logicrwllms.txtawesome-jev-projects
logicrw/awesome-jev-projects/public/llms-full.txt
# Awesome Jev The definitive community radar and directory for TypeSafe Jev and System-1
llms.txt examples
How real projects summarise themselves for language models.
Best matches · from page 2Worked for most · soon
logicrwllms.txt
nirholasllms.txtXActions
nirholas/XActions/llms-full.txt
handlers scripts/ 95 browser console scripts, plus build and maintenance scripts dashboard/ Static HTML frontend extension/ Chrome and Edge extension (Manifest V3) skills/ 50 Agent Skills (skills/*/SKILL.md) tests/ Vitest
evolution-foundationllms.txtevo-nexus
evolution-foundation/evo-nexus/docs/llms-full.txt
# EvoNexus Documentation Complete reference. --- # Aria — HR & People **Command:** `/aria-hr` | **Color:** pink | **Model:** Sonnet Aria
Ikalus1988llms.txtMisakaNet
Ikalus1988/MisakaNet/docs/llms-full.txt
badges](https://misakanet.org/evidence-badges/) - [Guide: fanuc-knowledge-card-2026-07](https://misakanet.org/fanuc-knowledge-card-2026-07/) - [Guide: frontend-status](https://misakanet.org/frontend-status/) - [Guide: glama-mcp-publish-guide](https://misakanet.org/glama-mcp-publish-guide/) - [Guide: glama
mixpeekllms.txtamux / site
mixpeek/amux/site/llms.txt
glance summary (member count, active/idle/waiting split, board doing/todo counts, schedule counts). Use cases: separate frontend, infra, gtm, and customer groups each with their own CLAUDE.md context and environment variables; switch
waynesuttonllms.txtopensync
waynesutton/opensync/public/llms.txt
real-time database, serverless functions, vector search) - Auth: WorkOS AuthKit (SSO, magic link, OAuth) - Frontend: React + Vite + Tailwind CSS - Embeddings: OpenAI text-embedding-3-small - Hosting: Netlify (frontend), Convex Cloud
HuangYuChuhllms.txtComfyUI_Skills_OpenClaw
HuangYuChuh/ComfyUI_Skills_OpenClaw/docs/llms-full.txt
ComfyUI APIs, waits and downloads. - `scripts/server_manager.py`: Manage multi-server settings from CLI. - `ui/`: FastAPI + frontend dashboard for server/workflow/schema management. - `data/ / /workflow.json`: normalized ComfyUI API workflow. - `data/ / /schema.json`: parameter exposure
jamditisllms.txtclaude-skills-journalism
jamditis/claude-skills-journalism/docs/llms.txt
Electron app patterns - python-pipeline, data pipeline workflows - web-scraping, content extraction - zero-build-frontend, no-build web apps - mobile-debugging, Eruda, vConsole, remote debug - accessibility-compliance, WCAG, alt text
aayushchllms.txtlaya / landing
aayushch/laya/landing/llms.txt
before the user opens the app. ## Architecture - Desktop app: Tauri (Rust) + SvelteKit (Svelte 5) frontend - Engine: Python FastAPI backend with async SQLite + ChromaDB - Integration gateway: n8n running as a local
VasiHemanthllms.txttokentelemetry
VasiHemanth/tokentelemetry/llms.txt
Vasi - **Category:** AI observability, LLM monitoring, autonomous agent observability, developer tools - **Tech stack:** Node.js (frontend: Next.js 16), Python (backend: FastAPI) - **Platforms:** macOS, Linux, Windows - **Privacy:** Local-first — your logs, prompts
griddynamicsllms.txtrosetta
griddynamics/rosetta/llms-full.txt
workflow execution; single entry point; ALL data/IP stays local, zero network calls. Dual frontend (CLI+MCP, same run delegates). Feature: plan management = `npx -y rosettify@latest plan <create|next|update
claude-did-thisllms.txtMCPControl
claude-did-this/MCPControl/docs/llms-full.txt
# Example Clients Source: https://modelcontextprotocol.io/clients A list of applications that support MCP integrations
bibinprathapllms.txtVeritasGraph
bibinprathap/VeritasGraph/llms-full.txt
State and catalog store: [studio_api/store.py](./studio_api/store.py) - Graph engine integration: [studio_api/graphrag_engine.py](./studio_api/graphrag_engine.py) ### Studio Frontend - Single-page UI: [demos/agent-studio/index.html](./demos/agent-studio/index.html) ### MCP Server (Model Context Protocol) - Zero-trust, air-gapped GraphRAG
Higangsshllms.txthomebutler
Higangssh/homebutler/llms.txt
terminal dashboard for all configured servers - `serve`: embedded web dashboard with no separate frontend runtime - Docker management: list, restart, stop, logs, stats - App install: one-command self-hosted app deployment
ffrolivallms.txtgflow-cli
ffroliva/gflow-cli/llms.txt
REST API at aisandbox-pa.googleapis.com — and, for accounts Google has moved to flow.google.com (#639), that frontend's batchexecute wire: text-to-video, image-to-video from a local `--initial-frame
Big-Ponyllms.txtpocketshell / site
Big-Pony/pocketshell/site/llms.txt
task finishes, tap it and read the answer - [Live demo](https://demo.pocketshell.net): the real frontend running against a simulated agent — no install, no host, no signup. Best on a phone
nikolai-vysotskyillms.txttrace-mcp
nikolai-vysotskyi/trace-mcp/docs/llms-full.txt
subproject is any working repository that is part of your project's ecosystem: microservices, frontends, backends, shared libraries, CLI tools, etc. A project auto-detects its subprojects on indexing
softsparkllms.txtai-toolkit
softspark/ai-toolkit/llms-full.txt
memory leak. - **persona**: Switches engineering persona at runtime. Triggers: persona, switch role, backend-lead, frontend-lead, devops-eng, junior-dev. - **php-rules**: PHP coding rules: style, patterns, security, testing. Triggers
smnandrellms.txtsymfony-ux-skills
smnandre/symfony-ux-skills/llms.txt
Symfony UX Agent Skills > AI agent skills for the Symfony UX frontend stack: Stimulus, Turbo, TwigComponent, LiveComponent, Icons, and Map. Built on the agentskills.io open standard. Covers Symfony
Dynatracellms.txtdynatrace-for-ai
Dynatrace/dynatrace-for-ai/llms.txt
services: Service RED metrics, runtime telemetry (.NET, Java, Node.js, Python, PHP, Go). - dt-obs-frontends: RUM, Web Vitals, user sessions, mobile, frontend errors. - dt-obs-tracing: Distributed traces, spans, dependencies
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.