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retro

Analyze git commit history and code metrics to generate engineering retrospectives.

1|Updated Oct 9, 2025
Search Tags:#code quality#git#analytics#productivity#retrospective#engineering
One-click install
npx skills add https://github.com/gth-ai/hadriengayap.github.io --skill retro-gth-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: retro
Source: https://github.com/gth-ai/hadriengayap.github.io/tree/main/.claude/skills/gstack/retro
Command: npx skills add https://github.com/gth-ai/hadriengayap.github.io --skill retro-gth-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the guesswork in team performance reviews by automatically analyzing git commit history to provide objective insights into work patterns, code quality, and team velocity.

Core Features & Use Cases

  • Automated Metrics: Calculates commit frequency, test coverage ratios, and PR size distribution to identify bottlenecks.
  • Team-Aware Analysis: Provides personalized praise and growth opportunities for every contributor based on their specific code contributions.
  • Use Case: Use this at the end of every week to generate a comprehensive report that highlights your team's shipping streak, identifies hotspots in the codebase, and tracks trends in code quality over time.

Quick Start

Run the retro skill to generate an engineering retrospective for the last seven days.

Frequently Asked Questions about retro

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate an engineering retrospective from git commit history?▼

To generate an engineering retrospective, run the retro skill to parse git commit logs and calculate metrics like commit frequency, test coverage ratios, and PR size distribution for your selected time window.

What is data-driven weekly engineering retrospective analysis?▼

Data-driven engineering retrospectives analyze git commit history and code metrics to provide objective insights into work patterns, code quality, and team velocity, replacing guesswork in team performance reviews.

Can I track individual contributor performance using git analytics?▼

Yes, git analytics supports contributor-specific feedback by parsing individual code contributions to provide personalized praise and identify growth opportunities for every team member.

Do I need local shell execution and git access to analyze code metrics?▼

Yes, you need local shell execution and git access because the skill parses commit logs directly from your repository and persists historical JSON snapshots for trend analysis.

How do I track code quality trends over time for my development team?▼

You can track code quality trends over time by running the skill weekly, which persists historical JSON snapshots of your code metrics to compare performance and identify bottlenecks across sessions.

What's the best way to identify codebase hotspots and shipping bottlenecks?▼

Analyzing PR size distribution and commit frequency from your git history is the best way to identify codebase hotspots and bottlenecks, generating a comprehensive report of your team's shipping streak.

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