docs-seeker

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.

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.

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.

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.

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.

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.