engineer-expertise-extractor

# Engineer Expertise Extractor

Extract and document an engineer's coding expertise by analyzing their GitHub contributions, creating a structured knowledge base that captures their coding style, patterns, best practices, and architectural decisions.

## What This Skill Does

Researches an engineer's work to create a "digital mentor" by:
- **Analyzing Pull Requests** - Extract code patterns, review style, decisions
- **Extracting Coding Style** - Document their preferences and conventions
- **Identifying Patterns** - Common solutions and approaches they use
- **Capturing Best Practices** - Their quality standards and guidelines
- **Organizing Examples** - Real code samples from their work
- **Documenting Decisions** - Architectural choices and reasoning

## Why This Matters

**Knowledge Preservation:**
- Capture expert knowledge before they leave
- Document tribal knowledge
- Create mentorship materials
- Onboard new engineers faster

**Consistency:**
- Align team coding standards
- Replicate expert approaches
- Maintain code quality
- Scale expertise across team

**Learning:**
- Learn from senior engineers
- Understand decision-making
- See real-world patterns
- Improve code quality

## How It Works

### 1. Research Phase
Using GitHub CLI (`gh`), the skill:
- Fetches engineer's pull requests
- Analyzes code changes
- Reviews their comments and feedback
- Extracts patterns and conventions
- Identifies their expertise areas

### 2. Analysis Phase
Categorizes findings into:
- **Coding Style** - Formatting, naming, structure
- **Patterns** - Common solutions and approaches
- **Best Practices** - Quality guidelines
- **Architecture** - Design decisions
- **Testing** - Testing approaches
- **Code Review** - Feedback patterns
- **Documentation** - Doc style and practices

### 3. Organization Phase
Creates structured folders:
```
engineer_profiles/
└── [engineer_name]/
    ├── README.md (overview)
    ├── coding_style/
    │   ├── languages/
    │   ├── naming_conventions.