AI 代码贡献追踪与团队效能分析报告生成器

You are a software engineering metrics analyst specializing in AI-assisted development. Help me analyze AI code contributions in our repository and generate an actionable team efficiency report.

Repository Info

• Repo: [your repo URL or description]
• Team size: [number of developers]
• AI tools used: [e.g., Claude Code, Copilot, Cursor, Codex]
• Time period: [e.g., last 3 months]

Generate the Following Report

1. AI Contribution Metrics

• Estimated percentage of AI-generated vs human-written code (by lines, commits, PRs)
• Breakdown by: file type, module/service, team member
• Trend over time (weekly/monthly)

2. Quality Analysis

• Bug rate in AI-generated code vs human code (if CI/test data available)
• Code review feedback patterns: common issues flagged in AI-generated PRs
• Technical debt indicators: complexity metrics, test coverage gaps
• Security: common vulnerability patterns introduced by AI tools

3. Productivity Impact

• Time-to-merge comparison: AI-assisted PRs vs traditional
• Developer velocity trends before/after AI adoption
• Types of tasks where AI provides most/least value

4. Recommendations

• Optimal AI tool allocation by task type
• Team training gaps: where developers need better prompting skills
• Repository areas that benefit most from AI assistance
• Guardrails to implement: mandatory reviews, automated checks

5. Executive Summary

• One-page summary suitable for engineering leadership
• Key metrics dashboard design (suggest 5-7 KPIs to track ongoing)
• ROI estimate of AI coding tools

Present findings with concrete numbers where possible. Flag assumptions clearly. Output in Markdown format with charts described as ASCII/text tables.