gstack-openclaw-retro

Automated engineering retrospectives are generated by analyzing git commit history to calculate team performance metrics. The Skill processes commit logs, file changes, and session detection to identify work patterns, code hotspots, and individual contributor growth areas.

A git analytics retrospective report includes commit volume, PR size, and test ratios. It also provides per-author leaderboards, identifies code hotspots, and tracks individual shipping streaks to measure engineering velocity and team health.

Git access to the repository is required to generate team performance metrics. The Skill calculates insights by directly processing repository data from commit logs and file changes rather than relying on external integrations.

To identify code hotspots and contributor growth areas, run the Skill to process repository data and session detection. It analyzes commit logs and file changes to pinpoint heavily modified areas of the codebase and tracks individual author progress.

Git commit analysis is highly effective for weekly sprint reviews and team insights. Running the Skill at the end of the week produces a data-backed summary of what the team shipped, where they focused, and how to improve for the next sprint.

The best way to track engineering velocity using git logs is to automate commit history analysis to calculate work patterns and code quality metrics. This approach solves visibility gaps by detecting coding sessions and generating per-author leaderboards.