / v0 / Bolt | **Open Design** |\n| --- | --- | --- | --- |\n| Open source | ❌ | ❌ | ❌ | **✅ Apache-2.0** |\n| Self-host / desktop | ❌ | ❌ | ❌ | **✅ macOS + Windows + Docker + Vercel web** |\n| Agent-native (runs in your CLI) | Anthropic only | ❌ | Cloud agent only | **✅ 25 CLIs + BYOK** |\n| Brand-grade `DESIGN.md` | Proprietary | Theme JSON | Limited tokens | **✅ 151 systems shipped** |\n| Skills / plugins / templates | Closed | Plugin store | Closed | **✅ 100+ functional skills · rendering templates · 277 plugins** |\n| HyperFrames (HTML→MP4) | ❌ | ❌ | ❌ | **✅ First-class** |\n| Refresh an existing repo to brand | ❌ | ❌ | ❌ | **✅ via agent + `DESIGN.md`** |\n| Minimum billing | Pro / Max / Team | Pro / Org | Pro / Team | **BYOK · any compatible endpoint** |\n\n\n\n---\n\n\n\n## Quick start\n\nThe fastest way to use Open Design. No Node, no pnpm, no clone.\n\n- **macOS** (Apple Silicon · Intel x64) → [**open-design.ai**](https://open-design.ai/?utm_source=github&utm_medium=referral&utm_content=readme_download_macos) or [GitHub Releases](https://github.com/nexu-io/open-design/releases)\n- **Windows** (x64) → [**open-design.ai**](https://open-design.ai/?utm_source=github&utm_medium=referral&utm_content=readme_download_windows) or [GitHub Releases](https://github.com/nexu-io/open-design/releases)\n- **Linux** (AppImage, optional lane) → [GitHub Releases](https://github.com/nexu-io/open-design/releases) After install: the app auto-detects every coding-agent CLI on your `PATH`, loads 100+ functional skills, the separate rendering-template catalog, and 151 design systems, and lets you type a brief in the entry view.\n\n\n\n### 🤖 Install into your coding agent (no UI)\n\nYou can use Open Design without ever opening the GUI — call it as a skill, plugin, or MCP server inside Claude Code, Codex, Cursor, Copilot, OpenClaw, Antigravity, Hermes, Kimi, and more.\n\nIf you installed the macOS desktop app via the DMG or Homebrew cask, your shell may still resolve `od` to Apple's built-in `/usr/bin/od` octal-dump utility. In that case, open **Settings → MCP server** in the desktop app and copy the client-specific snippet; it uses absolute paths and does not rely on the bare `od` command.\n\n\n\n```\n# One-line install into the agent you're using:\nod mcp install\n# = claude | codex | reasonix | raven | cursor | copilot | openclaw\n# | antigravity | pi | vibe | hermes | cline | kimi | kiro\n# | trae | opencode\n\n# Hosted equivalent for curl-based setup:\ncurl -fsSL https://open-design.ai/install.sh | sh -s\n```\n\n`install.sh` is a thin shell wrapper around `od mcp install`; it exists so the hosted URL returns shell instead of the landing-page HTML fallback and fails fast if your shell resolves a non-Open-Design `od` binary.\n\n\n\n> **macOS / WSL2 users:** `/usr/bin/od` is a system octal-dump command and can shadow Open Design's `od` command. Desktop-app users should prefer the **Settings → MCP server** snippet; WSL2 users should follow the [`WSL2 setup guide`](https://github.com/nexu-io/open-design/blob/main/docs/wsl-setup.md) first.\n\nThen, inside the agent:\n\n\n\n```\n> Use open-design to generate a landing page with the Linear design system\n```\n\nIn a filesystem-backed local CLI run, the agent composes the selected functional skill or design template with your `DESIGN.md`, writes the canonical project files, and Open Design previews those files. A BYOK/plain-API run without filesystem tools instead returns one complete `` block.\n\n\n\n### 🐳 Run with Docker\n\n\n\n```\ngit clone https://github.com/nexu-io/open-design.git\ncd open-design/deploy\ncp .env.example .env\necho \"OD_API_TOKEN=$(openssl rand -hex 32)\" >> .env\ndocker compose up -d\n# open http://localhost:7456\n```\n\n\n\n> **macOS users:** If the web UI shows `Authorization: Bearer required`, Docker Desktop bridge networking is the cause. See [Docker Desktop on macOS](https://github.com/nexu-io/open-design/blob/main/deploy/README.md#docker-desktop-on-macos) for the fix.\n\n\n\n### 🚀 Deploy on Sealos\n\n[![Deploy on Sealos](https://camo.githubusercontent.com/ea79f0254cdc854923560e4dc71f7e63ffe09b31cad41657a11a077dccdee01d/68747470733a2f2f7365616c6f732e696f2f4465706c6f792d6f6e2d5365616c6f732e737667)](https://sealos.io/products/app-store/open-design/)\n\nThe Sealos App Store template runs the published Open Design Docker image with persistent workspace storage and Basic Auth on the public proxy. For custom public or shared Docker deployments, follow the reverse-proxy and `OPEN_DESIGN_ALLOWED_ORIGINS` guidance in [`deploy/README.md`](https://github.com/nexu-io/open-design/blob/main/deploy/README.md#local-compose).\n\n\n\n### 🧑💻 Run from source\n\n\n\n```\ngit clone https://github.com/nexu-io/open-design.git\ncd open-design\ncorepack enable && pnpm install\npnpm tools-dev run web\n```\n\nOpen the URL printed by `tools-dev`; development ports are allocated dynamically unless you pass explicit port flags.\n\nNode `~24`, pnpm `10.33.x`. WSL2 users, see [`docs/wsl-setup.md`](https://github.com/nexu-io/open-design/blob/main/docs/wsl-setup.md); native Windows users, see [`docs/windows-troubleshooting.md`](https://github.com/nexu-io/open-design/blob/main/docs/windows-troubleshooting.md). Full quickstart, env vars, Nix flake, and packaged build flow → [`QUICKSTART.md`](https://github.com/nexu-io/open-design/blob/main/QUICKSTART.md).\n\n\n\n### A full workflow — from brief to artifact\n\n`brief → plugin → direction → design system → artifact → handoff → memory`\n\n1. **A PM submits a brief.** The plugin picker offers landing page · pitch deck · dashboard · social post · PM spec · OKR scorecard…\n2. **A designer (or the agent) locks the direction.** No brand? Pick from 5 curated directions. Have a brand? Drop a screenshot / URL → the agent connects GitHub, imports Figma, and codifies a reusable `DESIGN.md`.\n3. **The agent creates the first deliverable.** Plugin + functional skill or design template + `DESIGN.md` are bound. Filesystem-backed CLI runs write canonical project files and the preview follows them; BYOK/plain-API runs without file tools return one complete `` block.\n4. **Hand off to engineering.** The artifact is real HTML/CSS — drop it into Cursor, Codex, or Claude Code to keep building as code. Or export PPTX / PDF / MP4 straight to marketing.\n5. **Open Design gets smarter as you use it.** Your screenshots, fonts, palettes, and confirmed artifacts accumulate as defaults for the next session. Less rework, less drift.\n\n---\n\n\n\n## Use Open Design from your coding agent\n\nOpen Design ships a **stdio MCP server** and per-agent **install scripts**. Any MCP-compatible agent in another repo can read files from your local Open Design projects directly — tokens CSS, JSX components, entry HTML — as a structured API queryable by name. The agent always sees the live file, not a stale export.\n\n\n\n```\n# One-line install (16+ CLIs supported):\nod mcp install\n\n# Then the agent can:\nod project list --json\nod files list --json\nod files read\nod plugin list --json\nod skills list --json\n```\n\n**Why MCP?** Exporting and re-attaching a zip every iteration breaks flow. MCP exposes the design source directly — the agent always sees the live file.\n\n**For an agent starting from scratch,** the installer places `~/.config//open-design.json` (or the platform equivalent) plus a copy-paste MCP snippet. Cursor gets a one-click deeplink; Claude Code gets a `claude mcp add-json` one-liner; every other agent gets JSON in the schema its config expects. On macOS desktop installs, prefer that Settings snippet over typing bare `od mcp install ` in Terminal, because `/usr/bin/od` may win on PATH. Full per-agent flow → **Settings → MCP server** in the desktop app, or [`docs/agent-adapters.md`](https://github.com/nexu-io/open-design/blob/main/docs/agent-adapters.md).\n\n**Security model.** Read-only by default, the daemon binds to `127.0.0.1`, and SSRF is blocked at the proxy edge. LAN exposure requires an explicit `OD_BIND_HOST` plus `OD_ALLOWED_ORIGINS`. Connector credentials and live-artifact preview routes stay loopback-only regardless.\n\n**Internally-hosted model endpoints.** To prevent SSRF, the daemon blocks provider base URLs that resolve to private/internal address ranges (RFC1918, link-local, CGNAT, and cloud-metadata IPs) by default, surfacing `Internal IPs blocked`. If you run an internally-hosted gateway (e.g. LiteLLM or Ollama on a VPN-only `10.x` / `192.168.x` address), opt that host out with `OD_ALLOWED_INTERNAL_HOSTS=,,...