retro

Name: retro
Availability: InStock
Author: kit4some

Analyze git history, memory activity, and work patterns to generate structured retro metrics.

4|Updated Mar 21, 2026

Search Tags:#git #analytics #metrics #memory #engineering #workflows #retro

Ready to run

npx skills add https://github.com/Kit4Some/Oh-my-ClaudeClaw --skill retro-kit4some

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: retro
Source: https://github.com/Kit4Some/Oh-my-ClaudeClaw/tree/main/skills/retro
Command: npx skills add https://github.com/Kit4Some/Oh-my-ClaudeClaw --skill retro-kit4some

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Engineering teams often struggle to derive actionable insights from Git history and memory data. This Skill automates data-driven retrospectives by analyzing commits, memory activity, and work patterns to surface trends and improvement opportunities.

Core Features & Use Cases

Automated data collection across git history, memory logs, and task patterns.
Trend analysis and actionable insights for sprint planning, process changes, and memory hygiene.
Use Case: A team runs a weekly retro to identify most impactful changes and memory bottlenecks to inform next sprint planning.

Quick Start

Invoke the /retro command to generate the latest engineering retrospective using stored git and memory data.

Frequently Asked Questions about retro

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

FAQPage Schema

How do I automate engineering retrospectives using git history and memory activity data?▼

Automating engineering retrospectives involves analyzing git commits, memory logs, and work patterns across configurable windows to surface trends. This Skill aggregates data to generate structured metrics, providing leadership-ready insights for sprint planning and process changes.

What is memory hygiene analysis in software engineering workflows?▼

Memory hygiene analysis in software workflows identifies bottlenecks by examining memory usage and activity logs during development cycles. It surfaces actionable insights to optimize task flows and memory storage, informing process improvements for future sprints.

How do I generate data-driven retro metrics for sprint planning from commit history?▼

Generating data-driven retro metrics from commit history requires aggregating git data and task patterns over a configurable window. This Skill analyzes the collected history to identify impactful changes and trends, outputting structured insights for sprint planning.

Do I need access to OpenClaw context hub to analyze engineering work patterns?▼

Yes, accessing the OpenClaw context hub is required to aggregate data for engineering retrospectives. The Skill relies on OpenClaw alongside git and memory storage to analyze work patterns, memory activity, and commits for structured retro metrics.

What's the best way to analyze team work patterns and memory bottlenecks for retros?▼

Analyzing team work patterns and memory bottlenecks for retros is best handled by automated data collection across git history and memory logs. This approach surfaces trends and improvement opportunities, replacing manual reflection with structured, data-driven insights.

Can I configure the analysis window when running automated engineering retros?▼

Yes, you can configure the analysis window when running automated engineering retros. The Skill analyzes git history, memory activity, and task flows across these configurable windows to generate structured retro metrics for the specified timeframe.