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scrum-master

Analyze sprint data to forecast velocity and generate health scores.

Updated Apr 16, 2026
Search Tags:#analytics#retrospective#agile#scrum#velocity#forecast#team-health
One-click install
npx skills add https://github.com/devCharuzu/philfida-taskmanage --skill scrum-master-devcharuzu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scrum-master
Source: https://github.com/devCharuzu/philfida-taskmanage/tree/main/.windsurf/skills/scrum-master
Command: npx skills add https://github.com/devCharuzu/philfida-taskmanage --skill scrum-master-devcharuzu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Advanced Scrum Master skill that enables data-driven coaching by forecasting sprint velocity, assessing agile health, and surfacing improvement opportunities through integrated analyses of velocity, health, and retrospectives.

Core Features & Use Cases

  • Velocity forecasting with Monte Carlo simulations to provide confidence intervals for sprint planning and release timing.
  • Multi-dimensional team health scoring across Commitment Reliability, Scope Stability, Blocker Resolution, Ceremony Engagement, Story Completion, and Velocity Predictability.
  • Retrospective analysis to track action-item completion, recurring themes, and team-maturity trends.
  • On-demand coaching support for sprint planning, standups, backlog refinement, and blockers.

Quick Start

Provide a sprint data JSON file and run the three scripts to generate forecasts, health scores, and retrospective insights.

Frequently Asked Questions about scrum-master

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I forecast sprint velocity for release planning?▼

Sprint velocity forecasting uses Monte Carlo simulations on historical sprint data to generate confidence intervals, helping predict realistic completion ranges for upcoming release planning.

What is team health scoring in agile analytics?▼

Team health scoring evaluates sprint performance across six dimensions: Commitment Reliability, Scope Stability, Blocker Resolution, Ceremony Engagement, Story Completion, and Velocity Predictability.

How do I track retrospective action items and recurring themes?▼

Retrospective analysis processes sprint data to track action-item completion rates, identify recurring themes across iterations, and measure team-maturity trends over time for continuous improvement.

Can I use Python scripts to analyze sprint data without external dependencies?▼

Yes, the sprint health and velocity analysis runs entirely through standalone Python scripts like velocity_analyzer.py and sprint_health_scorer.py, requiring no external library dependencies.

What format does sprint data need to be in for agile health analysis?▼

Sprint health analysis requires a JSON file containing your sprint records, which the Python scripts process to output health scores, velocity forecasts, and retrospective improvement recommendations.

When should I not rely on Monte Carlo velocity forecasts for sprint planning?▼

Monte Carlo velocity forecasts are less reliable when historical sprint data is sparse or highly inconsistent, as limited data points reduce the statistical confidence of the predictive intervals generated.

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