` — a comma- or whitespace-separated list of bare hostnames or IPs (`10.0.0.5`, `litellm.internal.corp`; a `host:port` or full URL is accepted and reduced to its hostname; IPv6 must be bracketed, e.g. `[fd00::1]`). The allowlist is strict opt-in (empty by default), exact-host (no subdomain/substring matching), and applies **only** to provider endpoints you configure (connection test, model discovery, BYOK chat). It deliberately does **not** relax the guard on download URLs returned inside upstream responses, which stay blocked. A malformed entry — or CIDR notation, which is not supported — is dropped with a warning rather than silently trusted, so a typo never quietly widens (or fails to widen) the guard. Allowlisting a hostname trusts whatever it resolves to (like `OD_ALLOWED_ORIGINS`); allowlist the resolved IP instead if you want the DNS-resolved address re-checked.\n\n\n\n---\n\n\n\n## Skills and design templates\n\n**100+ functional skills ship in [`skills/`](https://github.com/nexu-io/open-design/blob/main/skills)**. Each follows the Agent Skills [`SKILL.md`](https://docs.anthropic.com/en/docs/claude-code/skills) convention and supplies reusable agent behavior, references, or utilities. Renderable starters live separately in [`design-templates/`](https://github.com/nexu-io/open-design/blob/main/design-templates); they may also use `SKILL.md`, but they populate the design-template catalog rather than the functional-skill registry.\n\nTwo **modes** anchor the design-template catalog: `prototype` (web/mobile/desktop single-page artifacts) and `deck` (horizontal-swipe presentations). Other templates cover `image`, `video`, `audio`, and utility surfaces. The **`scenario`** field groups templates by audience: `design` · `marketing` · `operation` · `engineering` · `product` · `finance` · `hr` · `sale` · `personal`.\n\n\n\n| Design template | Mode | Scenario | What it produces |\n| --- | --- | --- | --- |\n| `web-prototype` | prototype | design | Default landing page / hero |\n| `saas-landing` | prototype | marketing | Hero / features / pricing / CTA |\n| `dashboard` | prototype | operation | Admin / analytics (with sidebar) |\n| `mobile-app` | prototype | design | iPhone 15 Pro / Pixel framed app |\n| `mobile-onboarding` | prototype | design | Splash · value-prop · sign-in flow |\n| `social-carousel` | prototype | marketing | 3-card 1080×1080 carousel |\n| `email-marketing` | prototype | marketing | Table-fallback-safe brand email |\n| `magazine-poster` | prototype | marketing | Single-page magazine layout |\n| `motion-frames` | prototype | marketing | Looping CSS motion hero |\n| `sprite-animation` | prototype | marketing | 8-bit pixel animated explainer |\n| `pm-spec` | prototype | product | PM spec doc (with TOC + decision log) |\n| `team-okrs` | prototype | product | OKR scorecard |\n| `eng-runbook` | prototype | engineering | Incident runbook |\n| `finance-report` | prototype | finance | Exec finance summary |\n| `hr-onboarding` | prototype | hr | Role onboarding plan |\n| `guizang-ppt` | deck | marketing | Magazine-style web PPT (deck default) |\n| `html-ppt-*` | deck | marketing | 15 deck templates × 36 themes (master template in `design-templates/html-ppt/`) |\n| `hyperframes` | video | marketing | HTML → MP4 motion graphics (HeyGen OSS framework) |\n| `critique` | utility | design | Five-dimensional self-critique scoresheet |\n| `tweaks` | utility | design | AI-emitted tweaks-panel manifest |\n\nFull protocol and directory split → [`docs/skills-protocol.md`](https://github.com/nexu-io/open-design/blob/main/docs/skills-protocol.md). Registry endpoints: `GET /api/skills` for functional skills and `GET /api/design-templates` for rendering templates.\n\n\n\n---\n\n\n\n## Design Systems\n\n**151 brand-grade design-system packages centered on `DESIGN.md`** ship with the repo. Legacy packages may contain only that Markdown contract; newer packages can also carry `manifest.json`, compiled `tokens.css`, component fixtures, assets, and provenance evidence. The catalog mixes upstream-derived systems with project-owned additions; [`design-systems/README.md`](https://github.com/nexu-io/open-design/blob/main/design-systems/README.md) records the package shape and provenance. Switch a system → the next render uses the new tokens.\n\n**Full catalog (click to expand)** **AI & LLM** — `claude` · `cohere` · `mistral-ai` · `minimax` · `together-ai` · `replicate` · `runwayml` · `elevenlabs` · `ollama` · `x-ai`\n\n**Developer Tools** — `cursor` · `vercel` · `linear-app` · `framer` · `expo` · `clickhouse` · `mongodb` · `supabase` · `hashicorp` · `posthog` · `sentry` · `warp` · `webflow` · `sanity` · `mintlify` · `lovable` · `composio` · `opencode-ai` · `voltagent`\n\n**Productivity** — `notion` · `figma` · `miro` · `airtable` · `superhuman` · `intercom` · `zapier` · `cal` · `clay` · `raycast`\n\n**Fintech** — `stripe` · `coinbase` · `binance` · `kraken` · `mastercard` · `revolut` · `wise`\n\n**E-commerce** — `shopify` · `airbnb` · `uber` · `nike` · `starbucks` · `pinterest`\n\n**Media** — `spotify` · `playstation` · `wired` · `theverge` · `meta`\n\n**Automotive** — `tesla` · `bmw` · `ferrari` · `lamborghini` · `bugatti` · `renault`\n\n**Other** — `apple` · `ibm` · `nvidia` · `vodafone` · `resend` · `spacex`\n\n**Starters** — `default` (Neutral Modern) · `warm-editorial`\n\nRe-import the library via [`scripts/sync-design-systems.ts`](https://github.com/nexu-io/open-design/blob/main/scripts/sync-design-systems.ts). Add your own brand → drop a `DESIGN.md` into `design-systems//`. Full guide → [`design-systems/README.md`](https://github.com/nexu-io/open-design/blob/main/design-systems/README.md).\n\n\n\n---\n\n\n\n## Plugins\n\n**277 official plugins plus 183 remixable reference examples** live in [`plugins/_official/`](https://github.com/nexu-io/open-design/blob/main/plugins/_official). Each entry is a portable plugin directory anchored by `open-design.json` plus the payload required by its type: for example `SKILL.md` for agent workflows, `template.json` for media templates, or `DESIGN.md` for design-system entries. Jump straight to a category:\n\n\n\n| Category | Count | Contents |\n| --- | --- | --- |\n| `scenarios/` | 13 | Complete design scenarios — `od-default`, `od-design-refine`, `od-figma-migration`, `od-code-migration`, `od-react-export`, `od-nextjs-export`, `od-vue-export`, `od-media-generation`, `od-new-generation`, `od-tune-collab`, `od-plugin-authoring`, `od-share-to-community`, `od-web-effect-extractor` |\n| `image-templates/` | 45 | One-shot image prompts — editorial, cinematic, product, portrait |\n| `video-templates/` | 63 | HyperFrames / Seedance / Veo motion templates |\n| `design-systems/` | 143 | Brand `DESIGN.md` wrapped as plugins |\n| `atoms/` | 13 | Reusable UI fragments (buttons, heroes, KPI cards) |\n| `examples/` | 183 | Remixable reference outputs |\n\nAlso [`plugins/community/`](https://github.com/nexu-io/open-design/blob/main/plugins/community) for community plugins and [`plugins/registry/`](https://github.com/nexu-io/open-design/blob/main/plugins/registry) for the publishing flow.\n\n\n\n### What plugins can do\n\n- 🤖 **Run in any coding agent** — [Claude Code](https://github.com/nexu-io/open-design/blob/main/docs/agent-adapters.md), Codex, Cursor, Copilot, [OpenClaw](https://github.com/openclaw/openclaw), [Antigravity](https://antigravity.google/), Hermes, Kimi… through the same skill protocol the agent already knows.\n- 🔁 **Migrate Figma / Pencil workflows** → React, Next.js, or Vue source. See [`od-figma-migration`](https://github.com/nexu-io/open-design/blob/main/plugins/_official/scenarios/od-figma-migration).\n- 🛠️ **Refresh an existing codebase to a brand spec** — point a plugin at a `git` repo + `DESIGN.md`, get a PR. See [`od-code-migration`](https://github.com/nexu-io/open-design/blob/main/plugins/_official/scenarios/od-code-migration).\n- 💾 **Persist custom workflows** — your team's reusable templates sit next to the shipped ones.\n\n### Using plugins\n\nPlugins are at full parity across the **web UI** and the **`od` CLI** — same `/api/plugins` endpoints, pick whichever fits.\n\n**In the desktop / web app:** open the **Plugin** page to browse the marketplace and click **Install**; inside a project's Studio, plugins appear as composer chips you click to apply (with the inputs they declare).