docs-seeker

Detect topic relevance, fetch llms.txt sources from context7, and analyze documentation.

Updated Dec 23, 2025
One-click install
npx skills add https://github.com/dige04/hieu-ccsetup --skill docs-seeker-dige04
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: docs-seeker
Source: https://github.com/dige04/hieu-ccsetup/tree/main/config/skills/docs-seeker
Command: npx skills add https://github.com/dige04/hieu-ccsetup --skill docs-seeker-dige04

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This tool automates discovery and analysis of technical documentation by detecting query topic relevance, fetching llms.txt sources from context7, and delivering structured results for rapid decision-making.

Core Features & Use Cases

  • Script-first discovery: Detects topic specificity, constructs relevant documentation URLs, and fetches content automatically.
  • Targeted library/topic coverage: Handles topic-specific queries and general library documentation, plus repository-analysis fallbacks.
  • Analytics & distribution planning: Analyzes llms.txt to categorize URLs and recommends agent distribution strategies for efficient work.

Quick Start

Use docs-seeker to automatically detect topic relevance, fetch relevant llms.txt sources from context7, and analyze results to produce a compact report.

Frequently Asked Questions about docs-seeker

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate technical documentation discovery for llms.txt sources?

Automating documentation discovery involves detecting topic relevance and fetching llms.txt sources from context7 to deliver structured results. This approach categorizes fetched URLs and produces an agent-distribution plan for rapid decision-making.

What is the best way to analyze library documentation from a repository?

Analyzing library documentation uses script-first detection to assess topic specificity and fetch relevant content automatically. It includes repository-analysis fallbacks to ensure coverage when standard documentation sources are insufficient.

How do I fetch and categorize documentation URLs using llms.txt?

Fetching and categorizing documentation URLs with llms.txt requires running detection, fetch, and analysis scripts. The process analyzes fetched content to categorize URLs and recommend agent distribution strategies for efficient work.

Can I use script-based documentation analysis for topic-specific queries?

Yes, script-based documentation analysis handles topic-specific queries by detecting relevance and constructing appropriate documentation URLs. It targets both specific topics and general library documentation to provide structured analysis results.

Do I need a configured environment to run documentation detection scripts?

Yes, a configured environment is required to execute the detection, fetch, and analysis scripts. These scripts process topic relevance, retrieve llms.txt sources from context7, and generate structured documentation reports.