How real projects summarise themselves for language models.
garrytanllms.txtgarrytan/gstack/gstack/llms.txt
only queue dashboard for workspace-aware ship. - [/learn](learn/SKILL.md): Manage project learnings. - [/make-pdf](make-pdf/SKILL.md): Turn any markdown file into a publication-quality PDF. - [/office-hours](office-hours/SKILL.md
alirezarezvanillms.txtalirezarezvani/claude-skills/docs/llms-full.txt
markdown deck → single-file HTML presentation with keyboard nav, presenter mode, and print-to-PDF). Output is single-file HTML (Google Fonts + Prism.js CDN the only permitted externals). --- ## Agents
enescingozllms.txtenescingoz/awesome-n8n-templates/llms.txt
Templates](https://github.com/enescingoz/awesome-n8n-templates/tree/main/Telegram): 19 templates for AI chatbots, voice assistants, content moderation, PDF chat, resume building, Spotify integration, and multi-language translation bots. - [Google Drive and Google Sheets
tonhowtfllms.txttonhowtf/omniget/llms-full.txt
with quality options, click download. The same window then plays the course, reads the PDF, transcribes the audio and backs up the Pinterest board. yt-dlp and FFmpeg install themselves
tonhowtfllms.txttonhowtf/omniget/llms.txt
Claude Desktop, Cursor, VS Code, Goose and Codex. - Tools include: queue and control downloads, PDF merge/split/render/extract/sanitize, whisper.cpp transcription, text to speech, OCR, image resize, duplicate finder, file search, X posts/threads/profiles/search
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.
