Agent skill · Documentation

wiki-llms-txt

Generates llms.txt and llms-full.txt files for LLM-friendly project documentation following the llms.txt specification. Use when the user wants to create LLM-readable summaries, llms.txt files, or make their wiki accessible to language models.

Microsoft293,217★ · +1,988/wk · 14 repos on radarProfile →
copilotMIT
Install
npx skills add microsoft/skills --skill wiki-llms-txt --agent copilot

Same command for any agent — swap --agent for claude-code, codex, cursor.

Facts
Files in the skill folder: 1
SKILL.md size: 5 KB
Bundled scripts: none
Version: 1.0.0
Declared author: Microsoft
Path: .github/plugins/deep-wiki/skills/wiki-llms-txt/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,860
Language: TypeScript
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# llms.txt Generator Generate `llms.txt` and `llms-full.txt` files that provide LLM-friendly access to wiki documentation, following the [llms.txt specification](https://llmstxt.org/). ## When This Skill Activates - User asks to generate `llms.txt` or mentions the llms.txt standard - User wants to make documentation "LLM-friendly" or "LLM-readable" - User asks for a project summary file for langua

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About this skill
What does the wiki-llms-txt skill do?

Generates llms.txt and llms-full.txt files for LLM-friendly project documentation following the llms.txt specification. Use when the user wants to create LLM-readable summaries, llms.txt files, or make their wiki accessible to language models.

How do I install it?

Run `npx skills add microsoft/skills --skill wiki-llms-txt --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From microsoft/skills, a repository with 2,860 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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