Individual skill
sprint-velocity-analysis
Analyze sprint velocity data and produce an engineering team health report covering delivery trends, capacity utilization, and improvement recommendations. Use when asked to analyze sprint velocity, review team delivery health, identify delivery risks, or produce a retrospective data analysis. Produces a velocity trend analysis, health diagnosis table, top improvement recommendations with implementation steps, and a next-sprint capacity forecast.
skills/sprint-velocity-analysis/SKILL.md
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# 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.