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retro

Analyze commit history, work patterns, and code quality metrics for weekly engineering retrospectives.

Updated Jun 9, 2026
Search Tags:#retrospective#engineering#AI analysis#retro#team insights
One-click install
npx skills add https://github.com/ericdahl-dev/coauthor-cleaner --skill retro-ericdahl-dev
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: retro
Source: https://github.com/ericdahl-dev/coauthor-cleaner/tree/main/.claude/skills/gstack/retro
Command: npx skills add https://github.com/ericdahl-dev/coauthor-cleaner --skill retro-ericdahl-dev

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires Bash, Read, Write, Glob, AskUserQuestion, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps manage engineering retrospectives by analyzing commit history, work patterns, and code quality metrics, providing team insights and suggestions.

Core Features & Use Cases

  • Analyzes Commit History: Breaks down contributions and identifies praise-worthy and growth areas per person.
  • Work Pattern Analysis: Identifies work trends and areas of focus.
  • Code Quality Metrics: Offers insights into code quality and performance.
  • Use Case: Use this Skill during your weekly engineering retrospective to gain a deeper understanding of your team's performance and to suggest improvements.

Quick Start

Invoke the retro skill during your engineering retrospective to review your team's progress and learnings.

Frequently Asked Questions about retro

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

FAQPage Schema
How do I analyze commit history for an engineering retrospective?▼

Engineering retrospective analysis uses commit history, work patterns, and code quality metrics to identify team contributions and areas for improvement. It breaks down individual performance to highlight praise-worthy actions and growth opportunities.

What is AI-driven engineering retrospective analysis?▼

AI-driven retrospective analysis is the process of evaluating weekly engineering progress by examining code metrics and work trends. It provides data-backed insights and suggestions to enhance team performance during review sessions.

How do I run a weekly engineering retrospective using AI insights?▼

Run a weekly engineering retrospective by invoking the analysis tool during your review session. It evaluates code quality metrics and work patterns, delivering targeted suggestions for team improvement.

Does the retrospective analysis require specific tools or environment setup?▼

Retrospective analysis requires Bash, Read, Write, Glob, and AskUserQuestion tools to function. Your environment must support these dependencies to successfully access commit history and generate team insights.

Can I identify work trends and code quality issues for my engineering team?▼

You can identify work trends and code quality issues by analyzing work patterns and commit metrics. This process offers insights into code performance and highlights specific areas where the team should focus improvement efforts.

What is the best way to generate team insights from code quality metrics?▼

Generating team insights from code quality metrics works best by combining commit history analysis with work pattern evaluation. This approach surfaces data-driven suggestions for improvement rather than relying solely on manual review.

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