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.
coollabsioPipes a download into a shellllms.txtcoollabsio/coolify-cli/llms-full.txt
time --preview # Deploy workflows coolify deploy name my-application coolify deploy batch api,worker,frontend --force coolify deploy list coolify deploy cancel # Database backup coolify database backup create --frequency
coollabsioPipes a download into a shellllms.txtcoollabsio/coolify-cli/llms.txt
bash coolify deploy list coolify deploy name my-application coolify deploy batch api,worker,frontend --force coolify deploy cancel ``` ### Databases and Services ```bash coolify database get coolify database create postgresql
Azure-SamplesReads credentialsllms.txtAzure-Samples/azure-ai-travel-agents/llms.txt
This file is a merged representation of a subset of the codebase, containing specifically
jamditisllms.txtjamditis/claude-skills-journalism/docs/llms.txt
with proportional checks - 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
waynesuttonReads credentialsllms.txtwaynesutton/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
ClouGencellms.txtClouGence/open-cdm/llms-full.txt
Structure | Module | Description | |--------|-------------| | `backend/` | Gradle root with backend, plugins, launchers, utilities, and test modules. | | `frontend/` | Web frontend project. | | `package/` | Repository build entry, tgz packaging, Docker images, compose templates, Kubernetes manifests
HuangYuChuhllms.txtHuangYuChuh/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
openMFllms.txtopenMF/web-app/llms.txt
used by this web app. ## Examples - [Mifos Demo](https://demo.mifos.community): Live deployment of the frontend (Nightly build). ## Optional - [Mifos System Architecture](https://mifosforge.jira.com/wiki/spaces/docs/pages/10289191/System+Architecture): Historical/high-level architectural guide of the Mifos/Fineract
VasiHemanthPipes a download into a shellllms.txtVasiHemanth/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
griddynamicsPipes a download into a shellllms.txtgriddynamics/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
Lazztechllms.txtLazztech/Libre-Closet/public/llms-full.txt
environment variable options. ## Tech Stack - **License:** AGPL-3.0 (Free Software) - **Backend:** NestJS (TypeScript) - **Frontend:** HTMX + hyperscript + DaisyUI (server-rendered, no client framework) - **Database:** SQLite or PostgreSQL - **AI:** ONNX runtime
Lazztechllms.txtLazztech/Libre-Closet/public/llms.txt
Open source (AGPL-3.0 license) - Self-hosted with Docker - NestJS backend (TypeScript) - HTMX + hyperscript frontend (server-rendered, no client framework) - SQLite or PostgreSQL database - ONNX runtime for client-side
mindroom-aiReads credentialsllms.txtmindroom-ai/mindroom/skills/mindroom-docs/references/llms-full.txt
# MindRoom > AI agents that know you and your work, in a chat app anyone
ffrolivallms.txtffroliva/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` (optionally
baseReads credentialsllms.txtbase/docs/docs/llms-full.txt
# Base Documentation — Full Context > Full context for AI agents building on Base, the blockchain
claude-did-thisPipes a download into a shellllms.txtclaude-did-this/MCPControl/docs/llms-full.txt
# Example Clients Source: https://modelcontextprotocol.io/clients A list of applications that support MCP integrations
bibinprathapllms.txtbibinprathap/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
HigangsshPipes a download into a shellllms.txtHigangssh/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
OdyseeTeamReads credentialsllms.txtOdyseeTeam/odysee-frontend/llms.txt
source-verified technical map of Odysee web/mobile/TV integrations. Scope: - Main source of truth: `odysee-frontend`. - Supporting repos: `odysee-api`, `commentron`, `odysee-roku`, `odysee-ios`. - `Odysee Internal APIs` (private/internal repository): included
nirholasReads credentialsllms.txtnirholas/three.ws/llms-full.txt
# three.ws > Open-source platform for 3D AI agents. Turn text or a photo into
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.
