What is agent distribution strategy?

Based on the volume of documentation found, the skill's scripts recommend whether one or multiple agents should process the content to ensure comprehensive coverage.

What is the primary benefit of using Docs Seeker?

Docs Seeker automates the search for technical documentation, ensuring Claude receives the most relevant context using the llms.txt standard without manual URL searching.

What sources does Docs Seeker use?

It primarily leverages context7.com and the llms.txt standard to find LLM-optimized documentation for libraries, frameworks, and repositories.

How does it handle token usage?

It uses local Node.js scripts for query detection and result analysis, which results in zero-token overhead for the initial classification and strategy phases.

Docs Seeker

Name: Docs Seeker
Author: wollfoo

bywollfoo

학습 및 문서화

Automates the discovery and analysis of technical documentation using the llms.txt standard to provide context-aware developer resources.

소개

Docs Seeker is a specialized utility designed to streamline how developers locate and process technical documentation within Claude Code. By utilizing a script-first workflow, it identifies whether a user needs specific component details or broad library overviews, fetches high-quality resources via the llms.txt standard (using context7.com), and analyzes results to recommend optimal agent distribution strategies. This approach ensures token-efficient context retrieval while handling complex fallback chains for GitHub repositories and API references automatically.

주요 기능

Automated topic detection to distinguish between general and feature-specific queries
0 GitHub stars
Script-driven documentation retrieval utilizing the llms.txt standard
Zero-token execution for query classification and URL construction
Integrated fallback logic for repository-level analysis when documentation is sparse
Intelligent analysis of documentation density to suggest multi-agent workflows

사용 사례

Automating documentation discovery for GitHub repositories during the development cycle
Quickly finding specific component documentation for UI libraries like Shadcn or Tailwind
Mapping out comprehensive documentation sets for large frameworks like Next.js

소개

주요 기능

Automated topic detection to distinguish between general and feature-specific queries
0 GitHub stars
Script-driven documentation retrieval utilizing the llms.txt standard
Zero-token execution for query classification and URL construction
Integrated fallback logic for repository-level analysis when documentation is sparse
Intelligent analysis of documentation density to suggest multi-agent workflows

사용 사례

Automating documentation discovery for GitHub repositories during the development cycle
Quickly finding specific component documentation for UI libraries like Shadcn or Tailwind
Mapping out comprehensive documentation sets for large frameworks like Next.js