What is the benefit of using llms.txt with Claude?

The llms.txt file provides a condensed, AI-friendly map of a documentation site, allowing Claude to find specific content quickly without the overhead of parsing full HTML pages.

How does the MCP integration improve documentation searches?

It connects Claude to a Model Context Protocol server to perform semantic searches, which find relevant documentation based on meaning and intent rather than just exact keyword matches.

Can I use this skill for non-Mintlify documentation sites?

Yes, while it offers enhanced features for Mintlify sites, it functions with any documentation that provides an llms.txt file or an accessible MCP endpoint.

How does this skill help save context window tokens?

It uses strategies like grep-searching and semantic indexing to only fetch the specific sections of documentation you need, rather than loading the entire documentation site.

What is a skill.md file in the context of documentation?

A skill.md file is a specialized document that teaches Claude specific implementation patterns, best practices, and domain-specific knowledge for a particular tool or platform.

Documentation Reader

Name: Documentation Reader
Author: mintlify

bymintlify

•

333

Learning & Documentation

Navigates and consumes external documentation efficiently using AI-friendly standards like llms.txt and MCP servers.

About

The Documentation Reader skill empowers Claude to interact with external developer documentation without exhausting context windows. It intelligently discovers AI-optimized resources such as llms.txt files and Model Context Protocol (MCP) servers to perform semantic searches, targeted keyword lookups, or strategic full-file ingestion. Designed to handle everything from quick API lookups to deep library research, this skill is especially optimized for Mintlify-powered sites, ensuring you always have the most relevant technical context while keeping your development workflow lean.

Key Features

Support for specialized skill.md installation for product-specific guidance and best practices.
Smart context management that prevents token overflow by analyzing file sizes before ingestion.
Efficient keyword filtering and snippet extraction using grep on remote documentation sources.
Automated discovery of AI-friendly llms.txt and llms-full.txt files at documentation roots.
Semantic documentation search via Model Context Protocol (MCP) server integration.
333 GitHub stars

Use Cases

Researching a new API or library architecture before starting a fresh implementation.
Debugging specific error messages by performing targeted keyword searches across documentation.
Onboarding to complex tools by loading specialized skill guides directly into the AI environment.

About

Key Features

Support for specialized skill.md installation for product-specific guidance and best practices.
Smart context management that prevents token overflow by analyzing file sizes before ingestion.
Efficient keyword filtering and snippet extraction using grep on remote documentation sources.
Automated discovery of AI-friendly llms.txt and llms-full.txt files at documentation roots.
Semantic documentation search via Model Context Protocol (MCP) server integration.
333 GitHub stars

Use Cases

Researching a new API or library architecture before starting a fresh implementation.
Debugging specific error messages by performing targeted keyword searches across documentation.
Onboarding to complex tools by loading specialized skill guides directly into the AI environment.