ck:docs-seeker

Detect topics and fetch llms.txt documentation from context7.com or GitHub.

Updated Apr 2, 2026
One-click install
npx skills add https://github.com/hidonguyen/trade-ops --skill ck-docs-seeker-hidonguyen
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ck:docs-seeker
Source: https://github.com/hidonguyen/trade-ops/tree/main/.opencode/skills/docs-seeker
Command: npx skills add https://github.com/hidonguyen/trade-ops --skill ck-docs-seeker-hidonguyen

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Quickly locates and retrieves authoritative library and framework documentation by automating URL construction, topic detection, and llms.txt discovery so users don't have to search manually across context7.com, official sites, or GitHub repositories.

Core Features & Use Cases

  • Topic Detection: Extracts library and topic from natural language queries to target topic-specific documentation.
  • Context7 Fetch with Fallbacks: Builds context7.com URLs, tries topic-specific then general endpoints, and falls back to web search or repository analysis when needed.
  • llms.txt Analysis: Parses llms.txt, categorizes URLs into critical/important/supplementary, and suggests agent distribution for downstream research.
  • Use Case: Developers or researcher agents needing focused API pages, installation guides, or targeted component docs for rapid information retrieval and agent orchestration.

Quick Start

Run the detect and fetch scripts to retrieve topic-specific llms.txt results for the query How do I use date picker in shadcn/ui?.

Frequently Asked Questions about ck:docs-seeker

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

FAQPage Schema
How do I locate authoritative library documentation using llms.txt?

To locate library documentation using llms.txt, the system automates topic detection from natural language queries and fetches targeted context7.com endpoints to retrieve relevant docs. It parses the fetched llms.txt file to categorize URLs into critical, important, and supplementary documentation layers.

What is llms.txt and when do I need it for documentation discovery?

llms.txt is a standardized text file that outlines a library's documentation structure for automated retrieval. You need it when orchestrating agent research or fetching targeted API pages, as it allows automated systems to prioritize critical documentation URLs over supplementary guides.

How do I retrieve topic-specific framework documentation from a natural language query?

Retrieving topic-specific framework documentation involves executing topic detection scripts that extract the target library and feature from a natural language query. The system then constructs context7.com URLs, attempting topic-specific endpoints first before falling back to general library documentation.

Does this documentation discovery approach work with libraries hosted on GitHub?

Yes, documentation discovery works with libraries hosted on GitHub by using repository analysis as a fallback. When context7.com endpoints and general web searches do not return the required llms.txt file, the system analyzes the repository directly to extract documentation.

What happens when llms.txt fetch workflows fail to find library docs?

When llms.txt fetch workflows fail to find library docs, the system executes sequential fallbacks. It first attempts a general context7.com endpoint, then falls back to a broader web search, and ultimately performs direct GitHub repository analysis if the library is hosted there.

Do I need Node.js to run context7 documentation retrieval scripts?

Yes, you need Node.js as the runtime environment to execute the topic detection and llms.txt fetch scripts. The documentation discovery workflows rely on Node.js to parse natural language queries and construct the necessary context7.com URLs for retrieval.