setup-llms-txt

Create and configure llms.txt for any website or project. Analyzes project structure, generates llms.txt and llms-full.txt, places files in the correct location for your framework. Use when setting up llms.txt, improving AI discoverability, or making a site LLM-friendly.

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Install skill "setup-llms-txt" with this command: npx skills add cartoonitunes/inlay-skills/cartoonitunes-inlay-skills-setup-llms-txt

Setup llms.txt Skill

Create and configure llms.txt and llms-full.txt for any website. These files help LLMs understand your site — think of them as robots.txt for AI models.

What is llms.txt?

llms.txt is a standard file (served at /llms.txt) that tells AI models:

  • What your site/product does
  • Where to find key resources (docs, API, guides)
  • How to interact with your service

llms-full.txt is an expanded version with full content that LLMs can ingest without following links.

Spec: https://llmstxt.org

Workflow

Step 1: Analyze the Project

Examine the project structure to understand:

  • What the site/product does
  • Key pages and documentation
  • API endpoints (if any)
  • Framework being used
# Check framework
ls package.json next.config.* astro.config.* gatsby-config.* nuxt.config.* 2>/dev/null

# Find key content
find . -name "*.md" -o -name "*.mdx" | head -20
ls -la public/ static/ 2>/dev/null

# Check for existing llms.txt
curl -s "https://YOUR_SITE/llms.txt" | head -5

Step 2: Generate llms.txt

Create the file following the standard format:

# [Site/Product Name]

> [One-line description of what the site does]

## Docs
- [Getting Started](/docs/getting-started): How to get started with [Product]
- [API Reference](/docs/api): Full API documentation
- [Examples](/docs/examples): Code examples and tutorials

## API
- Base URL: https://api.example.com
- [Authentication](/docs/auth): How to authenticate API requests
- [Rate Limits](/docs/rate-limits): API rate limiting details

## Key Pages
- [Pricing](/pricing): Plans and pricing
- [Blog](/blog): Latest updates and articles
- [Changelog](/changelog): Product updates

## Contact
- Support: support@example.com
- Twitter: @example

Guidelines:

  • Use Markdown format
  • Start with # heading and > blockquote summary
  • Group links by category with ## headings
  • Use descriptive link text with brief explanations
  • Include all important pages and resources
  • Keep it concise — this is a summary, not full docs

Step 3: Generate llms-full.txt (Optional but Recommended)

Create an expanded version with full content inline:

# [Site/Product Name]

> [Description]

## Getting Started

[Full getting started content here, not just a link]

## API Reference

[Full API docs inline]

...

This is especially valuable for documentation sites — LLMs can ingest the full content in one request.

Step 4: Place Files

Place based on framework:

FrameworkLocation
Next.jspublic/llms.txt
Astropublic/llms.txt
Gatsbystatic/llms.txt
Hugostatic/llms.txt
Nuxtpublic/llms.txt
SvelteKitstatic/llms.txt
Vite/Reactpublic/llms.txt
Plain HTMLRoot directory
Express/APIServe via route handler

Step 5: Validate

# Check it's accessible
curl -s https://YOUR_SITE/llms.txt | head -20

# Verify content type (should be text/plain or text/markdown)
curl -sI https://YOUR_SITE/llms.txt | grep -i content-type

# Check llms-full.txt too
curl -s https://YOUR_SITE/llms-full.txt | head -20

Step 6: Verify with Inlay

Run an AI readiness audit to confirm the llms.txt is detected:

curl -s -X POST https://www.inlay.dev/api/audit \
  -H 'Content-Type: application/json' \
  -d '{"url":"https://YOUR_SITE"}'

The llms.txt category score should improve after adding the file.

Tips

  • Keep llms.txt under 10KB — it's a summary
  • llms-full.txt can be larger but aim for under 500KB
  • Update when you add major features or change docs structure
  • Include API endpoints if you have a public API
  • Link to your MCP server if you have one

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