docs-seeker

Locate software documentation via context7 llms.txt URL patterns.

Updated Mar 7, 2026

Search Tags:#llms.txt #github analysis #context7 #api lookup #documentation discovery #fallback strategy

Ready to run

npx skills add https://github.com/MinhHoangDono/antigravity-kit --skill docs-seeker-minhhoangdono

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: docs-seeker
Source: https://github.com/MinhHoangDono/antigravity-kit/tree/main/.agent/skills/docs-seeker
Command: npx skills add https://github.com/MinhHoangDono/antigravity-kit --skill docs-seeker-minhhoangdono

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

It eliminates the time-consuming guesswork of locating correct, up-to-date documentation by automatically discovering relevant sources for a given library, framework, or repository.

Core Features & Use Cases

Topic-aware documentation discovery: Classifies whether a query is topic-specific and selects the most relevant context7 llms.txt-based documentation sources.
Repository and library lookup: Supports API usage verification, GitHub repository documentation analysis, and finding recent features or breaking changes.
URL recommendation for distribution strategy: Analyzes returned llms.txt URLs to guide how an agent should allocate research across multiple sources.

Quick Start

Ask an AI agent to “search documentation for shadcn date picker usage patterns and return the most relevant official and context7-backed sources”.

Frequently Asked Questions about docs-seeker

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

FAQPage Schema

How do I find official documentation for a specific library or GitHub repository?▼

To find official documentation for a library or GitHub repository, this Skill locates relevant sources by classifying topic-specific queries and fetching context7 llms.txt URLs. It applies fallback chains to return the most accurate and up-to-date documentation links.

What is the best way to verify API usage and breaking changes for a framework?▼

The best way to verify API usage and breaking changes for a framework is using context7-based documentation discovery. The Skill analyzes llms.txt patterns to locate recent features, breaking changes, and API lookup sources across topic-specific and general queries.

Does context7 llms.txt discovery work for any software library?▼

Context7 llms.txt discovery works for any software library, framework, or GitHub repository that provides llms.txt documentation patterns. It applies topic detection and URL fetching with fallback chains to ensure broad coverage across topic-specific and general queries.

How do I distribute research across multiple documentation sources?▼

To distribute research across multiple documentation sources, the Skill analyzes returned llms.txt URLs to guide agent allocation. It post-processes fetched URLs to evaluate coverage and recommend a distribution strategy for efficient research across sources.

Why does documentation lookup sometimes fail to return the right source?▼

Documentation lookup might fail to return the right source if the target lacks standard llms.txt patterns or topic detection misclassifies the query. The Skill mitigates this by applying context7-based fallback chains to fetch alternative documentation URLs.

When should I use llms.txt patterns for documentation discovery?▼

You should use llms.txt patterns for documentation discovery when you need to locate correct, up-to-date sources for API usage verification or breaking-change analysis. It eliminates guesswork by automatically discovering relevant sources for a given repository.