Efficiently consume and navigate external documentation sites...
This skill helps you efficiently consume documentation without overwhelming your context window or missing important information.
| Situation | Approach |
|---|---|
| First visit to a doc site | Check for llms.txt, then MCP |
| Know exactly what you're looking for | MCP search or grep llms-full.txt |
| Need to read a specific page | Try .md URL variant first, then HTML |
| Exploring/browsing | View HTML page in browser |
| Need comprehensive understanding | Load llms-full.txt (check length first) |
| Multiple doc sites in one task | Set up MCPs for each |
When you encounter a documentation site, check for AI-friendly resources.
Every well-structured doc site should have an llms.txt file at the root. For example https://docs.example.com/llms.txt or https://example.com/docs/llms.txt.
This file contains:
Sites may also have llms-full.txt files at the root which contain all the content on the documentation site as a single .md file.
Many doc sites serve clean markdown versions of pages at .md URL variants. Prefer the .md URL extensions for easier-to-parse content.
For any specific page you need to read, try the .md variant first:
https://docs.example.com/page → try https://docs.example.com/page.md
If it returns valid markdown (not a 404 or HTML error page), use that instead of fetching the HTML.
Some documentation sites provide a skill.md file that teaches you how to work with the product that is documented. Check for it at the root like https://docs.example.com/skill.md or https://example.com/docs/skill.md.
Read the skill to understand the product and features. Add the skill if it will be helpful with your current task:
npx skills add docs.example.com/skill.md
Some documentation sites provide MCP servers for semantic search. The MCP endpoint often follows this pattern:
https://docs.example.com/mcp
MCP (Model Context Protocol) servers let you search documentation semantically rather than relying on keyword matching or loading entire files.
The setup process varies by platform. For Claude Code:
{
"mcpServers": {
"example-docs": {
"type": "http",
"url": "https://docs.example.com/mcp"
}
}
}
Once connected, you'll have access to the search tool for semantic search across the documentation. The tool follows the naming pattern Search{DocsTitle} (for example, SearchMintlify).
When working with multiple documentation sources:
Use when:
Use the MCP search tool with a natural language query describing what you need.
Use when:
Try the .md variant of the page URL:
curl -s "https://docs.example.com/page.md"
If it returns valid markdown, use it. If it 404s, fall back to HTML (Strategy E).
Use when:
Grep for your terms:
curl -s "https://docs.example.com/llms-full.txt" | grep -C 3 "your-search-term"
Use when:
Always check length first. Before loading a full file:
curl -sI "https://docs.example.com/llms-full.txt" | grep -i content-length
If the file is too large, consider:
Use when:
Fetch and render the HTML page, or direct the user to open it in their browser. HTML pages provide:
Watch for truncation. Pages over ~150,000 characters may get cut off, which means you may miss critical information without knowing it. If a page seems incomplete, try the .md URL variant (Strategy B) or look for section-specific files in llms.txt.
Prefer MCP for Mintlify sites: Semantic search is more efficient than loading and parsing raw text.
Cache strategically: If you'll reference the same docs repeatedly, loading llms-full.txt once may be more efficient than multiple MCP searches.
Use section files: If llms.txt links to section-specific files (like api/llms.txt), load only what you need.
Parallel MCP searches: When working with multiple doc sources, search them in parallel rather than sequentially.
Fall back to:
.md URL variants of specific pages you need to readFor docs over 15k tokens:
If a page 404s:
If you find documentation that seems outdated: