cyberdart-openclaw-retro

To conduct an engineering retrospective using git commit history, run the script against your repository to analyze commits, PR metrics, and code quality over a customizable time window. It requires a git repository with activity logs to function.

A code analysis retrospective for team productivity includes metrics on commits, lines of code, pull request sizes, coding session patterns, and frequently changed file hotspots to identify work patterns and areas for growth.

Yes, you can analyze code changes and team contributions for a specific time frame ranging from 7 to 30 days. You simply pass the desired duration as an argument, such as running the script with a 7d or 30d parameter.

Yes, you need to install pypdf2 and matplotlib along with git to run retrospective analysis. These dependencies support the script's code analysis logic and its generation of visual data outputs.

The best way to identify coding session patterns and hotspot files in a git repository is to use a retrospective analysis script that parses commit history to detect productivity impacts and highlight frequently changed files for maintenance awareness.

Pull request size distribution helps with workload management in software engineering by estimating and categorizing PR sizes from commit history. This allows teams to identify uneven workloads and adjust task allocation for better productivity.