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scrum-master

Analyze Scrum team performance from JSON sprint data with Python scripts.

2|Updated Mar 13, 2026
Search Tags:#project management#agile#data analysis#coaching#scrum#team performance
One-click install
npx skills add https://github.com/zhangzhang-111-i/claude-skills111 --skill scrum-master-zhangzhang-111-i
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scrum-master
Source: https://github.com/zhangzhang-111-i/claude-skills111/tree/main/project-management/scrum-master
Command: npx skills add https://github.com/zhangzhang-111-i/claude-skills111 --skill scrum-master-zhangzhang-111-i

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides advanced, data-driven analysis of Scrum team performance, enabling objective insights into sprint execution, team health, and continuous improvement.

Core Features & Use Cases

  • Data-Driven Insights: Leverages Python scripts to analyze sprint data exports (e.g., from Jira).
  • