Analyzes weekly engineering activity from commit history, PR cadence, and quality signals to produce a retrospective.
npx skills add https://github.com/legotec73/gstack --skill retro-legotec73
Please help me install this Agent Skill. Skill: retro Source: https://github.com/legotec73/gstack/tree/main/retro Command: npx skills add https://github.com/legotec73/gstack --skill retro-legotec73
Weekly retrospectives can be time-consuming and opaque. This skill provides a structured, data-driven approach by analyzing commit history, PR activity, and code quality to surface praise and growth areas with persistent history and trend tracking.
Run /retro to generate the weekly retrospective for the current project.
High-intent search queries and answers about installing and using this skill.
To generate a data-driven engineering retrospective from commit history, you can run a command to analyze repository history, PR cadence, and code quality signals. This produces structured outputs to guide sprint planning and team coaching.
The best way to analyze team engineering metrics for weekly sprint reviews is by inspecting repository history and PR cadence to surface praise and growth areas. This data-driven approach replaces opaque retrospectives with per-person contribution insights.
Yes, you can compare engineering activity and trends across multiple projects. The analysis enables cross-project global retros by comparing windows and showing team-wide trends to guide process changes.
Generating a code history retrospective does require persistent repository data. The analysis relies on persistent history to accurately track trend-based insights and deliver structured outputs for team coaching.
To identify individual growth areas and coaching opportunities from PR activity, the retrospective breaks down contributions per person. It analyzes quality signals to surface specific praise and targeted growth opportunities.
A key limitation when tracking team growth metrics from code history is the reliance on persistent history. Without continuous repository data and consistent PR cadence, trend-based insights and cross-project comparisons may be incomplete.
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