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retro

Analyze commit history and code-quality metrics to summarize weekly engineering retrospectives.

Updated Apr 7, 2026
Search Tags:#git#metrics#engineering#growth#code-quality#retro#team-performance
One-click install
npx skills add https://github.com/zz8011/harnesstest --skill retro-zz8011
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: retro
Source: https://github.com/zz8011/harnesstest/tree/main/.claude/skills/gstack/retro
Command: npx skills add https://github.com/zz8011/harnesstest --skill retro-zz8011

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Weekly engineering retrospectives are hard to recall past decisions and measure team progress. This skill automates the analysis of commits, work patterns, and code-quality metrics to generate a persistent historical view and constructive growth insights.

Core Features & Use Cases

  • Analyze commit history, work patterns, and quality metrics with a persistent history and trend tracking.
  • Break down results by contributor to highlight praise and growth areas.
  • Proactively suggest improvements at the end of each sprint or week.

Quick Start

Tell Claude to run a weekly retro for your team to see a summary of the past sprint.

Frequently Asked Questions about retro

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

FAQPage Schema
How do I automate a weekly engineering retro using git commit history?▼

You can automate a weekly engineering retro by analyzing git commit history, work patterns, and code-quality metrics to generate a structured narrative that highlights team contributions and growth opportunities.

What is an engineering retrospective and how does code quality tracking work?▼

An engineering retrospective analyzes repository history to compute code-quality metrics, tracking persistent trends and work patterns to reveal team performance and propose proactive improvements at the end of each sprint.

Can I break down engineering metrics by contributor to highlight individual growth areas?▼

Yes, you can break down engineering metrics by contributor to analyze individual commit history and work patterns, producing per-person insights that highlight specific praise and growth areas for the team.

What's the best way to measure team performance and shipped work for a sprint?▼

The best way to measure team performance for a sprint is to compute code-quality metrics from repository history, producing a structured narrative that summarizes what was shipped and identifies team-wide growth opportunities.

Do I need any external dependencies to generate a team performance retrospective?▼

No external dependencies are required to generate a team performance retrospective; the analysis directly reads repository history to compute metrics and produce structured insights without additional tool integrations.

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