\n\n**On the command line** (runs without a UI — this is the path external agents use):\n\n\n\n```\nod plugin list # list installed plugins (--task-kind / --mode / --tag filters)\nod plugin search \"landing page\" # search by keyword\nod plugin info od-default # inspect a plugin's metadata, inputs, capabilities\nod plugin install od-figma-migration # install from a registry; also accepts ./local-folder or an https://… link\nod plugin apply od-default --input brief=\"a one-page pitch for our seed round\"\nod plugin upgrade od-default # upgrade\nod plugin uninstall od-default # uninstall\n```\n\nEvery command supports `--json`, so you can pipe it through `jq` / `xargs` into automation.\n\n\n\n### Building a plugin\n\nAn Open Design plugin requires `open-design.json` plus the payload required by its type. A workflow skill or scenario also includes `SKILL.md`; manifest-only template and design-system entries use their own payloads instead:\n\n\n\n```\nmy-plugin/\n├── open-design.json ← required: marketplace metadata + inputs + pipeline + capabilities\n├── SKILL.md ← required for agent-skill/scenario entries; omitted for other plugin types\n├── README.md ← optional: usage, install, registry links\n├── preview/ ← optional: index.html / poster.png (strongly recommended for visual plugins)\n└── examples/ ← optional: concrete use cases\n```\n\nCore `open-design.json` fields: `specVersion` (currently `1.0.0`), `name` (stable ID), `version` (semver), optional `compat.agentSkills[].path` (points at `./SKILL.md` when the entry exposes an Agent Skill), `od.kind` (`skill` / `scenario` / `atom` / `bundle`), `od.taskKind` (`new-generation` / `figma-migration` / `code-migration` / `tune-collab`), `od.mode` (the output surface, e.g. `prototype` / `deck` / `live-artifact` / `image` / `video` / `hyperframes` / `audio` / `design-system` / `scenario`), `od.capabilities[]` (**declare the minimum** — a restricted install grants only `prompt:inject` by default), `od.inputs[]` (apply-time parameters).\n\nScaffold + validate locally:\n\n\n\n```\nod plugin scaffold --id my-plugin --title \"My Plugin\" # generate the skeleton\nod plugin validate ./my-plugin # check manifest / file layout\npnpm guard && pnpm --filter @open-design/plugin-runtime typecheck\n```\n\nFull field set and runtime contract → [`plugins/spec/SPEC.md`](https://github.com/nexu-io/open-design/blob/main/plugins/spec/SPEC.md); developing a plugin with a coding agent → [`plugins/spec/AGENT-DEVELOPMENT.md`](https://github.com/nexu-io/open-design/blob/main/plugins/spec/AGENT-DEVELOPMENT.md); copy-paste minimal templates → [`plugins/spec/examples/`](https://github.com/nexu-io/open-design/blob/main/plugins/spec/examples).\n\n\n\n### Contributing a plugin\n\n1. Drop the plugin folder into [`plugins/community/`](https://github.com/nexu-io/open-design/blob/main/plugins/community) (third-party plugins), or — to ship it bundled with Open Design — into the matching tier of [`plugins/_official/`](https://github.com/nexu-io/open-design/blob/main/plugins/_official).\n2. Pass validation: `od plugin validate`, `pnpm guard`, `pnpm --filter @open-design/plugin-runtime typecheck`.\n3. Fill the PR using the template in [`plugins/spec/CONTRIBUTING.md`](https://github.com/nexu-io/open-design/blob/main/plugins/spec/CONTRIBUTING.md) (ID, version, lane, mode, capabilities, trigger examples; attach a screenshot / preview for visual plugins).\n4. To publish to an external registry (skills.sh / ClawHub / standalone GitHub) → [`plugins/spec/PUBLISHING-REGISTRIES.md`](https://github.com/nexu-io/open-design/blob/main/plugins/spec/PUBLISHING-REGISTRIES.md). Plugin registry endpoint: `GET /api/plugins`. Directory overview → [`plugins/README.md`](https://github.com/nexu-io/open-design/blob/main/plugins/README.md) ([简体中文](https://github.com/nexu-io/open-design/blob/main/plugins/README.zh-CN.md)).\n\n\n\n---\n\n\n\n## Architecture\n\n\n\n```\n┌────────────────── browser (Next.js 16) / Electron shell ──────────────┐\n│ chat · file workspace · iframe preview · settings · import · MCP │\n└──────────────┬─────────────────────────────────────┬─────────────────┘\n│ /api/* │\n▼ ▼\n┌─────────────────────────────────┐ /api/proxy/{provider}/stream (SSE)\n│ local daemon (Express+SQLite) │ ─→ any OpenAI-compatible BYOK,\n│ │ SSRF-guarded at the edge\n│ /api/skills /api/design-templates /api/plugins │\n│ /api/design-systems │\n│ /api/chat (SSE) /api/proxy/* │\n│ /api/projects/:id/files/... │\n│ /api/artifacts/{save,lint} │\n│ /api/import/claude-design │\n│ MCP stdio server │\n└─────────┬───────────────────────┘\n│ spawn(cli, [...], { cwd: managed project cwd })\n▼\n┌──────────────────────────────────────────────────────────────────┐\n│ Local runtime definitions come from runtimes/registry.ts; │\n│ the base registry has 26 definitions (including byok-opencode), │\n│ backed by 25 distinct local CLI executables because byok-opencode shares │\n│ the OpenCode executable. See docs/agent-adapters.md. │\n│ composes a functional skill or design template + DESIGN.md; writes files │\n└──────────────────────────────────────────────────────────────────┘\n```\n\n\n\n| Layer | Stack |\n| --- | --- |\n| Frontend | Next.js 16 App Router + React 18 + TypeScript |\n| Daemon | Node 24 · Express · SSE streaming · `better-sqlite3` |\n| Storage | Before changing or documenting daemon storage paths, you MUST read `AGENTS.md` → **Daemon data directory contract**. This README MUST NOT restate it. |\n| Preview | Filesystem runs render canonical project files; BYOK/plain-API runs parse one complete `` block into a sandboxed `srcdoc` iframe |\n| Export | HTML (inlined) · PDF (browser print) · PPTX (agent-driven) · ZIP · Markdown · MP4 (HyperFrames) |\n| Desktop | Electron shell + sandboxed renderer + sidecar IPC (STATUS · EVAL · SCREENSHOT · CONSOLE · CLICK · SHUTDOWN) |\n| Lifecycle | One entry point: `pnpm tools-dev` (start / stop / run / status / logs / inspect / check) |\n\nFull architecture → [`docs/architecture.md`](https://github.com/nexu-io/open-design/blob/main/docs/architecture.md). Skill protocol → [`docs/skills-protocol.md`](https://github.com/nexu-io/open-design/blob/main/docs/skills-protocol.md). Agent adapter contract → [`docs/agent-adapters.md`](https://github.com/nexu-io/open-design/blob/main/docs/agent-adapters.md).\n\n\n\n---\n\n\n\n## Roadmap\n\n- Daemon + 26 runtime definitions across 25 distinct coding-agent CLI executables + skill/design-template registries + design-system catalog\n- Web app + chat + question form + 5-direction picker + todo progress + sandboxed preview\n- 100+ functional skills · separate rendering-template catalog · 151 design-system packages · 5 visual directions · 5 device frames\n- SQLite-backed projects · conversations · messages · tabs · templates\n- Multi-provider BYOK proxy (`/api/proxy/{anthropic,openai,azure,google,ollama,senseaudio}/stream`) with OpenAI-compatible presets including Atlas Cloud + SSRF guard\n- Claude Design ZIP import (`/api/import/claude-design`)\n- Sidecar protocol + Electron desktop + IPC automation\n- Artifact lint API + 5-dim self-critique pre-emit gate\n- **0.8.0** — plugin marketplace infrastructure (261 official plugins, manifest spec, per-agent install scripts)\n- **0.9.0** — Open Design Cloud (official model service built into the app: zero config, one-click sign-in)\n- **0.10.0** — the all-in-one design workspace: the whole craft loop in one window (references → material → interactive editing → motion → handoff)\n- **0.11.0** — *The Bazaar*: built in the open — a community marketplace of plugins and design systems anyone can pick from and contribute to\n- **0.12.0** — *Brand-backed Design System*: turn the brand you already own into a reusable, portable `DESIGN.md` system\n- **0.13.0** — *Stay in Flow*: native session resume, faster model picking, and export straight to screenshot-backed PPTX / PDF\n- Packaged Electron builds — macOS (Apple Silicon + Intel) + Windows (x64) + Linux AppImage (optional lane)\n- Comment-mode surgical edits — partially shipped; reliable targeted patching in progress\n- AI-emitted tweaks panel UX — not yet implemented\n- `npx od init` to scaffold a project with `DESIGN.md`\n- Plugin SDK + `od plugin {add,list,remove,test,publish}` CLI\n- Figma / Pencil → React / Next / Vue migration plugins (alpha)\n- Refresh-existing-codebase plugin (point at a git repo + `DESIGN.md`) Phased delivery → [`docs/roadmap.md`](https://github.com/nexu-io/open-design/blob/main/docs/roadmap.md).\n\n\n\n---\n\n\n\n## Community\n\nReal people behind every channel.