Generate code and project health reports from Git history.
npx skills add https://github.com/TNHoang2708/Gym_Ver2 --skill ck-retro-tnhoang2708
Please help me install this Agent Skill. Skill: ck:retro Source: https://github.com/TNHoang2708/Gym_Ver2/tree/main/.claude/skills/retro Command: npx skills add https://github.com/TNHoang2708/Gym_Ver2 --skill ck-retro-tnhoang2708
This Skill streamlines the post-sprint analysis by automating the collection and interpretation of code health and project metrics directly from Git history, ensuring a comprehensive and data-driven retrospective.
Execute the ck:retro command with the desired timeframe, e.g., ck:retro 1m to get a report for the last month.
High-intent search queries and answers about installing and using this skill.
You can generate a retrospective report by running the analysis command with a desired timeframe, such as `ck:retro 1m` for the last month. It collects Git metrics like commits, churn, and hotspots, and outputs a structured markdown or HTML report.
Git history analysis can extract code health metrics such as commit type distribution, lines of code, hotspots, churn rate, velocity, and test-to-code ratio. These indicators provide data-driven insights for post-sprint reviews.
Yes, Git is required for data retrieval and analysis to compute project health metrics. The tool directly analyzes your Git history to gather data and generate comprehensive retrospective reports.
Yes, you can export retrospective reports in either markdown or HTML format. This allows for easy review and action planning during post-sprint reviews, weekly check-ins, and review periods.
Automating code churn and velocity analysis is best handled by running the retrospective command with a weekly timeframe parameter. It automatically computes health indicators from Git history and outputs a structured report.
Git history analysis automates the collection and interpretation of code health metrics directly from commit data, ensuring a data-driven retrospective. Manual tracking requires gathering these indicators by hand, which is less efficient for post-sprint reviews.
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