Analyzes git commits to assess code quality and developer productivity. Uses AI to evaluate rewriteability and business value. Helps engineering managers identify high-impact developers and optimize team performance.
git clone https://github.com/shaoxyz/git-commit-analyzer.gitGit Commit Analyzer uses AI to evaluate git commits across new dimensions designed for the AI era. Instead of relying on traditional metrics like lines of code or commit frequency, it assesses rewriteability (how quickly AI could rewrite the code) and business value (whether the code solves critical problems or represents wasted effort). The tool generates detailed reports with AI survival indices to help engineering managers understand which contributions have lasting impact. It works directly in Claude Code and other AI coding tools, automatically analyzing commit history and producing ranked assessments that reveal true developer impact beyond surface-level productivity metrics.
Install with `npx skills add shaoxyz/git-commit-analyzer` and run `/git-commit-analyzer` in Claude Code or compatible AI tools. Optionally specify a repository path and time range with `--repo` and `--since` flags. The tool automatically fetches commits, analyzes code, and generates an interactive HTML report with detailed rankings and metrics.
Evaluate developer contributions beyond line counts and commit frequency
Identify high-impact code changes that solve business-critical problems
Assess code quality through AI rewriteability metrics
Generate team performance reports with AI-era productivity insights
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/shaoxyz/git-commit-analyzerCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Analyze the following git commits for [COMPANY] in the [INDUSTRY] sector. Evaluate the code quality, rewriteability, and business value of each commit. Identify high-impact developers and suggest team performance optimizations. Provide a detailed report with specific examples and actionable insights. [DATA]
# Git Commit Analysis Report ## Overview The following analysis evaluates 30 recent git commits from the engineering team at TechCorp, a fintech company. The commits span a two-week sprint focused on enhancing the payment processing module. ## Key Findings ### Code Quality - **High Rewriteability**: 65% of commits show clean, modular code with clear documentation. - **Low Rewriteability**: 20% of commits contain tightly coupled functions and minimal comments. - **Business Value**: 75% of commits directly enhance user experience or system stability. ### High-Impact Developers - **Developer A**: Contributed 12 commits, all with high rewriteability and significant business value. Focused on improving API response times. - **Developer B**: Contributed 8 commits, with a mix of high and low rewriteability. Specialized in database optimizations. ## Recommendations 1. **Code Reviews**: Schedule pair programming sessions for Developer B to improve code quality. 2. **Training**: Organize a workshop on modular design principles for the team. 3. **Recognition**: Highlight Developer A's contributions in the next team meeting to boost morale. ## Detailed Commit Analysis ### Commit Example 1 **Author**: Developer A **Business Value**: High **Rewriteability**: High ```python # Improved payment processing API endpoint # Reduced response time by 40% by optimizing database queries ``` ### Commit Example 2 **Author**: Developer B **Business Value**: Medium **Rewriteability**: Low ```python # Updated user authentication logic # Tightly coupled with existing session management ```
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