retro

Analyze git commit history and code quality metrics to generate engineering retrospective reports.

Updated May 27, 2026
One-click install
npx skills add https://github.com/Shmurdoc/EasyRide-v1 --skill retro-shmurdoc
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: retro
Source: https://github.com/Shmurdoc/EasyRide-v1/tree/main/.opencode/skills/gstack-retro
Command: npx skills add https://github.com/Shmurdoc/EasyRide-v1 --skill retro-shmurdoc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Engineering teams lose context between sprints, struggle to recall what shipped, and miss patterns in individual contributions and code quality trends. Manual retrospectives are often biased, incomplete, and fail to track progress over time.

Core Features & Use Cases

  • Commit History Analysis: Automatically parses git history to identify shipped features, bug fixes, and refactors across the team.
  • Work Pattern Tracking: Monitors commit frequency, PR sizes, and review turnaround to surface bottlenecks and productivity trends.
  • Team-Aware Breakdowns: Generates per-person contribution summaries with constructive praise and growth areas, making retros fair and data-driven.
  • Persistent History: Maintains trend data across sessions so teams can measure improvement in velocity, quality, and collaboration over time.

Quick Start

Use the retro skill to analyze this week's engineering contributions and generate a structured retrospective report with team metrics and individual highlights.

Frequently Asked Questions about retro

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

FAQPage Schema
How do I generate a sprint retrospective from git commit history?

Generate a sprint retrospective from git commit history by analyzing work patterns and code quality metrics to produce structured reports with team praise and growth areas. It parses version control data to identify shipped features, bug fixes, and refactors automatically.

Can I track individual engineering contributions and code quality trends over time?

Track individual engineering contributions and code quality trends over time using persistent history data across sessions. It monitors commit frequency, PR sizes, and review turnaround to surface productivity trends and generate per-person contribution summaries.

What is needed to run automated engineering retrospectives on my repository?

Automated engineering retrospectives require git repository access and gstack tooling to parse version control history. These dependencies allow the system to analyze commit data and produce structured reports with team metrics and individual highlights.

How do data-driven retrospectives compare to manual sprint reviews?

Data-driven retrospectives improve upon manual sprint reviews by eliminating bias and tracking persistent trend data across sessions. They automatically parse git history to surface bottlenecks, monitor code quality, and measure improvement in velocity and collaboration over time.

Are there limitations when analyzing commit frequency for team analytics?

Analyzing commit frequency for team analytics is limited to repositories with accessible git history and gstack tooling. It relies on version control data to monitor work patterns, meaning incomplete commit logs will affect the accuracy of the generated retrospective reports.