Docs Seeker

About

Streamlines the process of finding and understanding technical documentation by leveraging AI-friendly standards like llms.txt and repository-to-XML tools like Repomix. It employs a multi-phase workflow that attempts to find standardized documentation first, falls back to analyzing complete GitHub repositories if needed, and uses parallel explorer agents to aggregate information from multiple sources simultaneously. This ensures developers always have the most relevant and up-to-date technical context for any library or framework, including specific version handling and comprehensive API analysis.

Key Features

• Structured output generation including source methodology, key information, and resource links.
• 0 GitHub stars
• Parallel exploration using multiple agents to crawl and aggregate diverse documentation sections simultaneously.
• Deep repository analysis via Repomix to pack entire codebases into structured AI-ready context.
• Standardized discovery using the llms.txt protocol for AI-optimized documentation access.
• Explicit version handling to retrieve documentation for specific library releases or tags.

Use Cases

• Quickly onboarding onto a new framework or library by fetching the latest AI-friendly documentation.
• Analyzing complex GitHub repositories when official web documentation is sparse or outdated.
• Gathering comprehensive API references and code examples from multiple sources in parallel.