code-forensics

What problem does it solve?

Understanding large or unfamiliar codebases can be challenging, making it hard to identify existing patterns, measure complexity, detect duplication, or grasp architectural structure. This skill provides deep analytical insights into the codebase, helping to assess code quality and technical debt.

Core Features & Use Cases

• Pattern Identification: Find specific code patterns like error handling, caching, validation, or database interactions across the entire codebase.
• Complexity Analysis: Measure cyclomatic complexity, lines of code, and function/class counts to identify complex "hot spots."
• Duplication Detection: Automatically identify duplicate code snippets, suggesting refactoring opportunities to reduce redundancy.
• Architectural Analysis: Analyze component relationships, dependencies, and imports to understand the codebase's overall structure.
• Use Case: An architect needs to perform a code quality assessment. They use this skill to quickly identify areas of high complexity, significant code duplication, and inconsistent patterns, informing their technical debt reduction strategy.

Quick Start

# Find all error handling patterns in the codebase
python scripts/code_forensics.py find_patterns --pattern error_handling

# Analyze code complexity for a specific file
python scripts/code_forensics.py analyze_complexity --file coffee_maker/auth/jwt.py

# Identify duplicate code across the project
python scripts/code_forensics.py identify_duplication