Claude-skill-registry llms-txt

Generate an llms.txt file for any project or website following the llmstxt.org specification. Use when asked to create llms.txt, generate LLM-friendly documentation, make a project AI-readable, or prepare documentation for language models.

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/llms-txt" ~/.claude/skills/majiayu000-claude-skill-registry-llms-txt && rm -rf "$T"
manifest: skills/data/llms-txt/SKILL.md
source content

llms.txt Generator

Generate a well-structured

/llms.txt
file following the llmstxt.org specification proposed by Jeremy Howard.

What is llms.txt?

A markdown file that helps LLMs understand and use a project/website efficiently. It provides:

  • Concise project overview
  • Links to key documentation with descriptions
  • Organized sections for different resource types

Generation Process

  1. Analyze the project structure using Glob to find:

    • README files
    • Documentation directories (
      docs/
      ,
      documentation/
      ,
      wiki/
      )
    • API documentation
    • Example files and tutorials
    • Configuration files that explain the project
    • Source code entry points
  2. Identify key information:

    • Project name and purpose
    • Main features and capabilities
    • Important caveats or limitations
    • Dependencies and requirements
  3. Generate the llms.txt following this exact format:

# Project Name

> Brief description of the project in 1-2 sentences. Include the most critical information needed to understand what this project does.

Key notes (if any important caveats exist):
- Important limitation or compatibility note
- Another critical detail

## Docs

- [Doc Title](url): Brief description of what this doc covers

## Examples

- [Example Title](url): What this example demonstrates

## API

- [API Reference](url): Description of API coverage

## Optional

- [Secondary Resource](url): Less critical but potentially useful

Format Rules

  1. H1 (Required): Project/site name - this is the ONLY required section
  2. Blockquote: Short summary with key context (highly recommended)
  3. Body text: Important notes, caveats, or guidance (optional)
  4. H2 Sections: Categorized lists of resources with URLs and descriptions
  5. Optional Section: Resources that can be skipped for shorter context

Best Practices

  • Be concise: LLMs have limited context windows
  • Prioritize: Put most important resources first
  • Describe well: Each link should have a brief, informative description
  • Use "Optional" wisely: Secondary resources that aren't always needed
  • Avoid jargon: Explain terms that aren't universally known
  • Include external links: Reference external docs if helpful (e.g., framework docs)

URL Handling

  • For websites: Use absolute URLs (
    https://example.com/docs/api.md
    )
  • For repositories: Use relative paths or raw GitHub URLs
  • Suggest creating
    .md
    versions of HTML pages at same URL +
    .md
    extension

Output

Write the generated

llms.txt
to:

  • $ARGUMENTS
    if provided
  • Otherwise, project root as
    llms.txt

After generating, briefly explain what was included and why.

Reference Examples

For examples of well-crafted llms.txt files, see references/examples.md.


Note: This skill does not require external scripts. The analysis and generation is performed directly using available tools (Glob, Grep, Read) to understand the project structure and generate appropriate content.