skill-seekers

What This Skill Does

Skill Seekers is a powerful CLI-based automation tool designed to transform fragmented technical information into structured, usable Claude AI Skills. It acts as an ingestion and synthesis engine that bridges the gap between raw data sources—such as documentation websites, GitHub repositories, and complex PDF manuals—and the knowledge base required for high-performance AI agents. By utilizing deep AST parsing for code, OCR for scanned documents, and multi-source conflict resolution, Skill Seekers ensures that your AI agents remain equipped with the most accurate and up-to-date technical insights. Whether you are standardizing internal documentation or creating new framework-specific agents, this tool streamlines the lifecycle of skill development, from initial data scraping to finalized, AI-enhanced knowledge integration.

Installation

To install the Skill Seekers utility directly into your OpenClaw environment, use the provided install command:

clawhub install openclaw/skills/skills/truongvknnlthao-gif/skill-seekers

Alternatively, you can install the engine via Python: pip install skill-seekers

Ensure you have the necessary dependencies by verifying your Python environment. For repository analysis, you may need a GitHub token (set GITHUB_TOKEN) to access private repositories or bypass rate limits.

Use Cases

• Framework Onboarding: Quickly generate a comprehensive knowledge skill for a new language or framework (e.g., React, FastAPI) by scraping official documentation.
• Repository Intelligence: Analyze large, undocumented GitHub repositories to auto-generate code usage patterns and implementation details.
• PDF Knowledge Extraction: Digitize offline technical manuals, research papers, or specification documents into an AI-ready format with table and OCR support.
• Unified Knowledge Bases: Combine scattered documentation and source code into a single, conflict-free skill that reflects both theory and practical implementation.

Example Prompts

1. "Scrape the documentation from https://fastapi.tiangolo.com and create a new skill named 'FastAPI-Expert' with a focus on asynchronous endpoints."
2. "Analyze the repository 'facebook/react' and include the latest issues to identify common debugging patterns for my AI agent."
3. "Run a unified build using 'configs/myframework_unified.json' to merge the latest docs and source code while performing an automated conflict check."

Tips & Limitations

• Efficiency: Use the --async flag with high --workers counts for large documentation sites to significantly reduce processing time.
• Accuracy: When performing multi-source merges, always review the generated output, as rule-based conflict detection can occasionally require manual verification for complex API signatures.
• Security: Be mindful when parsing private repositories; ensure your GITHUB_TOKEN is managed via secure environment variables. For encrypted PDFs, ensure the password is provided at runtime to avoid process hang-ups. The tool is highly effective but works best when you provide structured configuration files (JSON) for repeatable, consistent skill builds.