Agent skill · Data & Analytics

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.

mohitagw158561,255★ · 1 repos on radarProfile →
claude-codecursorMIT
Install
npx skills add mohitagw15856/pm-claude-skills --skill sprint-velocity-analysis --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 13 KB
Bundled scripts: none
Path: skills/sprint-velocity-analysis/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,255
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 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) - **Defin

What's inside
Steps it walks through
  1. Required Inputs
  2. Output Format
  3. Velocity Trend
  4. Raw Data
  5. Velocity Chart (Completed Points per Sprint)
  6. Trend Diagnosis
  7. Story Point Calibration
  8. Carry-Over Pattern Analysis
  9. Capacity Utilization
  10. Health Diagnosis
  11. Blocker Frequency Analysis
  12. Improvement Recommendations
  13. Recommendation 1: [Title]
  14. Recommendation 2: [Title]
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About this skill
What does the sprint-velocity-analysis skill do?

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.

How do I install it?

Run `npx skills add mohitagw15856/pm-claude-skills --skill sprint-velocity-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From mohitagw15856/pm-claude-skills, a repository with 1,255 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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