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Himanshu-Sangshetti
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retro

Analyzes Git history to generate data-driven engineering retrospective reports.

6|1|Updated Mar 14, 2026
Search Tags:#metrics#engineering#postmortem#velocity#git-history#retro#team-performance
One-click install
npx skills add https://github.com/Himanshu-Sangshetti/cursor-stack --skill retro-himanshu-sangshetti
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: retro
Source: https://github.com/Himanshu-Sangshetti/cursor-stack/tree/main/retro
Command: npx skills add https://github.com/Himanshu-Sangshetti/cursor-stack --skill retro-himanshu-sangshetti

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Engineering managers need objective, data-backed insights to understand what happened over a period, identify patterns, and drive improvements.

Core Features & Use Cases

  • Data Gathering: Collects Git history, commits per author, files changed, and lines of code to establish context.
  • Metrics & Patterns: Calculates key metrics (commits, LOC, test ratios, PRs) and identifies recurring patterns and hotspots.
  • Actionable Recommendations: Generates concrete improvements and next steps for the team.
  • Use Case: Weekly retrospectives or sprint postmortems to improve velocity and collaboration.

Quick Start

Run the retro workflow to generate a weekly retrospective for your engineering team.

Frequently Asked Questions about retro

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

FAQPage Schema
How do I generate a data-driven engineering retrospective from Git history?▼

Generate a data-driven engineering retrospective by analyzing Git history within a defined time window to output quick stats, pattern insights, and actionable recommendations for your team.

What engineering metrics are needed for a sprint postmortem?▼

Sprint postmortems require engineering metrics like commits per author, lines of code changed, test ratios, and PR counts to identify recurring patterns and hotspots for team improvement.

Can I use Git commit history to identify engineering team performance patterns?▼

You can use Git commit history to identify engineering team performance patterns by calculating metrics like commits, LOC, and test ratios to highlight recurring hotspots and collaboration trends.

How do I run a weekly retrospective to improve engineering velocity?▼

Run a weekly retrospective to improve engineering velocity by gathering Git activity data, calculating key metrics, and generating concrete recommendations to drive team collaboration improvements.

Do I need a defined time window to analyze engineering activity for a retrospective?▼

You need a defined time window and Git history access to analyze engineering activity, enabling the system to accurately calculate metrics and deliver actionable retrospective insights.

What is the best way to analyze engineering activity for performance dashboards?▼

The best way to analyze engineering activity for performance dashboards is extracting Git history metrics to establish context, identify patterns, and generate concrete improvement steps.

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