How real projects summarise themselves for language models.
Ataraxy-Labsllms.txtAtaraxy-Labs/sem/docs/llms.txt
github.com/Ataraxy-Labs/sem", version = "0.3" } ``` Used by weave (semantic merge driver) and inspect (entity-level code review). ## Links - GitHub: https://github.com/Ataraxy-Labs/sem - Website: https://ataraxy-labs.github.io/sem - License: MIT OR Apache
LangChainllms.txtlangchain-ai/langgraphjs/docs/docs/llms.txt
wait for user input (Functional API)](https://docs.langchain.com/oss/javascript/langgraph/how-tos/wait-user-input-functional/) - [How to review tool calls (Functional API)](https://docs.langchain.com/oss/javascript/langgraph/how-tos/review-tool-calls-functional/) ### Time Travel [Time travel](https://docs.langchain.com/oss/javascript/langgraph/concepts/time-travel/) allows you to replay
tractorjuicellms.txttractorjuice/arc-kit/docs/llms.txt
Bureaucracy / Service Catalogue](https://github.com/tractorjuice/arc-kit/blob/main/plugins/arckit-uae/commands/uae-zero-bureaucracy.md): `/arckit:uae-zero-bureaucracy` UAE Code for Government Services service catalogue review and CX KPIs. - [Digital Records Plan](https://github.com/tractorjuice/arc-kit/blob/main/plugins/arckit-uae/commands/uae-digital-records.md): `/arckit:uae-digital
mrgooniellms.txtmrgoonie/claudekit-skills/.claude/skills/claude-code/llms.txt
shortcuts - See: references/ide-integration.md ### CI/CD Integration - GitHub Actions workflows - GitLab CI/CD pipelines - Automated testing and code review - See: references/cicd-integration.md ### Advanced Features - Extended thinking - Prompt caching - Checkpointing - Memory management - Context windows
Lumiwealthllms.txtLumiwealth/lumibot/llms-full.txt
# Lumibot Documentation (Compiled) # Generated: 2026-09-13T21:04:40Z ===== MIGRATING_FROM_BACKTRADER ===== Migrating
Lumiwealthllms.txtLumiwealth/lumibot/llms.txt
Complete two-agent Strategy: https://lumibot.lumiwealth.com/agents_quickstart.html - Examples and recorded evidence: https://lumibot.lumiwealth.com/agents_examples.html - Coding-agent instructions: https://lumibot.lumiwealth.com/agent_start_here.html - Standalone components: https://lumibot.lumiwealth.com/standalone_components.html - Existing Strategy subclasses remain
Microsoftllms.txtmicrosoft/WhatTheHack/068-AzureOpenAIApps/Student/Resources/data/mcp-info/llms-full.txt
# Example Clients Source: https://modelcontextprotocol.io/clients A list of applications that support MCP integrations
fynnflueggellms.txtfynnfluegge/agtx/llms-full.txt
coding agents in parallel. agtx manages coding agent sessions through a spec-driven workflow with phases: backlog, planning, implementation (running), review, and done. Each task gets its own git worktree
fynnflueggellms.txtfynnfluegge/agtx/llms.txt
orchestrates multiple AI coding agents in parallel. agtx manages coding agent sessions through a spec-driven workflow: backlog, planning, implementation, review, done. Each task gets its own git worktree
umputunllms.txtumputun/ralphex/llms.txt
Executes implementation plans task by task in fresh Claude sessions, then runs multi-phase code reviews. Write a plan, start ralphex, walk away. **GitHub:** https://github.com/umputun/ralphex ## Installation ```bash # from
razzantllms.txtrazzant/ouroboros/docs/llms.txt
Claudexor](https://claudexor.ai/): The local execution layer Ouroboros uses for delegated coding and hosted-agent review. - [Claudexor source](https://github.com/razzant/claudexor): Routing, execution, and durable evidence for connected coding
mbaileyllms.txtmbailey/voicemode/llms.txt
based Git repository hosting, CI/CD via GitHub Actions, project management with Issues and Projects, code review via pull requests, AI-powered development with GitHub Copilot, and APIs (REST and GraphQL
sceneviewllms.txtsceneview/sceneview/llms.txt
# SceneView > Declarative 3D and AR SDK for Jetpack Compose (Filament, ARCore), SwiftUI (RealityKit, ARKit
sipyourdrink-ltdllms.txtsipyourdrink-ltd/bernstein/docs/llms-full.txt
execution, git worktree isolation, janitor verification, quality gates (lint, types, PII scan), cross-model code review, circuit breaker for misbehaving agents, token growth monitoring with auto-intervention. - **Intelligence**. Contextual bandit
ksimbackllms.txtksimback/hermes-ecosystem/llms-full.txt
Hermes skill executions | — | Experimental | --- ## Security Notes All community repos with 25+ stars were reviewed for obfuscated code, credential harvesting, typosquatting, supply chain attacks, crypto mining, and excessive permissions. **No repos
ksimbackllms.txtksimback/hermes-ecosystem/llms.txt
marshallrichards/ClawPhone - [A multi-agent build pipeline](https://hermesatlas.com/use-cases/multi-agent-build-pipeline): I want several agents planning, coding, reviewing and shipping in parallel instead of one agent doing everything serially — builderz-labs/mission-control
aklofasllms.txtaklofas/kicad-happy/llms.txt
kicad-happy > AI-powered design review skills for KiCad electronics projects A suite of 11 skills that turn an AI coding agent into an electronics design assistant. Structured Python analysis
LING71671llms.txtLING71671/open-reverselab/docs/llms-full.txt
# ReverseLab — Full Knowledge Base Dump for LLM Ingestion Total articles: 183 Generated: 2026-08
vshulczllms.txtvshulcz/deja-vu/docs/llms.txt
chat history across every agent at once - [Switching agents](https://vshulcz.github.io/deja-vu/guide/switching-agents.html): move between Claude Code, Codex and Cursor without re-explaining - [After compaction](https://vshulcz.github.io/deja-vu/guide/after-compaction.html): recovering the commands
RyanAlbertsllms.txtRyanAlberts/best-of-Agent-Harnesses/llms.txt
# Best of Agent Harnesses > Hand-curated, ranked list of 167 AI agent harnesses — the
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.
