forensic-change-coupling

Analyze Git history to identify files that frequently change together.

3|2|Updated Oct 27, 2025
One-click install
npx skills add https://github.com/AlabamaMike/forensic-skills --skill forensic-change-coupling
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: forensic-change-coupling
Source: https://github.com/AlabamaMike/forensic-skills/tree/main/.claude/skills/forensic-change-coupling
Command: npx skills add https://github.com/AlabamaMike/forensic-skills --skill forensic-change-coupling

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you uncover files that frequently change together by analyzing Git history, revealing temporal coupling and architectural violations that inform refactoring decisions and help reveal the system's actual boundaries.

Core Features & Use Cases

  • Identify strong couplings and coupling clusters by analyzing co-changes across commits.
  • Flag cross-module couplings and architectural violations to guide boundary definitions.
  • Provide integration guidance with other forensic skills to plan targeted refactors and track impact over time.

Quick Start

  • Run forensic-change-coupling on your Git repository to compute coupling data from the history (e.g., last 12 months).
  • Review top coupled file pairs and clusters to identify refactoring opportunities and architectural improvement targets.
  • Use recommended next steps with other skills (forensic-hotspot-finder, forensic-knowledge-mapping, forensic-refactoring-roi) to plan and value-refactor initiatives.

Frequently Asked Questions about forensic-change-coupling

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

FAQPage Schema
How do I identify temporal coupling and shotgun surgery patterns in my Git history?

Temporal coupling analysis detects files that frequently change together in Git history, revealing hidden cross-module dependencies and architectural violations. It computes co-change frequency to guide module boundary definitions and prioritize refactoring targets.

How do I detect cross-module architectural violations from commit history?

You detect cross-module architectural violations by analyzing commit co-changes to flag files from different modules that frequently change together. This quantifies temporal coupling scores to reveal boundary violations and guide architecture refactoring planning.

Can I use change coupling analysis on large codebases with extensive commit history?

Yes, change coupling analysis applies to codebases of varying sizes. By computing co-change frequency from Git history, it scales to reveal temporal coupling clusters and architectural violations regardless of repository scale.

What is the best way to quantify co-change frequency for architecture refactoring?

The best way to quantify co-change frequency is analyzing Git commit history to compute coupling scores for file pairs. This identifies strong coupling clusters and cross-module dependencies, providing data to guide refactoring decisions.

How do I find coupled file clusters to plan targeted module refactors?

Find coupled file clusters by analyzing Git history to compute co-change frequency, identifying groups of files that consistently change together. This reveals strong temporal coupling clusters to plan targeted refactors and track impact over time.