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.
NangoHQllms.txtNangoHQ/nango/docs/llms.txt
Customize per customer](https://nango.dev/docs/getting-started/use-cases/customer-configuration.md): Adapt integration behavior for each customer without forking code. - [Use cases: React to connection lifecycle events](https://nango.dev/docs/getting-started/use-cases/implement-event-handler.md): Run integration logic when
DuarteSantos8Reads credentialsllms.txtDuarteSantos8/openGym/website/llms.txt
every release ## How it is built - Developed with Claude Code (Anthropic's coding agent); changes are reviewed, tested and released by the maintainer. The app itself needs no AI service
Steady16 mentions in 2 weeks
No other project uses it yet
tw93llms.txttw93/Kami/site/llms.txt
kami` - Claude Desktop: download the release asset `kami.zip` from GitHub Releases (not the source-code ZIP) and upload it via Customize > Skills > "+" > Create skill - MCP client: `claude mcp add kami
Steady6 mentions in 2 weeks
No other project uses it yet
HKUSTDialllms.txtHKUSTDial/Supervisor-Skills/llms.txt
research discovery, idea evaluation, paper planning, drafting, polishing, figure design and reconstruction, pre-submission review, and AI-assisted research workflow. Usable as a standalone Chinese curriculum at `handbook
No other project uses it yet
replicatellms.txtreplicate/cog/docs/llms.txt
# Cog: Containers for machine learning Cog is an open-source tool that lets you
themesbergllms.txtthemesberg/flowbite/llms-full.txt
# Flowbite Documentation > Flowbite is a free and open-source UI component library based on
No other project uses it yet
chaitanyagirillms.txtchaitanyagiri/munder-difflin/docs/llms-full.txt
source: a desktop app that runs a team of coding agents > such as Claude Code, Codex and Gemini CLI on your own computer. It is presented as a > virtual office
1 project uses a version of this
chaitanyagirillms.txtchaitanyagiri/munder-difflin/docs/llms.txt
Engines it runs: Claude Code, OpenAI Codex, Gemini CLI, Antigravity (Gemini), xAI Grok, Kimi Code, Qwen, OpenCode, Crush, pi.dev, GitHub Copilot CLI, Cursor, or any custom command. Your
lastmile-aiReads credentialsllms.txtlastmile-ai/mcp-agent/LLMS.txt
requests, handle flight modifications, cancellations, and lost baggage cases. https://github.com/user-attachments/assets/b314d75d-7945-4de6-965b-7f21eb14a8bd **Link to code**: [examples/workflows/workflow_swarm](./examples/workflows/workflow_swarm/) ## Core Components The following are the building blocks of the mcp-agent framework
No other project uses it yet
zumerlabllms.txtzumerlab/snapdom/docs/llms-full.txt
# SnapDOM: v3 reference Last updated: 2026-10-28. SnapDOM (`@zumer/snapdom`) is a high-performance
SciPhi-AIReads credentialsllms.txtSciPhi-AI/R2R/llms.txt
# Understanding Internals of R2R Library ## Table of Contents 1. [Introduction](#introduction) 2. [Installation](#installation
No other project uses it yet
anbeimellms.txtanbeime/skill/public/llms-full.txt
postgres-best-practices - **Expo** (3个) - expo-app-design, expo-deployment, upgrading-expo - **Sentry** (7个) - code-review, commit, create-pr, find-bugs 等 - **Better Auth** (3个) - best-practices, commands, create-auth
Steady13 mentions in 2 weeks
No other project uses it yet
HenryNdubuakullms.txtHenryNdubuaku/maths-cs-ai-compendium/llms.txt
production software engineering/04. testing and quality assurance.md): pytest, mocking, testing ML code, CI/CD, linting, code review - [Deployment and DevOps](chapter 15: production software engineering/05. deployment and devops.md): Docker, model serving
No other project uses it yet
tw93llms.txttw93/Waza/llms.txt
Code, Codex, Cursor, Antigravity, OpenCode, Pi, and compatible agents. - `think`: pressure-test a requirement and produce a decision-complete plan - `ui`: build or polish a distinctive frontend interface - `check`: review
Steady4 mentions in 2 weeks
1 project uses a version of this
wesmllms.txtwesm/agentsview/docs/llms.txt
example `/docs/quickstart/`). ## Product - [AgentsView](https://agentsview.io/index.md): The system of record for your AI coding agents. - [The session intelligence loop](https://agentsview.io/guide.md): A nine-stop tour from session capture
Steady8 mentions in 2 weeks
No other project uses it yet
FlorianBruniauxPipes a download into a shellllms.txtFlorianBruniaux/claude-code-ultimate-guide/llms-full.txt
lets developers interact with Claude directly from the terminal to write, edit, debug, and review code. Unlike IDE plugins, it has full filesystem access, can run shell commands, and works
FlorianBruniauxllms.txtFlorianBruniaux/claude-code-ultimate-guide/llms.txt
privacy and retention, enterprise governance (guardrail tiers, MCP approval workflow, audit trails) - CI/CD and code review: GitHub Actions patterns, the Code Review feature (Teams/Enterprise), multi-provider review pipelines - Verification methods
Q00llms.txtQ00/ouroboros/llms.txt
that rewrites its own architecture -- a different project with a different design, no shared code. ## Core Concepts - Seed Spec: An immutable YAML specification auto-generated from a Socratic interview. Contains
Steady29 mentions in 2 weeks
No other project uses it yet
HelixDBPipes a download into a shellllms.txtHelixDB/helix-db/docs/llms-full.txt
same `POST /v2/query` interface as Helix Cloud, which makes it the default development target: code written against it works unchanged in Cloud. ## Embedded Embedded clients open the engine inside your
HelixDBPipes a download into a shellllms.txtHelixDB/helix-db/docs/llms.txt
contract — Page type: Reference - [Query error reference](https://docs.helix-db.com/database/helix-db/query-guides/error-handling): Branch on stable error codes, apply retry rules, and look up every HelixDB query error — Page type: Reference - [Troubleshoot HelixDB
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.
