skill-seekers

Extract structured SKILL.md files from documentation, codebases, and GitHub repositories.

Updated Aug 27, 2013

Search Tags:#documentation #codebase #skills #GitHub #generate #frontmatter #AI-enhancement

Ready to run

npx skills add https://github.com/pkking/dotfiles --skill skill-seekers-pkking

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: skill-seekers
Source: https://github.com/pkking/dotfiles/tree/main/dotfiles/dot_config/opencode/skills/skill-seekers
Command: npx skills add https://github.com/pkking/dotfiles --skill skill-seekers-pkking

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill converts scattered documentation, codebases, and GitHub project data into structured, reusable LLM skills. It generates frontmatter-driven SKILL.md, comprehensive references, and ready-to-integrate content for AI agents.

Core Features & Use Cases

Analyze documentation, codebases, and GitHub repositories to produce skill metadata, API references, and design-pattern insights.
Generate a complete SKILL.md with platform-agnostic frontmatter and linked references, plus a rich reference set for quick API lookups.
Produce machine-readable metadata and human-friendly guides to accelerate AI-driven knowledge extraction and reuse.

Quick Start

Analyze a local codebase: skill-seekers-codebase --directory /path/to/project --output output/skill-seekers/
Package for Claude: skill-seekers package output/skill-seekers/ --no-open
Optionally upload or enhance via AI using the platform of your choice.

Frequently Asked Questions about skill-seekers

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

FAQPage Schema

How do I convert a codebase into structured LLM skills?▼

You can convert a codebase by analyzing local project directories to extract knowledge and generate SKILL.md files with frontmatter metadata, API references, and code examples for AI agents.

What is the best way to generate SKILL.md frontmatter from GitHub repositories?▼

Generating SKILL.md frontmatter from GitHub repositories involves extracting design-pattern insights and API references to produce machine-readable metadata and human-friendly guides for AI-driven knowledge reuse.

Can I use documentation to generate actionable AI agent skills?▼

Yes, you can use documentation to generate actionable AI agent skills by identifying and extracting knowledge from source material to produce reusable skills with integrated references and frontmatter metadata.

Does this skill generation process work without external dependencies?▼

Yes, the skill generation process works without external dependencies, allowing you to analyze codebases and package structured skills with frontmatter and linked references independently.

How do I package generated skills for Claude after analyzing a codebase?▼

You package generated skills for Claude by running the package command on the output directory, consolidating the extracted frontmatter, references, and code examples into a ready-to-integrate format.

What are the limitations when extracting knowledge from scattered codebases?▼

A limitation when extracting knowledge from scattered codebases is that the generated skill relies on source structure, requiring comprehensive documentation and clear design patterns to produce effective AI-enhancement references.