Analyze commit history and per-author contributions to generate a week-long retrospective.
npx skills add https://github.com/NaKMiers/Port4lio --skill retro-nakmiers
Please help me install this Agent Skill. Skill: retro Source: https://github.com/NaKMiers/Port4lio/tree/main/.agents/skills/retro Command: npx skills add https://github.com/NaKMiers/Port4lio --skill retro-nakmiers
This summary helps engineering teams reflect on past work by aggregating commit history, per-person contributions, and code-quality signals into a concise, actionable retrospective.
Type /retro to generate the current week's retrospective for the default 7-day window.
High-intent search queries and answers about installing and using this skill.
To generate an engineering retrospective from git commit history, you can use a tool that analyzes per-author contributions and code-quality signals to produce a team-aware weekly summary. It aggregates repository data into actionable insights.
Analyzing code-quality signals improves weekly sprint retrospectives by surfacing specific hotspots and PR activity patterns. This allows teams to move beyond subjective memories and base their reflections on concrete repository metrics.
Yes, you can run a retrospective across multiple projects. The tool supports global retrospectives that aggregate commit history and per-author contributions across different repositories to provide a comprehensive team overview.
The best way to surface per-author praise and growth areas is to analyze individual commit contributions and code-quality metrics. This creates a structured narrative that highlights specific achievements and targeted growth opportunities.
You can adjust the time window for a sprint retrospective analysis by specifying a custom compare window. While the default generates a 7-day retrospective, the tool supports configurable sprint windows to match your team's cadence.
No, this team retrospective tool does not require external dependencies to calculate metrics. It relies entirely on built-in repository data analysis to process commit history and code-quality signals into a structured narrative.
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