Can I search for specific versions of a library?

Yes, Docs-Seeker supports version-specific searches by including version tags in the query and checking versioned documentation paths or repository tags.

Why use parallel explorer agents?

Parallel agents allow Claude to read multiple documentation sections simultaneously, significantly speeding up the extraction of information from large, multi-page docs.

What is the llms.txt standard?

It is a standardized way for libraries to provide documentation in a format optimized for large language models to ingest and process efficiently.

What happens if a library doesn't have an llms.txt file?

The skill automatically falls back to searching for a GitHub repository for Repomix analysis or deploying Researcher agents to find official tutorials and web guides.

How does this skill handle GitHub repositories?

It uses Repomix to pack the repository into a single AI-friendly XML file, preserving the directory structure for comprehensive codebase analysis by Claude.

Documentation Seeker

Name: Documentation Seeker
Author: trungtnm

bytrungtnm

0•

Learning & Documentation

Locates and analyzes technical documentation using llms.txt standards, GitHub repository packing, and parallel exploration agents.

Docs-seeker is a specialized Claude Code skill designed to streamline technical discovery by locating high-quality, AI-friendly documentation. It prioritizes the llms.txt standard—leveraging aggregators like context7.com—and utilizes Repomix to analyze entire GitHub repositories when official documentation is insufficient. By deploying parallel explorer agents to process multiple documentation pages simultaneously, it provides developers with deep, version-specific insights and consolidated reports, eliminating the need for manual browsing and context gathering.

Key Features

01Consolidated reporting across multiple sources, tutorials, and API references

02Version-specific documentation targeting and automated fallback research

03Parallel exploration using multiple agents for high-speed documentation coverage

040 GitHub stars

05AI-friendly documentation discovery via llms.txt and context7.com

06GitHub repository analysis using Repomix packing for deep codebase insights

Use Cases

01Quickly learning a new framework's best practices using its llms.txt file

02Analyzing complex GitHub repositories for undocumented internal logic or patterns

03Researching specific API features across multiple documentation sections in parallel

Key Features

01Consolidated reporting across multiple sources, tutorials, and API references

02Version-specific documentation targeting and automated fallback research

03Parallel exploration using multiple agents for high-speed documentation coverage

040 GitHub stars

05AI-friendly documentation discovery via llms.txt and context7.com

06GitHub repository analysis using Repomix packing for deep codebase insights

Use Cases

01Quickly learning a new framework's best practices using its llms.txt file

02Analyzing complex GitHub repositories for undocumented internal logic or patterns

03Researching specific API features across multiple documentation sections in parallel