\n\n- 💬 **Discord** — daily chat, plugin sharing, questions → [**discord.gg/mHAjSMV6gz**](https://discord.gg/mHAjSMV6gz)\n- 🐦 **X / Twitter** — release notes, milestones, behind the scenes → [**@OpenDesignHQ**](https://x.com/OpenDesignHQ)\n- 🗣️ **GitHub Discussions** — deep Q&A, RFCs, \"show your work\" → [**Discussions**](https://github.com/nexu-io/open-design/discussions)\n- 🐛 **GitHub Issues** — bug reports, feature requests → [**Issues**](https://github.com/nexu-io/open-design/issues) The [`good-first-issue`](https://github.com/nexu-io/open-design/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) and [`help-wanted`](https://github.com/nexu-io/open-design/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22) labels are the easiest way in.\n\n\n\n---\n\n\n\n## Contributing\n\nOpen Design keeps moving because contributors — designers, engineers, prompt authors — keep showing up. Many of the most-used skills, design systems, and plugins were written by people outside the core team.\n\n\n\n### 🎯 Where to start (max leverage, min change)\n\n\n\n| Want to ship… | How | Where |\n| --- | --- | --- |\n| A new functional **skill** | Drop a folder with `SKILL.md` + optional `assets/` + `references/` | `skills/` · spec in `docs/skills-protocol.md` |\n| A new rendering **design template** | Add a renderable `SKILL.md` bundle | `design-templates/` |\n| A new **design system** | Drop a package centered on `DESIGN.md`; add `manifest.json`, `tokens.css`, components, assets, or provenance when needed | `design-systems//` |\n| A new **plugin** | Drop `open-design.json` + the type-specific payload under a category folder | `plugins/community/` · spec in `plugins/spec/SPEC.md` · agent dev guide in `plugins/spec/AGENT-DEVELOPMENT.md` |\n| Support a new **coding-agent CLI** | One runtime definition + registry entry; add a parser only for a new wire format | `apps/daemon/src/runtimes/defs/` |\n| Fix a bug or polish UI | Browse the `good-first-issue` label | Issues → |\n| Translate the docs | Update the `README..md` files | `TRANSLATIONS.md` |\n\n\n\n### 🤖 Contributing as an agent\n\nIf *you are the agent reading this*, the fastest path is:\n\n\n\n```\n# 1. Boot locally\ngit clone https://github.com/nexu-io/open-design.git\ncd open-design && corepack enable && pnpm install\npnpm tools-dev run web\n\n# 2. Find a good-first-issue and assign yourself\ngh issue list --label \"good first issue\" --state open --limit 20\ngh issue develop # create a branch and worktree\n\n# 3. Make the change, run the checks\npnpm guard && pnpm typecheck\npnpm --filter @open-design/ test\n\n# 4. Open the PR\ngh pr create --fill\n```\n\nFull agent-friendly contribution flow, code style, and PR bar → [`CONTRIBUTING.md`](https://github.com/nexu-io/open-design/blob/main/CONTRIBUTING.md) ([Deutsch](https://github.com/nexu-io/open-design/blob/main/docs/i18n/CONTRIBUTING.de.md) · [Français](https://github.com/nexu-io/open-design/blob/main/docs/i18n/CONTRIBUTING.fr.md) · [简体中文](https://github.com/nexu-io/open-design/blob/main/docs/i18n/CONTRIBUTING.zh-CN.md) · [日本語](https://github.com/nexu-io/open-design/blob/main/docs/i18n/CONTRIBUTING.ja-JP.md) · [한국어](https://github.com/nexu-io/open-design/blob/main/docs/i18n/CONTRIBUTING.ko.md) · [Português](https://github.com/nexu-io/open-design/blob/main/docs/i18n/CONTRIBUTING.pt-BR.md) · [ภาษาไทย](https://github.com/nexu-io/open-design/blob/main/docs/i18n/CONTRIBUTING.th.md)).\n\n\n\n### 🏅 Open Design Fellow program\n\nWe're recruiting **Open Design Fellows** around the world — Fellows shape the product alongside the core team, represent Open Design officially in their region, and grow the community locally, backed by funded support ($1,000 / MR), free LLM credits, and a direct review track. Details → [`MAINTAINERS.md`](https://github.com/nexu-io/open-design/blob/main/MAINTAINERS.md) and the announcement on [Discord](https://discord.gg/mHAjSMV6gz).\n\n\n\n---\n\n\n\n## Maintainers\n\nThey carry a lot of the load — daily maintenance, review, and community support.\n\n\n\n| ![@Nagendhra-web](https://github.com/Nagendhra-web.png) **@Nagendhra-web** Maintainer | ![@Sid-Qin](https://github.com/Sid-Qin.png) **@Sid-Qin** Maintainer | ![@YOMXXX](https://github.com/YOMXXX.png) **@YOMXXX** Maintainer |\n| --- | --- | --- |\n\nMaintainer rules, promotion criteria, and the exit protocol → [`MAINTAINERS.md`](https://github.com/nexu-io/open-design/blob/main/MAINTAINERS.md) (also [Deutsch](https://github.com/nexu-io/open-design/blob/main/docs/i18n/MAINTAINERS.de.md) · [Français](https://github.com/nexu-io/open-design/blob/main/docs/i18n/MAINTAINERS.fr.md) · [简体中文](https://github.com/nexu-io/open-design/blob/main/docs/i18n/MAINTAINERS.zh-CN.md) · [日本語](https://github.com/nexu-io/open-design/blob/main/docs/i18n/MAINTAINERS.ja-JP.md) · [한국어](https://github.com/nexu-io/open-design/blob/main/docs/i18n/MAINTAINERS.ko.md) · [Português](https://github.com/nexu-io/open-design/blob/main/docs/i18n/MAINTAINERS.pt-BR.md) · [ภาษาไทย](https://github.com/nexu-io/open-design/blob/main/docs/i18n/MAINTAINERS.th.md)).\n\n\n\n## Contributors\n\nThanks to everyone who has taken part — code, docs, feedback, a sharp issue, a new skill, a new design system.\n\n[![Open Design contributors](https://camo.githubusercontent.com/2208217c7f3633ca71b24147888d7996ecf9724aed2026cddcfd0747f5ad7a5a/68747470733a2f2f636f6e747269622e726f636b732f696d6167653f7265706f3d6e6578752d696f2f6f70656e2d64657369676e266d61783d35303026636f6c756d6e733d323026616e6f6e3d312663616368655f627573743d323032362d30382d3034)](https://github.com/nexu-io/open-design/graphs/contributors)\n\n---\n\n\n\n## Repository activity\n\n\n\n![Open Design — repository metrics](https://camo.githubusercontent.com/578869d8ce49ad650d21acd62603f7846b8a3f215dfa0ea4bab4546129c1c1f8/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f6769746875622d6d6574726963732e737667)\n\n\nThe SVG above is regenerated daily by [`.github/workflows/metrics.yml`](https://github.com/nexu-io/open-design/blob/main/.github/workflows/metrics.yml) using [`lowlighter/metrics`](https://github.com/lowlighter/metrics).\n\n\n\n---\n\n\n\n## Star us\n\n[![Star Open Design on GitHub — github.com/nexu-io/open-design](https://camo.githubusercontent.com/591d034afc535cc83bc56d4090d4282ba5371e8ad60f8fde4b6ee81b560a3443/68747470733a2f2f7265706f2d6173736574732e6f70656e2d64657369676e2e61692f7265736f75726365732f696d616765732f737461722d75732e706e67)](https://github.com/nexu-io/open-design)\n\nIf this saved you thirty minutes, give it a ★. Stars don't pay rent — but they tell the next designer, agent, and contributor that this experiment is worth their attention. One click, three seconds, a real signal.\n\n[![Open Design star history](https://camo.githubusercontent.com/14c169d6c560776ba61203c58384dd6358066b82c40db615e4eb343949f359f0/68747470733a2f2f6170692e737461722d686973746f72792e636f6d2f7376673f7265706f733d6e6578752d696f2f6f70656e2d64657369676e26747970653d446174652663616368655f627573743d323032362d30382d3034)](https://star-history.com/#nexu-io/open-design&Date)\n\n---\n\n\n\n## References & lineage\n\n\n\n| Project | Role |\n| --- | --- |\n| Claude Design | The closed-source product this repo is the open-source alternative to. |\n| `alchaincyf/huashu-design` | The design-philosophy compass — junior-designer workflow, brand-asset protocol, anti-AI-slop checklist, five-dimensional critique. |\n| `op7418/guizang-ppt-skill` | The magazine-style web PPT skill, bundled verbatim under `design-templates/guizang-ppt/`. Default for deck mode. |\n| `lewislulu/html-ppt-skill` | The HTML PPT Studio family — 15 deck templates, 36 themes, 31 page layouts, animation runtime, magnetic-card presenter mode. |\n| `OpenCoworkAI/open-codesign` | The first open-source Claude Design alternative; UX patterns we borrow (streaming-artifact loop, sandboxed iframe, live agent panel). |\n| `multica-ai/multica` | The daemon + adapter architecture — PATH-scan agent detection, local daemon as the only privileged process. |\n| `VoltAgent/awesome-design-md` | Historical source of the original 9-section `DESIGN.md` schema and 70 upstream-derived systems; current packages may extend that baseline. |\n| `bergside/awesome-design-skills` | Source of the 57 design skills added under `design-systems/`. |\n| `heygen-com/hyperframes` | The HTML→MP4 motion-graphics framework, integrated as the first-class `hyperframes-html` in Open Design. |\n| Claude Code skills | The `SKILL.md` convention we adopt verbatim. |\n\nDetailed provenance → [`docs/references.md`](https://github.com/nexu-io/open-design/blob/main/docs/references.md).