Supabasellms.txtsupabase / learn
supabase/supabase/apps/learn/public/llms.txt
No summary in the file. Open it to read it.
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llms.txt examples
How real projects summarise themselves for language models.
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Supabasellms.txt
MicrosoftReads credentialsllms.txtai-agents-for-beginners / 15-browser-use
microsoft/ai-agents-for-beginners/15-browser-use/llms.txt
https://api.browser-use.com/api/v1/openapi.json get /balance Returns the user's current API credit balance, which includes both monthly subscription credits and any additional purchased credits. Required for monitoring usage and ensuring sufficient credits for task execution. https://api.browser-use.com/api/v1/openapi.json get /me Returns a boolean value indicating if the API key is valid and the user is authenticated. https://api.browser-use.com/api/v1/openapi.json post /uploads/presigned-url Returns a presigned url for uploading a file to the user's files bucket. After uploading a file, the user can use the included_file_names field in the…
Steady33 mentions in 2 weeks
No other project uses it yet
Blockllms.txtgoose / static
block/goose/documentation/static/llms.txt
This site covers using goose, the open-source agent application, and building applications with the goose Development Kit (GDK). Read the relevant documentation before writing commands, configuration, or code. Guides and Python/Kotlin references below are Markdown; native Rust APIs link to docs.rs. Use GDK's Rust crates to assemble an agent or call models directly. Python and Kotlin bindings expose providers and conversation compaction, not the full agent runtime. Use ACP to make the pre-built goose agent the backend for your application.
No other project uses it yet
LangChainllms.txtlanggraph
langchain-ai/langgraph/docs/llms.txt
Markdown index of the LangGraph (Python) documentation.
No other project uses it yet
OpenAIllms.txtopenai-agents-python
openai/openai-agents-python/docs/llms-full.txt
Extended reference map for the OpenAI Agents SDK documentation site. Use these curated links when assembling prompts that need authoritative guidance on building, operating, and extending agentic applications with the SDK. The Agents SDK delivers a focused set of Python primitives—agents, tools, guardrails, handoffs, sessions, and tracing—plus voice and realtime interfaces. The pages below provide detailed walkthroughs, architectural patterns, and API-level documentation for integrating those capabilities into production systems.
Steady2 mentions in 2 weeks
No other project uses it yet
OpenAIllms.txtopenai-agents-python
openai/openai-agents-python/docs/llms.txt
Official documentation for building production-ready agentic applications with the OpenAI Agents SDK, a Python toolkit that equips LLM-powered assistants with tools, guardrails, handoffs, sessions, tracing, voice, and realtime capabilities. The SDK focuses on a concise set of primitives so you can orchestrate multi-agent workflows without heavy abstractions. These pages explain how to install the library, design agents, coordinate tools, handle results, and extend the platform to new modalities.
Steady2 mentions in 2 weeks
No other project uses it yet
Googlellms.txtadk-python
google/adk-python/llms-full.txt
The machine-readable llms.txt documentation for Agent Development Kit (ADK) is no longer hosted statically in this repository. It is now automatically generated and hosted on the ADK documentation site. Please use the links below to access the source of truth.
1 project uses a version of this
Googlellms.txtadk-python
google/adk-python/llms.txt
The machine-readable llms.txt documentation for Agent Development Kit (ADK) is no longer hosted statically in this repository. It is now automatically generated and hosted on the ADK documentation site. Please use the links below to access the source of truth.
1 project uses a version of this
Googlellms.txtfilament
google/filament/docs/llms.txt
Filament is a real-time physically based rendering engine for Android, iOS, Linux, macOS, Windows, and WASM.
No other project uses it yet
Googlellms.txtA2UI / site
google/A2UI/docs/site/llms.txt
A2UI (Agent-to-User Interface) is an open protocol and set of renderer libraries for generative UI. An agent streams declarative JSON (surfaces, components from a trusted catalog, a data model); the client renders it with its own native components (React, Angular, Lit, Flutter, SwiftUI, Jetpack Compose). No code is executed. Protocol versions: {{A2UI_PROTOCOL_VERSIONS}}. - Component gallery - Message reference - Renderers - Agents {{A2UI_SPEC_LINKS}}
No other project uses it yet
Googlellms.txtosv-scanner
google/osv-scanner/llms.txt
A high-performance vulnerability scanner for Open Source Vulnerabilities (OSV), written in Go. osv-scanner acts as the presentation and orchestration layer, while osv-scalibr (https://github.com/google/osv-scalibr) provides the core analysis engine.
