How real projects summarise themselves for language models.
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
mathuollms.txtmathuo/dockview/llms.txt
install dockview-angular` | | dockview-enterprise | All (commercial) | `npm install dockview-enterprise` | ## Optional - [Full documentation for LLMs](https://dockview.dev/llms-full.txt): Extended reference with code examples for every framework ## Links - Documentation
No other project uses it yet
LangChainllms.txtlangchain-ai/langgraphjs/docs/docs/llms.txt
dangerous, especially when the decisions involve invoking certain tools or accessing specific documents. To remedy this, LangGraph allows you to insert human-in-the-loop behavior to ensure your graph
Steady6 mentions in 2 weeks
No other project uses it yet
danielpethollms.txtdanielpetho/fancy/public/llms.txt
reveal effect. ## Additional Resources - [GitHub Repository](https://github.com/danielpetho/fancy): Source code and contributions - [Interactive Documentation](https://fancycomponents.dev): Full documentation with live examples - [Installation Guide](https://fancycomponents.dev/docs/installation.md): Setup instructions - [Changelog
No other project uses it yet
alexei-ledllms.txtalexei-led/pumba/llms.txt
Netflix Chaos Monkey but for Docker environments. ## Docs - [README](https://github.com/alexei-led/pumba/blob/master/README.md): Full documentation, installation, usage - [Advanced Network Chaos](https://github.com/alexei-led/pumba/blob/master/docs/advanced-network-chaos.md): Bidirectional network chaos, iptables ## Architecture - **Language:** Go - **Container
Steady4 mentions in 2 weeks
No other project uses it yet
Microsoftllms.txtmicrosoft/skills/docs/llms-full.txt
Azure Language detection](https://learn.microsoft.com/en-us/azure/ai-foundry/azure/ai-services/language-service/language-detection/quickstart?context=/azure/foundry/context/context?view=foundry) - [Azure text translation](https://learn.microsoft.com/en-us/azure/ai-foundry/azure/ai-services/translator/text-translation/overview?context=/azure/foundry/context/context?view=foundry) - [Azure document translation](https://learn.microsoft.com/en-us/azure/ai-foundry/azure/ai-services/translator/document-translation/overview?context=/azure/foundry/context/context?view=foundry) - [Connect to MCP server](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/model-context-protocol?view=foundry) - [MCP authentication](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/mcp-authentication?view=foundry)
2 projects use a version of this
Microsoftllms.txtmicrosoft/skills/docs/llms.txt
JavaScript/TypeScript, and Java - All URLs require `?view=foundry` parameter to access the new documentation ## General - [What is Microsoft Foundry (new)?](https://learn.microsoft.com/en-us/azure/ai-foundry/what-is-foundry?view=foundry) ## Get started - ["Quickstart: Create resources"](https://learn.microsoft.com
2 projects use a version of this
ibelickllms.txtibelick/prompt-kit/llms-full.txt
install and configure shadcn/ui in your project. Follow the installation guide at [shadcn/ui documentation](https://ui.shadcn.com/docs/installation). Once shadcn/ui is set up, you can install **prompt-kit** components using
No other project uses it yet
ibelickllms.txtibelick/prompt-kit/llms.txt
designed to be easily customizable and can be installed individually using the shadcn CLI. ## Documentation - [README](https://github.com/ibelick/prompt-kit/blob/main/README.md): Installation instructions and basic usage guide - [Installation](https://www.prompt-kit.com/docs/installation): Detailed
No other project uses it yet
Googlellms.txtgoogle/docsy/docsy.dev/tests/md-output/goldens/llms.txt
Docsy > A Hugo theme for creating great technical documentation sites ## Site index - [Home page](http://localhost/index.md) - [About](http://localhost/about/index.md): Docsy is a pre-configured Hugo theme that provides the core
No other project uses it yet
mengjian-githubllms.txtmengjian-github/openclaw101/public/llms-full.txt
Library URL: https://openclaw101.dev/resources 70+ curated resources organized by category: - Official repositories and documentation - Community skills and plugins - Hosting providers and deployment guides - AI model provider comparisons - Complementary tools