\n\n\n\n## License\n\nApache-2.0. Bundled skills and templates with their own `LICENSE` files retain those licenses, including `design-templates/guizang-ppt/` (MIT, [@op7418](https://github.com/op7418)), `design-templates/html-ppt/` (MIT, [@lewislulu](https://github.com/lewislulu)), and `skills/web-clone/` (MIT, [@Jane-xiaoer](https://github.com/Jane-xiaoer))."},"author":{"name":"nexu-io","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/acb9ab7e19be520d/avatar-6a9577cd4f7f.svg","bio":"🎨 The open-source Claude Design alternative. 🖥️ Local-first desktop app. 🖼️ Your coding agent becomes the design engine: prototypes, landing pages, dashboards, slides, images & video — real fil..."},"metadata":{"timestamp":"2026-08-06T14:58:14.516Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/DeFTjf0yb9/media/0.png","type":"image","width":1200,"height":600}],"aiComments":[]},{"id":"web-vwbztq","shareId":"Ty9DrBBoVr","platform":"web","url":"https://github.com/responsively-org/responsively-app","title":"responsively-org/responsively-app: A modified web browser that helps in responsive web development. A web developer's must have dev-tool.","shareMode":"full","createdAt":1786028299289,"postedAt":"2026-08-06T14:58:07.008Z","publishedDate":"2026-08-06T14:58:07.008Z","archivedAt":"2026-08-06T14:58:10.663Z","archivedDate":"2026-08-06T14:58:10.663Z","viewCount":1,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/Ty9DrBBoVr","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/QW1yx63km5/media/0.png","contentType":"article","content":{"text":"[![Responsively Logo](https://camo.githubusercontent.com/0fefc998ce975f9a3fce39c4f79be20032d80b2aaba0a3df750c3fe9e24288ce/68747470733a2f2f726573706f6e736976656c792e6170702f6173736574732f696d672f6c6f676f2e706e67)](https://camo.githubusercontent.com/0fefc998ce975f9a3fce39c4f79be20032d80b2aaba0a3df750c3fe9e24288ce/68747470733a2f2f726573706f6e736976656c792e6170702f6173736574732f696d672f6c6f676f2e706e67)\n\n## Responsively App\n\n**A must-have dev tool for web developers for quicker responsive web development. 🚀**\n\n###### Save time by becoming 5x faster!\n\n\n[![Twitter](https://camo.githubusercontent.com/81d7c738a74191adc5c66e53a65423e4b1159a6cba2ca555387250259b7344cd/68747470733a2f2f696d672e736869656c64732e696f2f747769747465722f666f6c6c6f772f726573706f6e736976656c794170703f636f6c6f723d323641304544266c6162656c3d466f6c6c6f77266c6f676f3d74776974746572266c6f676f436f6c6f723d7768697465267374796c653d666c6174)](https://x.com/ResponsivelyApp) [![contributors](https://camo.githubusercontent.com/2914a2077a50035911d4061dbf1c2690f8a66dca3341b161a4e9d85c8694c377/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f616c6c2d636f6e7472696275746f72732f726573706f6e736976656c792d6f72672f726573706f6e736976656c792d6170703f7374796c653d666c6174)](#contributors-) [![Discord](https://camo.githubusercontent.com/6f5d7926a78a8546a35fe376ee99410b609eb0308ae2f6318a2fb94dfa96b5e7/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f4a6f696e2532302d446973636f72642d626c75653f6c6f676f3d646973636f7264266c6f676f436f6c6f723d7768697465)](https://responsively.app/join-discord) [![XS:Code](https://camo.githubusercontent.com/bf995d4f9bab7011cc7895c5c27519dca9022c8e0460233905a7511d48af7a2d/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f417661696c61626c652532306f6e2d7873253341636f64652d626c75653f7374796c653d3f7374796c653d666c6174266c6f676f3d6170707665796f72266c6f676f3d646174613a696d6167652f706e673b6261736536342c6956424f5277304b47676f414141414e5355684555674141414541414141424143414d41414143647434487341414141475852465748525462325a30643246795a5142425a4739695a53424a6257466e5a564a6c5957523563636c6c5041414141415a51544652462f2f2f2f2f2f2f2f56587a316241414141414a30556b35542f77446c747a424b414141416c556c455156523432757a58537771414d417745304d6e394c2b33476774676b6b33355177636e534a6f39532b7947774d3944436f6f4362676e3459724a3443495055635146372f58534262783254457a3473415a3271315241454342416959426c437476774e2b4b6959416c47375544476a35394d56695439684f77457141685943744173555a764c36493657386332776362642b4c495753434853546553414145436e674e3478784944534b39663442397433373757643748354e74372f587a3865416777417665734c526a595950755541414141415355564f524b35435949493d)](https://xscode.com/manojvivek/responsively-app) [![PRs Welcome](https://camo.githubusercontent.com/7d9ed3c8f22eceb1711573169b1390cc0b1194467340dc815205060c162b5309/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f5052732d77656c636f6d652d627269676874677265656e2e7376673f7374796c653d666c6174)](https://github.com/responsively-org/responsively-app/issues)\n\n[![ProductHunt](https://camo.githubusercontent.com/a6dff16436dc55a2a9f1e4fa2bbedb14ee696398fc5e1bb7f4a9ed6f37eefa35/68747470733a2f2f6170692e70726f6475637468756e742e636f6d2f776964676574732f656d6265642d696d6167652f76312f746f702d706f73742d62616467652e7376673f706f73745f69643d323030333735267468656d653d6c6967687426706572696f643d6461696c79)](https://www.producthunt.com/posts/responsively?utm_source=badge-top-post-badge&utm_medium=badge&utm_souce=badge-responsively)\n\nDownload Now (free!): [responsively.app](https://responsively.app/download)\n\n\n\n## Responsively App\n\n\n\n> A modified browser built using [Electron](https://www.electronjs.org/) that helps in responsive web development.\n\n[![Quick Demo](https://camo.githubusercontent.com/978fd9c182f7fde1a0f00e4daa65ec0799588da03aee781bff81e14b3fe45714/68747470733a2f2f726573706f6e736976656c792e6170702f6173736574732f696d672f726573706f6e736976656c792d6170702e676966)](https://camo.githubusercontent.com/978fd9c182f7fde1a0f00e4daa65ec0799588da03aee781bff81e14b3fe45714/68747470733a2f2f726573706f6e736976656c792e6170702f6173736574732f696d672f726573706f6e736976656c792d6170702e676966)\n\n\n\n## Features\n\n1. Mirrored User-interactions across all devices.\n2. Customizable preview layout to suit all your needs.\n3. One handy elements inspector for all devices in preview.\n4. 30+ built-in device profiles with the option to add custom devices.\n5. One-click screenshots on all your devices.\n6. Hot reloading is supported for developers. Please visit the website to learn more about the application - [https://responsively.app](https://responsively.app/)\n\n\n\n## Download\n\nThe application is available for Mac, Windows and Linux platforms. Please [download it from responsively.app](https://responsively.app/download)\n\nAlternatively, MacOS users can use [`brew`](https://formulae.brew.sh/cask/responsively) [![Homebrew installs](https://camo.githubusercontent.com/9e983c3856e747f82794d8ca947900be687c0f4ce0cfecd3b0a48f051552469d/68747470733a2f2f62616467656e2e6e65742f686f6d65627265772f6361736b2f64792f726573706f6e736976656c79)](https://formulae.brew.sh/cask/responsively)\n\n\n\n```\nbrew install --cask responsively\n```\n\nAlso, Windows users can use [`chocolatey`](https://chocolatey.org/packages/responsively/) [![Chocolatey installs](https://camo.githubusercontent.com/c60a34bfbe006b61c054114a652fe55ccb9b0cb666e00faa82d5aaf7e698baa6/68747470733a2f2f696d672e736869656c64732e696f2f63686f636f6c617465792f64742f726573706f6e736976656c79)](https://chocolatey.org/packages/responsively/)\n\n\n\n```\nchoco install responsively\n```\n\nor [`winget`](https://github.com/microsoft/winget-cli):\n\n\n\n```\nwinget install ResponsivelyApp\n```\n\nLinux users using an RPM Package Manager can use `rpm`\n\n\n\n```\nsudo rpm -i https://github.com/responsively-org/responsively-app/releases/download/v[VERSION]/Responsively-App-[VERSION].x86_64.rpm\n```\n\notherwise, download an AppImage from [the releases page](https://github.com/responsively-org/responsively-app/releases)\n\nFollow us on Twitter for future updates - [![Twitter Follow](https://camo.githubusercontent.com/321513dde13e54936bd657265a87f56ff6d7f55f10c82e4470f8b661a32fabb7/68747470733a2f2f696d672e736869656c64732e696f2f747769747465722f666f6c6c6f772f526573706f6e736976656c794170703f7374796c653d736f6369616c)](https://x.com/ResponsivelyApp)\n\n\n\n## Browser Extension\n\nInstall the handy browser extension to easily send links from your browser to the app and preview instantly.