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untangledfinance
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docs-seeker

Classify user queries and fetch technical documentation via context7 llms.txt URLs.

Updated May 24, 2025
Search Tags:#documentation#API#technical writing#libraries#search#GitHub#knowledge discovery
One-click install
npx skills add https://github.com/untangledfinance/untangled-web --skill docs-seeker-untangledfinance
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: docs-seeker
Source: https://github.com/untangledfinance/untangled-web/tree/main/docs-seeker
Command: npx skills add https://github.com/untangledfinance/untangled-web --skill docs-seeker-untangledfinance

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the complex process of finding precise technical documentation, eliminating manual searching across various platforms. It intelligently detects query types, fetches relevant information from curated sources, and even suggests optimal agent distribution for comprehensive analysis, saving significant research time.

Core Features & Use Cases

  • Intelligent Query Detection: Uses detect-topic.js to classify queries as topic-specific or general, extracting keywords for highly targeted searches.
  • Automated Documentation Fetching: Employs fetch-docs.js to construct and query context7.com URLs, handling robust fallback strategies (topic-specific -> general -> repository analysis) automatically.
  • Agent Distribution Strategy: Leverages analyze-llms-txt.js to categorize URLs by priority and recommend an optimal agent distribution strategy (e.g., single, parallel, phased) for efficient processing of results.
  • Use Case: You need to quickly understand "How to use date picker in shadcn/ui?". This skill will automatically identify "date" as the topic and "shadcn/ui" as the library, fetch the most relevant documentation, and present it to you, bypassing hours of manual searching and filtering.

Quick Start

Find documentation on "Next.js caching strategies".

Frequently Asked Questions about docs-seeker

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

FAQPage Schema
How do I find API documentation for a specific library or framework?▼

This Skill automatically detects your library name and fetches its API documentation by constructing targeted queries to authoritative sources, then returns structured results without manual searching across multiple platforms.

Can I search for documentation on specific features or components within a library?▼

Yes. The Skill classifies topic-specific queries, extracts feature keywords like "date picker" or "caching strategies," and retrieves documentation scoped to those components, bypassing general results.

What happens if documentation isn't found for my exact query?▼

The Skill implements automatic fallback strategies: it attempts topic-specific searches first, then falls back to general library documentation, and finally to repository analysis, ensuring comprehensive coverage.

How does this approach differ from manual documentation searching?▼

Manual searching requires visiting multiple platforms and filtering results; this Skill intelligently detects query intent, fetches curated documentation sources, and recommends optimal agent distribution for parallel processing, saving hours of research time.

Can I use this with GitHub repositories and multiple documentation sources?▼

Yes. The Skill works across libraries, repositories, and knowledge bases by constructing context7.com URLs with library and topic parameters, handling multiple sources and fallbacks automatically.

What's the recommended workflow after fetching documentation results?▼

The Skill outputs structured results and suggests agent distribution strategies—single, parallel, or phased—enabling downstream agents to analyze and synthesize documentation efficiently based on complexity and scope.

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