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gstack-openclaw-retro

Analyze git commit history and code quality metrics for engineering retrospectives.

Updated Apr 8, 2026
Search Tags:#code quality#team awareness#commit history analysis#engineering retro#work session analysis#metrics and trends
One-click install
npx skills add https://github.com/SoSoBurner/GStack --skill gstack-openclaw-retro-sosoburner
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gstack-openclaw-retro
Source: https://github.com/SoSoBurner/GStack/tree/main/openclaw/skills/gstack-openclaw-retro
Command: npx skills add https://github.com/SoSoBurner/GStack --skill gstack-openclaw-retro-sosoburner

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill unit addresses the challenge of organizing and analyzing engineering retro meetings by providing insights into commit history, work patterns, and code quality metrics.

Core Features & Use Cases

  • Weekly Engineering Retrospective: Analyzes commit history, work patterns, and code quality metrics.
  • Team Awareness: Identifies the user running the command and analyzes every contributor's contributions, praise, and growth areas.
  • Metrics and Trends: Computes and presents key metrics like commits, contributions, LOC, test ratio, and PR sizes.
  • Session Patterns: Detects and analyzes work sessions based on commit timestamps.
  • Code Quality Signals: Identifies hotspots, churn, and commit type breakdowns.
  • PR Size Distribution: Estimates PR sizes and buckets them into small, medium, large, and XL categories.
  • Focus Score: Measures the focus of the team on the most-changed directories.
  • Team Member Analysis: Computes and presents metrics for each team member, including commits, LOC, areas of focus, commit type mix, session patterns, test discipline, and biggest ships.
  • Week-over-Week Trends: Tracks trends over time if the window is 14 days or more.
  • Streak Tracking: Counts consecutive days with at least one commit.
  • Load History & Compare: Compares the current retro with the prior same-length retro.
  • Save Retro History: Saves a JSON snapshot of the retro metrics for trend tracking.

Quick Start

Run the /retro command to generate a comprehensive weekly engineering retrospective.

Frequently Asked Questions about gstack-openclaw-retro

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

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

An engineering retrospective analyzes commit history and work patterns to evaluate code quality metrics and team awareness. It computes contributions, LOC, test ratio, and PR sizes to identify growth areas and track week-over-week trends for your team.

What metrics are included in a git commit history analysis for team awareness?▼

Git commit history analysis for team awareness includes commits, LOC, test ratio, PR size distribution, and focus scores. It also evaluates session patterns, commit type mix, streak tracking, and churn hotspots to measure each contributor's growth areas and biggest ships.

How do I track week-over-week trends in code quality and work patterns?▼

To track week-over-week trends in code quality, you need to analyze a window of 14 days or more. The tool saves a JSON snapshot of your retro metrics, allowing you to compare the current retrospective against the prior same-length period for load history comparison.

Can I measure developer focus score and work session patterns from git data?▼

Yes, you can measure developer focus score and work session patterns directly from git data. The analysis detects work sessions based on commit timestamps and calculates a focus score by measuring team concentration on the most-changed directories.

Do I need a specific environment to run code quality and PR size analysis?▼

You need a git repository to run code quality and PR size analysis. The tool requires git to analyze commit history, estimate PR sizes into small, medium, large, and XL buckets, and identify code churn hotspots for your engineering retrospective.

How does engineering retro analysis identify code quality hotspots?▼

Engineering retro analysis identifies code quality hotspots by evaluating code churn and commit type breakdowns across the repository. It isolates highly modified file areas and combines this with PR size distribution to highlight potential stability risks.

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