\n\n- [Download for Chrome](https://chrome.google.com/webstore/detail/responsively-helper/jhphiidjkooiaollfiknkokgodbaddcj) [![Chrome Web Store](https://camo.githubusercontent.com/fbac267fe6b29374e7efc8131f4357e27e12c4bec2a0b5196470a75fd3c999db/68747470733a2f2f696d672e736869656c64732e696f2f6368726f6d652d7765622d73746f72652f75736572732f6a6870686969646a6b6f6f69616f6c6c66696b6e6b6f6b676f6462616464636a3f636f6c6f723d626c7565)](https://chrome.google.com/webstore/detail/responsively-helper/jhphiidjkooiaollfiknkokgodbaddcj)\n- [Download for Firefox](https://addons.mozilla.org/en-US/firefox/addon/responsively-helper/) [![Mozilla Add-on](https://camo.githubusercontent.com/1421bcf96e4fc309f32c344dc698160226b015848e382ba2362910b8abf90424/68747470733a2f2f696d672e736869656c64732e696f2f616d6f2f75736572732f726573706f6e736976656c792d68656c706572)](https://addons.mozilla.org/en-US/firefox/addon/responsively-helper/)\n- [Download for Edge](https://microsoftedge.microsoft.com/addons/detail/responsively-helper/ooiejjgflcgkbbehheengalibfehaojn) [![Edge Add-on](https://camo.githubusercontent.com/7113eaaea9b157941638e58b0bbeaedd62ea2539f7f8c0bf9623b46f5f6d8a49/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f64796e616d69632f6a736f6e3f6c6162656c3d75736572732671756572793d2532342e616374697665496e7374616c6c436f756e742675726c3d68747470732533412532462532466d6963726f736f6674656467652e6d6963726f736f66742e636f6d2532466164646f6e7325324667657470726f6475637464657461696c73627963727869642532466f6f69656a6a67666c63676b626265686865656e67616c6962666568616f6a6e)](https://microsoftedge.microsoft.com/addons/detail/responsively-helper/ooiejjgflcgkbbehheengalibfehaojn)\n\n## Issues\n\nIf you face any problems while using the application, please open an issue here - [https://github.com/responsively-org/responsively-app/issues](https://github.com/responsively-org/responsively-app/issues)\n\n\n\n## Roadmap\n\nHere is the roadmap of the desktop app - [https://github.com/responsively-org/responsively-app/projects/](https://github.com/responsively-org/responsively-app/projects/)\n\n\n\n## Gold sponsors 🥇\n\n\n\n## Contribute\n\nTo get started with contributing your awesome ideas to Responsively, follow the [comprehensive guide here](https://github.com/responsively-org/responsively-app/blob/main/CONTRIBUTING.md)!\n\n\n\n## Get in touch\n\nCome say hi to us on [Discord](https://responsively.app/join-discord)! 👋\n\n\n\n## Contributors ✨\n\nThanks go to these wonderful people ([emoji key](https://allcontributors.org/docs/en/emoji-key)):\n\n\n\n| ![Manoj Vivek](https://avatars1.githubusercontent.com/u/1283424?v=4?s=100) **Manoj Vivek** 💻 ⚠️ 📆 | ![Suresh P](https://avatars0.githubusercontent.com/u/26249498?v=4?s=100) **Suresh P** 💻 ⚠️ 📆 | ![Sigit Prabowo](https://avatars2.githubusercontent.com/u/11748183?v=4?s=100) **Sigit Prabowo** 💻 | ![Leon Feng](https://avatars1.githubusercontent.com/u/523684?v=4?s=100) **Leon Feng** 📖 | ![Kishore S](https://avatars2.githubusercontent.com/u/30261988?v=4?s=100) **Kishore S** 💻 |\n| --- | --- | --- | --- | --- |\n| ![José Javier Rodríguez Zas](https://avatars2.githubusercontent.com/u/13673443?v=4?s=100) **José Javier Rodríguez Zas** 💻 ⚠️ | ![Roman Akash](https://avatars1.githubusercontent.com/u/40427975?v=4?s=100) **Roman Akash** 💻 | ![Romain Francony](https://avatars3.githubusercontent.com/u/22396965?v=4?s=100) **Romain Francony** 💻 | ![AARYAN-MAHENDRA](https://avatars1.githubusercontent.com/u/64866670?v=4?s=100) **AARYAN-MAHENDRA** 💻 | ![Andy](https://avatars3.githubusercontent.com/u/18606648?v=4?s=100) **Andy** 💻 |\n| ![Ryan Pais](https://avatars0.githubusercontent.com/u/15522605?v=4?s=100) **Ryan Pais** 💻 ⚠️ | ![Jonathan](https://avatars1.githubusercontent.com/u/395137?v=4?s=100) **Jonathan** 💻 | ![Gema Anggada ✌︎](https://avatars1.githubusercontent.com/u/10743728?v=4?s=100) **Gema Anggada ✌︎** 💻 | ![jonathanurias96](https://avatars2.githubusercontent.com/u/57416786?v=4?s=100) **jonathanurias96** 💻 | ![Federico Alecci](https://avatars2.githubusercontent.com/u/17703824?v=4?s=100) **Federico Alecci** 💻 |\n| ![Abduraimov Muminjon](https://avatars1.githubusercontent.com/u/24930020?v=4?s=100) **Abduraimov Muminjon** 📖 | ![Víctor Lázaro](https://avatars1.githubusercontent.com/u/38981659?v=4?s=100) **Víctor Lázaro** 💻 | ![Kavita Nambissan](https://avatars0.githubusercontent.com/u/3608742?v=4?s=100) **Kavita Nambissan** 💻 | ![Prashant Palikhe](https://avatars0.githubusercontent.com/u/2657709?v=4?s=100) **Prashant Palikhe** 💻 | ![Jaune Sarmiento](https://avatars1.githubusercontent.com/u/1166928?v=4?s=100) **Jaune Sarmiento** 🖋 |\n| ![Diego Vieira](https://avatars2.githubusercontent.com/u/930792?v=4?s=100) **Diego Vieira** 💻 | ![Ajaykumar](https://avatars0.githubusercontent.com/u/21375014?v=4?s=100) **Ajaykumar** 💻 | ![Kiruba Karan](https://avatars0.githubusercontent.com/u/38885946?v=4?s=100) **Kiruba Karan** 💻 | ![Sebastián Rodríguez](https://avatars1.githubusercontent.com/u/1605931?v=4?s=100) **Sebastián Rodríguez** 💻 | ![Karthick Raja](https://avatars1.githubusercontent.com/u/47154512?v=4?s=100) **Karthick Raja** 💻 |\n| ![Johnny Zabala](https://avatars0.githubusercontent.com/u/1315054?v=4?s=100) **Johnny Zabala** 💻 | ![Ross Moody](https://avatars0.githubusercontent.com/u/29072694?v=4?s=100) **Ross Moody** 🎨 | ![Mehrdad Shokri](https://avatars1.githubusercontent.com/u/13661520?v=4?s=100) **Mehrdad Shokri** 🚇 | ![Abdelhak Akermi](https://avatars1.githubusercontent.com/u/60294727?v=4?s=100) **Abdelhak Akermi** 💻 | ![Carlos Perez](https://avatars0.githubusercontent.com/u/20329014?v=4?s=100) **Carlos Perez** 💻 |\n| ![Jayant Arya](https://avatars0.githubusercontent.com/u/42388314?v=4?s=100) **Jayant Arya** 💻 | ![John Rawlins](https://avatars3.githubusercontent.com/u/42707277?v=4?s=100) **John Rawlins** 💻 | ![lepasq](https://avatars3.githubusercontent.com/u/53230128?v=4?s=100) **lepasq** 💻 | ![mrfelfel](https://avatars0.githubusercontent.com/u/19575588?v=4?s=100) **mrfelfel** 💻 | ![gorogoroumaru](https://avatars3.githubusercontent.com/u/30716350?v=4?s=100) **gorogoroumaru** 💻 |\n| ![Rui Saraiva](https://avatars2.githubusercontent.com/u/7356098?v=4?s=100) **Rui Saraiva** 💻 | ![Mehmet Bakirci](https://avatars2.githubusercontent.com/u/9880089?v=4?s=100) **Mehmet Bakirci** 💻 | ![Julien Bertazzo Lambert](https://avatars0.githubusercontent.com/u/42924425?v=4?s=100) **Julien Bertazzo Lambert** 💻 | ![Dinesh Balaji](https://avatars3.githubusercontent.com/u/4656109?v=4?s=100) **Dinesh Balaji** 💻 | ![MedBMoussa](https://avatars3.githubusercontent.com/u/26111211?v=4?s=100) **MedBMoussa** 💻 |\n| ![Lucie Vrsovska](https://avatars.githubusercontent.com/u/46979603?v=4?s=100) **Lucie Vrsovska** 💻 | ![Jakub Cabak](https://avatars.githubusercontent.com/u/1818155?v=4?s=100) **Jakub Cabak** 💻 | ![Palakurthi Durga Kiran Kumar](https://avatars.githubusercontent.com/u/17452039?v=4?s=100) **Palakurthi Durga Kiran Kumar** 💻 | ![Karl Labrador](https://avatars.githubusercontent.com/u/58193703?v=4?s=100) **Karl Labrador** 💻 | ![Rishi Kumar Chawda](https://avatars.githubusercontent.com/u/26366288?v=4?s=100) **Rishi Kumar Chawda** 💻 |\n| ![Carlos Rafael de Oliveira Carneiro](https://avatars.githubusercontent.com/u/10589421?v=4?s=100) **Carlos Rafael de Oliveira Carneiro** 💻 | ![Zach Hoskins](https://avatars.githubusercontent.com/u/50255197?v=4?s=100) **Zach Hoskins** 💻 | ![KIWAN KIM](https://avatars.githubusercontent.com/u/25267859?v=4?s=100) **KIWAN KIM** 💻 | ![Andreas](https://avatars.githubusercontent.com/u/13819164?v=4?s=100) **Andreas** 💻 | ![Panu Valtanen](https://avatars.githubusercontent.com/u/28947061?v=4?s=100) **Panu Valtanen** 💻 |\n| ![Dustin Dauncey](https://avatars.githubusercontent.com/u/8153796?v=4?s=100) **Dustin Dauncey** 💻 | ![heagan01](https://avatars.githubusercontent.com/u/54394590?v=4?s=100) **heagan01** 💻 | ![Sahil Jangra](https://avatars.githubusercontent.com/u/74812563?v=4?s=100) **Sahil Jangra** 💻 | ![Jay Carlson](https://avatars.githubusercontent.com/u/1357866?v=4?s=100) **Jay Carlson** 💻 | ![Michael Padilla](https://avatars.githubusercontent.com/u/51935560?v=4?s=100) **Michael Padilla** 💻 |\n| ![Andreas Steinkellner](https://avatars.githubusercontent.com/u/6213380?v=4?s=100) **Andreas Steinkellner** 💻 | ![aniknia](https://avatars.githubusercontent.com/u/40159649?v=4?s=100) **aniknia** 💻 | ![Wayne Rocha](https://avatars.githubusercontent.com/u/62760711?v=4?s=100) **Wayne Rocha** 💻 | ![crbon](https://avatars.githubusercontent.com/u/2604330?v=4?s=100) **crbon** 💻 | ![Mohammad S](https://avatars.githubusercontent.com/u/59393936?v=4?s=100) **Mohammad S** 💻 |\n| ![Reshad Sadik](https://avatars.githubusercontent.com/u/66641469?v=4?s=100) **Reshad Sadik** 💻 | ![Kwesi Ansah](https://avatars.githubusercontent.com/u/31078314?v=4?s=100) **Kwesi Ansah** 💻 | ![Monalisa Sahoo](https://avatars.githubusercontent.com/u/65477771?v=4?s=100) **Monalisa Sahoo** 💻 | ![Mitesh Tank](https://avatars.githubusercontent.com/u/85953650?v=4?s=100) **Mitesh Tank** 💻 | ![Ryan](https://avatars.githubusercontent.com/u/82715592?v=4?s=100) **Ryan** 💻 |\n| ![jayway](https://avatars.githubusercontent.com/u/70596906?v=4?s=100) **jayway** 