Steady4 mentions in 2 weeks
No other project uses it yet
AWSllms.txtamazon-sagemaker-examples
aws/amazon-sagemaker-examples/llms.txt
Example notebooks for building, training, and deploying models with the Amazon SageMaker Python SDK v3. This repository targets v3 only; pip install sagemaker installs v3. SDK v3 is modular (sagemaker-core, sagemaker-train, sagemaker-serve, sagemaker-mlops) and is not backward compatible with v2. v2 examples are archived, not maintained. This file follows the llms.txt convention (https://llmstxt.org): a curated index plus explicit instructions so AI coding agents generate correct, current (v3) code. - SDK-first: for any SageMaker task (train, deploy, process, pipelines), use the…
No other project uses it yet
LangChainllms.txtlanggraphjs
langchain-ai/langgraphjs/docs/docs/llms.txt
These guides are designed to help you get started with LangGraph. These guides provide explanations of the key concepts behind the LangGraph framework.
Steady4 mentions in 2 weeks
No other project uses it yet
Microsoftllms.txtagent-skills
microsoft/agent-skills/docs/llms-full.txt
Microsoft Foundry (formerly Azure AI Foundry) is a unified Azure platform-as-a-service for enterprise AI operations, model builders, and application development. It combines production-grade infrastructure with friendly interfaces for building agents, deploying models, and developing generative AI applications. Portal: https://ai.azure.com SDK Installation: Authentication Pattern: Environment Variables:
2 projects use a version of this
Microsoftllms.txtagent-skills
microsoft/agent-skills/docs/llms.txt
Microsoft Foundry (formerly Azure AI Foundry) is a unified Azure platform-as-a-service for enterprise AI operations, model builders, and application development. It provides a comprehensive set of AI capabilities for building agents, deploying models, and developing generative AI applications with built-in enterprise-readiness including tracing, monitoring, evaluations, and safety controls. Important information:
2 projects use a version of this
Googlellms.txtdocsy / goldens
google/docsy/docsy.dev/tests/md-output/goldens/llms.txt
A Hugo theme for creating great technical documentation sites
No other project uses it yet
Googlellms.txtzerocopy / v1
google/zerocopy/anneal/v1/llms-full.txt
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. See ../PRINCIPLES.md for current project principles. Known differences are historical and need not be reconciled here. Anneal is a toolchain for formally verifying unsafe Rust code using Charon, Aeneas, and Lean 4, with a specific focus on memory layout and correctness boundaries. CRITICAL INSTRUCTION FOR AGENTS: If you are new to Anneal, you MUST…
No other project uses it yet
Googlellms.txtzerocopy / v1
google/zerocopy/anneal/v1/llms.txt
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. See ../PRINCIPLES.md for current project principles. Known differences are historical and need not be reconciled here. Anneal is a toolchain for formally verifying unsafe Rust code using Charon, Aeneas, and Lean 4, with a specific focus on memory layout and correctness boundaries. CRITICAL INSTRUCTION FOR AGENTS: If you are new to Anneal, you MUST…
No other project uses it yet
Metallms.txtfairchem
facebookresearch/fairchem/docs/llms-full.txt
Canonical site: https://facebookresearch.github.io/fairchem/ Source: docs/index.md +++ {"class": "col-page-inset"} FAIR Chemistry develops open datasets and machine-learning models for molecules, materials, and catalysts. UMA brings these domains together in one pretrained model…
Steady3 mentions in 2 weeks
No other project uses it yet
Metallms.txtfairchem
facebookresearch/fairchem/docs/llms.txt
Open datasets, pretrained models, and simulation tools for materials science and quantum chemistry from Meta FAIR. FAIR Chemistry provides the UMA family of universal interatomic potentials and the fairchem Python…
Steady3 mentions in 2 weeks
No other project uses it yet
About llms.txt
What is llms.txt?
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.
What's llms-full.txt?
The same idea with the content included, so an agent can read the documentation in one request.
Who reads it?
Agents and tools that fetch documentation on someone's behalf. It's a proposal, not a standard, and support varies.
How do I write one?
Start with a one-line summary, then sections of links with a sentence each. The examples here show what real projects do.