Analyze Git history and contributor activity to generate weekly engineering retrospectives.
npx skills add https://github.com/yolopunk/jedi --skill retro-yolopunk
Please help me install this Agent Skill. Skill: retro Source: https://github.com/yolopunk/jedi/tree/main/.claude/skills/gstack/retro Command: npx skills add https://github.com/yolopunk/jedi --skill retro-yolopunk
Weekly engineering retrospectives help teams understand what happened in the last period, celebrate successes, and identify concrete growth opportunities across individuals and codebases.
Run /retro to generate the weekly engineering retrospective for the default 7-day window.
High-intent search queries and answers about installing and using this skill.
To generate a weekly engineering retrospective, run the analysis against your project's Git history to compute metrics on commits, lines of code, and contributor activity. It produces a structured summary of team praise and growth opportunities for a default 7-day window.
You can analyze contributor activity for custom time ranges by specifying explicit windows such as 24h, 14d, or 30d. The analysis also supports a compare mode to contrast current contributor metrics and code quality signals with prior periods.
A codebase retrospective includes engineering metrics on commit velocity, lines of code, test proxy signals, and code hotspots. It also provides per-author leadership views, highlighting individual contributions alongside specific praise and growth opportunities.
The retrospective analysis supports optional signals like Greptile history and backlog status when that data exists. Integrating these optional inputs enriches the structured output, providing deeper context for weekly engineering summaries and dashboards.
You compare current engineering metrics with previous periods by using the built-in compare mode. This feature contrasts current windowed analytics, such as shipping velocity and test discipline, against prior ranges to highlight team growth and codebase trends.
Tracking team growth opportunities from commit history is best handled by analyzing per-author activity and code quality signals. This approach identifies specific areas for individual improvement while generating team-aware praise based on recent Git contributions.
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