💻 | ![Alex Fernandez](https://avatars.githubusercontent.com/u/3981106?v=4?s=100) **Alex Fernandez** 💻 | ![Danial Gharib](https://avatars.githubusercontent.com/u/90343552?v=4?s=100) **Danial Gharib** 💻 | ![Alexander Menk](https://avatars.githubusercontent.com/u/1087128?v=4?s=100) **Alexander Menk** 📖 | ![Tunahan Gediz](https://avatars.githubusercontent.com/u/75015671?v=4?s=100) **Tunahan Gediz** 📖 |\n| ![Jeff Bowen](https://avatars.githubusercontent.com/u/272795?v=4?s=100) **Jeff Bowen** 💻 | ![Param Birje](https://avatars.githubusercontent.com/u/87022870?v=4?s=100) **Param Birje** 💻 | ![Prajjwal Yadav](https://avatars.githubusercontent.com/u/111794524?v=4?s=100) **Prajjwal Yadav** 📖 | ![Steven Cabrera](https://avatars.githubusercontent.com/u/49458912?v=4?s=100) **Steven Cabrera** 💻 | ![negar nasiri](https://avatars.githubusercontent.com/u/113235504?v=4?s=100) **negar nasiri** 💻 |\n| ![Gaurav Singh](https://avatars.githubusercontent.com/u/99260988?v=4?s=100) **Gaurav Singh** 💻 | ![Nishidh Jain](https://avatars.githubusercontent.com/u/61869195?v=4?s=100) **Nishidh Jain** 💻 | ![Samiksha Mishra](https://avatars.githubusercontent.com/u/38784342?v=4?s=100) **Samiksha Mishra** 📖 | ![Len Dierickx](https://avatars.githubusercontent.com/u/1730624?v=4?s=100) **Len Dierickx** 💻 | ![Suraj Bobade](https://avatars.githubusercontent.com/u/102910293?v=4?s=100) **Suraj Bobade** 💻 |\n| ![Sagar Hedaoo](https://avatars.githubusercontent.com/u/10000167?v=4?s=100) **Sagar Hedaoo** 💻 | ![V](https://avatars.githubusercontent.com/u/36138541?v=4?s=100) **V** 💻 ⚠️ | ![Prabhas Jupalli](https://avatars.githubusercontent.com/u/139740712?v=4?s=100) **Prabhas Jupalli** 💻 | ![Pulkit](https://avatars.githubusercontent.com/u/65671483?v=4?s=100) **Pulkit** 💻 | ![Brandon Yee](https://avatars.githubusercontent.com/u/139765638?v=4?s=100) **Brandon Yee** 🖋 |\n| ![Wendy Pan](https://avatars.githubusercontent.com/u/110360465?v=4?s=100) **Wendy Pan** 💻 | ![Pranav Ithape](https://avatars.githubusercontent.com/u/170559714?v=4?s=100) **Pranav Ithape** 💻 | ![SUKRIT PRAKASH SINGH](https://avatars.githubusercontent.com/u/136228545?v=4?s=100) **SUKRIT PRAKASH SINGH** 💻 | ![Aryan Panchal](https://avatars.githubusercontent.com/u/97938438?v=4?s=100) **Aryan Panchal** 💻 | ![Samran Ahmed](https://avatars.githubusercontent.com/u/149153498?v=4?s=100) **Samran Ahmed** 💻 |\n| ![SatyamAgrawal](https://avatars.githubusercontent.com/u/95954551?v=4?s=100) **SatyamAgrawal** 💻 | ![Sai Tharun Dusa](https://avatars.githubusercontent.com/u/169873642?v=4?s=100) **Sai Tharun Dusa** 💻 | ![Pavlo](https://avatars.githubusercontent.com/u/179954458?v=4?s=100) **Pavlo** 💻 ⚠️ | ![AnalyticalDataArtisan](https://avatars.githubusercontent.com/u/183036785?v=4?s=100) **AnalyticalDataArtisan** 💻 | ![Kieren-Foenander](https://avatars.githubusercontent.com/u/68266113?v=4?s=100) **Kieren-Foenander** 💻 |\n| ![Trishit Swarnakar](https://avatars.githubusercontent.com/u/170200412?v=4?s=100) **Trishit Swarnakar** 💻 | ![Abhijeet Singh](https://avatars.githubusercontent.com/u/29686866?v=4?s=100) **Abhijeet Singh** 📖 | ![aaryan](https://avatars.githubusercontent.com/u/93996658?v=4?s=100) **aaryan** 💻 | ![Michael Klikushin](https://avatars.githubusercontent.com/u/135151016?v=4?s=100) **Michael Klikushin** 💻 | ![Bhanu Prakash](https://avatars.githubusercontent.com/u/48930756?v=4?s=100) **Bhanu Prakash** 💻 |\n| ![Saúl Sáyago](https://avatars.githubusercontent.com/u/67727553?v=4?s=100) **Saúl Sáyago** 💻 | ![Dailin](https://avatars.githubusercontent.com/u/71995555?v=4?s=100) **Dailin** 💻 |\n\nThis project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind are welcome!"},"author":{"name":"responsively-org","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/76c65a388b9d299d/avatar-6a9577cd4f7f.svg","bio":"A modified web browser that helps in responsive web development. A web developer's must have dev-tool. - responsively-org/responsively-app"},"metadata":{"timestamp":"2026-08-06T14:58:07.008Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/QW1yx63km5/media/0.png","type":"image","width":1280,"height":640}],"aiComments":[]},{"id":"web-44c296","shareId":"3bZdEZuvtX","platform":"web","url":"https://medium.com/@esimov/2d-cloth-simulation-in-go-using-gio-gui-b3dfe00b7223","title":"Attention Required!","shareMode":"full","createdAt":1786028201601,"postedAt":"2026-08-06T14:56:35.080Z","publishedDate":"2026-08-06T14:56:35.080Z","archivedAt":"2026-08-06T14:56:37.089Z","archivedDate":"2026-08-06T14:56:37.089Z","viewCount":2,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/3bZdEZuvtX","contentType":"article","content":{"text":"## Sorry, you have been blocked\n\n## You are unable to access medium.com\n\n## Why have I been blocked?\n\nThis website is using a security service to protect itself from online attacks. The action you just performed triggered the security solution. There are several actions that could trigger this block including submitting a certain word or phrase, a SQL command or malformed data.\n\n## What can I do to resolve this?\n\nYou can email the site owner to let them know you were blocked. Please include what you were doing when this page came up and the Cloudflare Ray ID found at the bottom of this page."},"author":{"name":"medium.com"},"metadata":{"timestamp":"2026-08-06T14:56:35.080Z"},"media":[],"aiComments":[]},{"id":"web-g1oyk","shareId":"kQcq6W95VR","platform":"web","url":"https://github.com/postlight/mercury-parser","title":"postlight/parser: 📜 Extract meaningful content from the chaos of a web page","shareMode":"full","createdAt":1786027545585,"postedAt":"2026-08-06T14:45:35.430Z","publishedDate":"2026-08-06T14:45:35.430Z","archivedAt":"2026-08-06T14:45:39.046Z","archivedDate":"2026-08-06T14:45:39.046Z","viewCount":1,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/kQcq6W95VR","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/QjfX1bNw8J/media/0.png","contentType":"article","content":{"text":"## Postlight Parser - Extracting content from chaos\n\n[![CircleCI](https://camo.githubusercontent.com/9f7d2da2c76ab7f2afaa5a0b8850b3728f45a93f3a8d59d89707116663fb56f2/68747470733a2f2f636972636c6563692e636f6d2f67682f706f73746c696768742f7061727365722e7376673f7374796c653d73766726636972636c652d746f6b656e3d33303236633262353237643337363737353065373637383732643038393931616562346638663130)](https://circleci.com/gh/postlight/mercury-parser) [![Greenkeeper badge](https://camo.githubusercontent.com/2f13c171cbe9902c792f4e8809c24d62f3c4aeaef944f086ceab52a79db4dbdc/68747470733a2f2f6261646765732e677265656e6b65657065722e696f2f706f73746c696768742f6d6572637572792d7061727365722e737667)](https://greenkeeper.io/) [![Apache License](https://camo.githubusercontent.com/753b222389d983713c05b305cd5ba4a064fcbe8dc060e90da88b74ee0401340a/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f4c6963656e73652d417061636865253230322e302d626c75652e7376673f7374796c653d666c61742d737175617265)](https://github.com/postlight/mercury-parser/blob/master/LICENSE-APACHE) [![MITC License](https://camo.githubusercontent.com/7cbe23ce33112919acc72b72214b94731f5f91912e68dbd1cf1446f0ef63a846/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f4c6963656e73652d4d4954253230322e302d626c75652e7376673f7374796c653d666c61742d737175617265)](https://github.com/postlight/mercury-parser/blob/master/LICENSE-MIT) [![Gitter chat](https://camo.githubusercontent.com/9fac294d3950e751e47ae5c9ec67662626b2e45fd093b08b98c7f950e4a3cb91/68747470733a2f2f6261646765732e6769747465722e696d2f706f73746c696768742f6d6572637572792e706e67)](https://gitter.im/postlight/mercury)\n\n[Postlight](https://postlight.com/) 's Parser extracts the bits that humans care about from any URL you give it. That includes article content, titles, authors, published dates, excerpts, lead images, and more.\n\nPostlight Parser powers [Postlight Reader](https://reader.postlight.com/), a browser extension that removes ads and distractions, leaving only text and images for a beautiful reading view on any site.\n\nPostlight Parser allows you to easily create custom parsers using simple JavaScript and CSS selectors. This allows you to proactively manage parsing and migration edge cases. There are [many examples available](https://github.com/postlight/parser/tree/master/src/extractors/custom) along with [documentation](https://github.com/postlight/parser/blob/master/src/extractors/custom/README.md).\n\n\n\n## How? Like this.