docs-seeker

Name: docs-seeker
Availability: InStock
Author: nguyenvanlinh1902

Automate library and framework documentation discovery via topic-aware llms.txt lookups.

Updated Dec 16, 2025

Search Tags:#automation #library #discovery #docs #llms.txt #context7 #topic-detection

Ready to run

npx skills add https://github.com/nguyenvanlinh1902/trackingSolar --skill docs-seeker-nguyenvanlinh1902

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: docs-seeker
Source: https://github.com/nguyenvanlinh1902/trackingSolar/tree/main/.opencode/skill/docs-seeker
Command: npx skills add https://github.com/nguyenvanlinh1902/trackingSolar --skill docs-seeker-nguyenvanlinh1902

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill automates the discovery of library and framework documentation by locating relevant llms.txt resources and official docs using a topic-aware, script-driven workflow, reducing manual search time.

Core Features & Use Cases

Script-first discovery: detect-topic.js, fetch-docs.js, and analyze-llms-txt.js coordinate to fetch a curated list of URLs.
Topic-specific and general queries: handles precise feature queries as well as broad library lookups.
Automatic fallbacks: gracefully degrades from topic URLs to general docs and repo analyses when needed.
Agent-guided retrieval: provides analysis and guidance on how to deploy agents to synthesize results.

Quick Start

Ask a library question to trigger the end-to-end discovery workflow and retrieve targeted docs.

Frequently Asked Questions about docs-seeker

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

FAQPage Schema

How do I automate library documentation discovery for API references?▼

Automating library documentation discovery uses a script-first workflow with topic detection and llms.txt lookups to fetch curated API reference URLs from official sites and GitHub. It coordinates scripts to handle precise feature queries and broad library lookups automatically.

What is llms.txt and how does it work for finding framework docs?▼

The llms.txt mechanism provides structured documentation resources for frameworks. Analyzing llms.txt allows scripts to extract targeted URLs for official docs and API references, enabling rapid, automated retrieval of technical documentation across official sites and repositories.

Can I retrieve topic-specific docs from Context7 and GitHub repositories?▼

Yes, you can retrieve topic-specific docs from Context7 and GitHub repositories. The discovery workflow constructs targeted URLs based on detected topics and applies automatic fallbacks, gracefully degrading from specific topic URLs to general docs and repository analyses when needed.

What is the best way to handle fallbacks when official library docs are missing?▼

The best way to handle missing official library docs is using an automatic fallback workflow that degrades from topic-specific URLs to general documentation and repository analyses. This script-driven approach ensures you still retrieve relevant technical context when primary sources fail.

Do I need agent-based retrieval to synthesize documentation lookup results?▼

You need agent-based retrieval to synthesize documentation lookup results after the scripts fetch them. The workflow provides guidance on deploying agents to analyze and synthesize the curated URLs, ensuring the fetched documentation is processed into targeted, usable context.

Why does my topic detection fail on broad library lookups without specific features?▼

Topic detection may fail on broad library lookups without specific features because the scripts are optimized for precise feature queries. The workflow handles this by applying automatic fallbacks to general docs and repository analyses, ensuring broad queries still return relevant results.