Sprint Velocity Analysis

Analyze sprint velocity data to produce an honest engineering team health report. The goal is not to generate optimistic-looking charts — it is to surface delivery patterns, identify dysfunction early, and give the team and their manager actionable recommendations. Look for: velocity trends (improving, declining, flat, erratic), story point calibration consistency, carry-over patterns that indicate chronic over-commitment, and capacity-related signals. Produce text-based trend visualizations, a health diagnosis, and specific improvement recommendations with measurable targets.

Required Inputs

Ask for these if not already provided:

• Sprint history — for each sprint: sprint name/number, committed story points, completed story points, and number of items carried over to next sprint; ideally 6–8 sprints minimum
• Team size and any changes — current team size and any additions or departures during the data window
• Known disruptions — holidays, company all-hands, on-call incidents, or other events that affected specific sprints
• Cycle time data (optional) — if available, p50 and p90 cycle time per sprint (time from start to done)
• Definition of Done — what "completed" means for this team (merged to main? deployed to prod? accepted by PO?)

If cycle time data is not provided, omit that section and note it as a recommended data source to add.

Output Format