\n\n\n\n### Installation\n\n\n\n```\n# If you're using yarn\nyarn add @postlight/parser\n\n# If you're using npm\nnpm install @postlight/parser\n```\n\n\n\n### Usage\n\n\n\n```\nimport Parser from '@postlight/parser';\n\nParser.parse(url).then(result => console.log(result));\n\n// NOTE: When used in the browser, you can omit the URL argument\n// and simply run `Parser.parse()` to parse the current page.\n```\n\nThe result looks like this:\n\n\n\n```\n{\n\"title\": \"Thunder (mascot)\",\n\"content\": \"... **Thunder** is the stage name for the...\",\n\"author\": \"Wikipedia Contributors\",\n\"date_published\": \"2016-09-16T20:56:00.000Z\",\n\"lead_image_url\": null,\n\"dek\": null,\n\"next_page_url\": null,\n\"url\": \"https://en.wikipedia.org/wiki/Thunder_(mascot)\",\n\"domain\": \"en.wikipedia.org\",\n\"excerpt\": \"Thunder Thunder is the stage name for the horse who is the official live animal mascot for the Denver Broncos\",\n\"word_count\": 4677,\n\"direction\": \"ltr\",\n\"total_pages\": 1,\n\"rendered_pages\": 1\n}\n```\n\nIf Parser is unable to find a field, that field will return `null`.\n\n\n\n#### parse() Options\n\n\n\n##### Content Formats\n\nBy default, Postlight Parser returns the `content` field as HTML. However, you can override this behavior by passing in options to the `parse` function, specifying whether or not to scrape all pages of an article, and what type of output to return (valid values are `'html'`, `'markdown'`, and `'text'`). For example:\n\n\n\n```\nParser.parse(url, { contentType: 'markdown' }).then(result =>\nconsole.log(result)\n);\n```\n\nThis returns the the page's `content` as GitHub-flavored Markdown:\n\n\n\n```\n\"content\": \"...**Thunder** is the [stage name](https://en.wikipedia.org/wiki/Stage_name) for the...\"\n```\n\n\n\n##### Custom Request Headers\n\nYou can include custom headers in requests by passing name-value pairs to the `parse` function as follows:\n\n\n\n```\nParser.parse(url, {\nheaders: {\nCookie: 'name=value; name2=value2; name3=value3',\n'User-Agent':\n'Mozilla/5.0 (iPhone; CPU iPhone OS 10_3_1 like Mac OS X) AppleWebKit/603.1.30 (KHTML, like Gecko) Version/10.0 Mobile/14E304 Safari/602.1',\n},\n}).then(result => console.log(result));\n```\n\n\n\n##### Pre-fetched HTML\n\nYou can use Postlight Parser to parse custom or pre-fetched HTML by passing an HTML string to the `parse` function as follows:\n\n\n\n```\nParser.parse(url, {\nhtml:\n'Thunder (mascot)Thunder is the stage name for the horse who is the official live animal mascot for the Denver Broncos\n\n',\n}).then(result => console.log(result));\n```\n\nNote that the URL argument is still supplied, in order to identify the web site and use its custom parser, if it has any, though it will not be used for fetching content.\n\n\n\n#### The command-line parser\n\nPostlight Parser also ships with a CLI, meaning you can use it from your command line like so:\n\n[![Postlight Parser CLI Basic Usage](https://github.com/postlight/parser/raw/main/assets/parser-basic-usage.gif)](https://github.com/postlight/parser/blob/main/assets/parser-basic-usage.gif)\n\n\n\n```\n# Install Postlight Parser globally\nyarn global add @postlight/parser\n# or\nnpm -g install @postlight/parser\n\n# Then\npostlight-parser https://postlight.com/trackchanges/mercury-goes-open-source\n\n# Pass optional --format argument to set content type (html|markdown|text)\npostlight-parser https://postlight.com/trackchanges/mercury-goes-open-source --format=markdown\n\n# Pass optional --header.name=value arguments to include custom headers in the request\npostlight-parser https://postlight.com/trackchanges/mercury-goes-open-source --header.Cookie=\"name=value; name2=value2; name3=value3\" --header.User-Agent=\"Mozilla/5.0 (iPhone; CPU iPhone OS 10_3_1 like Mac OS X) AppleWebKit/603.1.30 (KHTML, like Gecko) Version/10.0 Mobile/14E304 Safari/602.1\"\n\n# Pass optional --extend argument to add a custom type to the response\npostlight-parser https://postlight.com/trackchanges/mercury-goes-open-source --extend credit=\"p:last-child em\"\n\n# Pass optional --extend-list argument to add a custom type with multiple matches\npostlight-parser https://postlight.com/trackchanges/mercury-goes-open-source --extend-list categories=\".meta__tags-list a\"\n\n# Get the value of attributes by adding a pipe to --extend or --extend-list\npostlight-parser https://postlight.com/trackchanges/mercury-goes-open-source --extend-list links=\".body a|href\"\n\n# Pass optional --add-extractor argument to add a custom extractor at runtime.\npostlight-parser https://postlight.com/trackchanges/mercury-goes-open-source --add-extractor ./src/extractors/fixtures/postlight.com/index.js\n```\n\n\n\n## License\n\nLicensed under either of the below, at your preference:\n\n- Apache License, Version 2.0 ([LICENSE-APACHE](https://github.com/postlight/parser/blob/main/LICENSE-APACHE) or [http://www.apache.org/licenses/LICENSE-2.0](http://www.apache.org/licenses/LICENSE-2.0))\n- MIT license ([LICENSE-MIT](https://github.com/postlight/parser/blob/main/LICENSE-MIT) or [http://opensource.org/licenses/MIT](http://opensource.org/licenses/MIT))\n\n## Contributing\n\nFor details on how to contribute to Postlight Parser, including how to write a custom content extractor for any site, see [CONTRIBUTING.md](https://github.com/postlight/parser/blob/main/CONTRIBUTING.md)\n\nUnless it is explicitly stated otherwise, any contribution intentionally submitted for inclusion in the work, as defined in the Apache-2.0 license, shall be dual licensed as above without any additional terms or conditions.\n\n\n\n---\n\n🔬 A Labs project from your friends at [Postlight](https://postlight.com/). Happy coding!"},"author":{"name":"postlight","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/7aa3a023cbcb954c/avatar-6a9577cd4f7f.svg","bio":"📜 Extract meaningful content from the chaos of a web page - postlight/parser"},"metadata":{"timestamp":"2026-08-06T14:45:35.430Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/QjfX1bNw8J/media/0.png","type":"image","width":1200,"height":628}],"aiComments":[]},{"id":"web-pp0yp8","shareId":"yDFRa3TM23","platform":"web","url":"https://www.underwritex.com/#pricing","title":"UnderwriteX - AI Real Estate Underwriting | Analyze Deals in Seconds","shareMode":"full","createdAt":1786024729467,"postedAt":"2026-08-06T13:58:41.976Z","publishedDate":"2026-08-06T13:58:41.976Z","archivedAt":"2026-08-06T13:58:43.934Z","archivedDate":"2026-08-06T13:58:43.934Z","viewCount":0,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/yDFRa3TM23","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/OxqreyB9Vg/media/0.png","contentType":"article","content":{"text":" "},"author":{"name":"UnderwriteX","bio":"Transform your real estate analysis with AI-powered underwriting. Get accurate property valuations and investment insights in seconds."},"metadata":{"timestamp":"2026-08-06T13:58:41.976Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/OxqreyB9Vg/media/0.png","type":"image","width":1200,"height":640}],"aiComments":[]},{"id":"ai-agent-ownership","shareId":"WAiFmpVNh0","platform":"substack","url":"https://natesnewsletter.substack.com/p/ai-agent-ownership","title":"Executive Briefing: Your team is running agents nobody owns. The one-page card and two prompts that fix it.","shareMode":"full","createdAt":1785995065990,"postedAt":"2026-08-06T05:44:19.688Z","publishedDate":"2026-08-06T05:44:19.688Z","archivedAt":"2026-08-06T05:44:21.138Z","archivedDate":"2026-08-06T05:44:21.138Z","viewCount":2,"ownerUsername":"arc","canonicalUrl":"https://social-archive.org/arc/WAiFmpVNh0","thumbnail":"https://social-archiver-api.social-archive.org/media/archives/arc/Bcvfwy0Nnv/media/0.jpg","contentType":"article","content":{"text":"Watch now | I have watched too many agents fail because everyone wanted what they could do and nobody wanted to own them. The next real AI skill? Ownership."},"author":{"name":"Nate","handle":"@natesnewsletter","avatar":"https://social-archiver-api.social-archive.org/media/authors/arc/a62141a4e26ee0b2/avatar-dbff3882a817.png","bio":"Daily newsletters on AI strategy, news, and implementation for practitioners and leaders who are past the hype and ready to build. Click to read Nate’s Substack, a Substack publication with hundreds of thousands of subscribers."},"metadata":{"timestamp":"2026-08-06T05:44:19.688Z"},"media":[{"url":"https://social-archiver-api.social-archive.org/media/archives/arc/Bcvfwy0Nnv/media/0.jpg","type":"image","width":1200,"height":600}],"aiComments":[]}],"total":131,"pagination":{"page":1,"limit":50,"total":131,"hasMore":true}}}

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