No other project uses it yet
moltis-orgPipes a download into a shellllms.txtmoltis-org/moltis/website/llms.txt
markers, sessions use `oc:` prefixes, skills/MCP skip duplicates, workspace files skip user-customized content. ### Documentation Full details: <https://docs.moltis.org/openclaw-import.html> ## Start and Handoff - Start gateway: `moltis gateway --bind 0.0.0.0 --port
Steady3 mentions in 2 weeks
No other project uses it yet
chdb-ioPipes a download into a shellllms.txtchdb-io/chdb/llms-full.txt
interface that compiles to optimized SQL — up to 247× faster than pandas on COUNT. - Documentation pages under `clickhouse.com/docs` return clean Markdown when requested with an `Accept: text/markdown` header — prefer
No other project uses it yet
chdb-iollms.txtchdb-io/chdb/llms.txt
interface that compiles to optimized SQL — up to 247× faster than pandas on COUNT. - Documentation pages under `clickhouse.com/docs` return clean Markdown when requested with an `Accept: text/markdown` header — prefer
No other project uses it yet
datachain-aillms.txtdatachain-ai/datachain/docs/llms.txt
fields 8. Use `dc.func.*` for SQL-speed analytics: distance, aggregate, window, path, string, conditional ## Documentation Sections - Getting Started: /getting-started/ - Core Concepts: /concepts/ (dataset db, datasets, chain, execution model, files
snapotter-hqllms.txtsnapotter-hq/SnapOtter/llms.txt
compression, OCR, transcription, metadata scrubbing, and local AI across image, video, audio, PDF, and documents, through a web UI, REST API, and automation pipelines. Everything runs on your own infrastructure
1 project uses a version of this
themesbergllms.txtthemesberg/flowbite-svelte/static/llms.txt
llms.txt # Documentation index for LLMs # See https://llmstxt.org for details version: 1 llms: markdown # Main documentation sections /docs: https://flowbite-svelte.com/llm/components/accordion.md /docs: https://flowbite-svelte.com/llm/components/alert.md /docs: https://flowbite-svelte.com/llm/components/avatar.md /docs
No other project uses it yet
nteractllms.txtnteract/semiotic/llms.txt
content identity; verify the installed package separately before applying current-development guidance. The generated documentation catalog is available at [semiotic.nteract.io/llms.txt](https://semiotic.nteract.io/llms.txt), with the expanded reference at [semiotic.nteract.io/llms-full.txt](https://semiotic.nteract.io/llms-full.txt).
No other project uses it yet
CodeBoardingReads credentialsllms.txtCodeBoarding/CodeBoarding/llms.txt
ANALYSIS_CONFIG={project_root}/static_analysis_config.yml PROJECT_ROOT={project_root} DIAGRAM_DEPTH_CAP=1 CACHING_DOCUMENTATION=false # Monitoring Configuration ENABLE_MONITORING=false # ============================================================================ # LLM PROVIDER OPTIONS (uncomment and configure as needed) # ============================================================================ # OpenAI
No other project uses it yet
botswinllms.txtbotswin/BotBrowser/llms.txt
ships in two builds. Both share the same fingerprint protection model, profile format, and documented CLI/CDP interfaces. Capability availability still depends on the active profile package and subscription tier. - **Standard
Googlellms.txtgoogle/zerocopy/anneal/v1/llms-full.txt
Anneal Formal Verification Toolchain > **Historical V1 documentation:** This document describes the prototype in > `anneal/v1/`. It remains authoritative for using and maintaining V1, but it is > not current Anneal design authority
No other project uses it yet
A markdown file at a website's root that gives language models a short guide to the site and links to the pages worth reading.
The same idea with the content included, so an agent can read the documentation in one request.
Agents and tools that fetch documentation on someone's behalf. It's a proposal, not a standard, and support varies.
Start with a one-line summary, then sections of links with a sentence each. The examples here show what real projects do.
