mm-retro

To run a sprint retrospective using Git repository data, execute the Skill command to analyze commits and generate project velocity statistics, then follow the structured prompts to capture team feedback and improvement actions.

A structured sprint retrospective is a guided process ensuring comprehensive feedback capture of what shipped, what worked, and what needs improvement. It uses Git data to provide insights into project velocity and code changes for continuous improvement.

Yes, you need Python installed to execute the scripts that generate sprint statistics from Git data. You also need Git repository access so the scripts can analyze project velocity and code changes for the retrospective.

Yes, you can use this for team collaboration to create a concise, actionable retrospective document at the end of a sprint. It captures what shipped, what worked well, and what needs improvement using Git integration and structured feedback.

The best way to integrate code change insights into project management retrospectives is using a Skill that pulls Git data directly to generate project velocity statistics. This provides concrete data on code changes to ground the team's structured feedback.

Limitations when generating project velocity statistics from Git repositories include requiring both Python for script execution and direct Git repository access. Without these dependencies, the Skill cannot analyze code changes or guide the structured retrospective process.