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gstack-openclaw-retro

Analyze git history to generate weekly engineering retrospectives with per-author insights.

Updated Apr 18, 2026
Search Tags:#git#analysis#metrics#retrospective#engineering#team#retro
One-click install
npx skills add https://github.com/algorithmbasics/gstack --skill gstack-openclaw-retro-algorithmbasics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gstack-openclaw-retro
Source: https://github.com/algorithmbasics/gstack/tree/main/openclaw/skills/gstack-openclaw-retro
Command: npx skills add https://github.com/algorithmbasics/gstack --skill gstack-openclaw-retro-algorithmbasics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The weekly engineering retrospective summarizes commit activity, work patterns, and code quality trends to reveal team health and shipping momentum, reducing manual toil and enabling data-driven improvements.

Core Features & Use Cases

  • Automatic aggregation of per-author contributions, praise, and growth opportunities across a persistent history.
  • Trend-aware reporting of commits, LOC, hotspots, and session patterns to guide focus and improvements.
  • Telegram-ready narrative that can be shared with stakeholders and the team; supports week-over-week comparisons when memory history exists.

Quick Start

Ask your AI agent to generate this week's engineering retrospective for the current project window.

Frequently Asked Questions about gstack-openclaw-retro

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

FAQPage Schema
How do I generate a weekly engineering retrospective from git history?▼

To generate a weekly engineering retrospective, you can analyze git history to summarize commit activity, work patterns, and code quality trends automatically. It aggregates per-author contributions and identifies team-wide growth opportunities.

What are engineering retrospective metrics and how do they reveal team health?▼

Engineering retrospective metrics include commit counts, lines of code, hotspots, and session patterns. Analyzing these metrics reveals team health and shipping momentum, reducing manual toil and enabling data-driven improvements.

Can I track per-author work patterns and code quality trends over time?▼

Yes, you can track per-author work patterns and code quality trends over time using memory-backed history. This supports week-over-week comparisons and provides persistent tracking of individual contributions and growth opportunities.

How do I share engineering analysis reports with stakeholders via Telegram?▼

You can share engineering analysis reports via Telegram by generating a Telegram-ready narrative from the retrospective data. This format allows the summarized team insights and metrics to be shared directly with stakeholders.

Does weekly retrospective analysis support week-over-week comparisons?▼

Yes, weekly retrospective analysis supports week-over-week comparisons when memory history exists. Saving history to memory allows the analysis to compare current git metrics against previous weeks to identify trends.

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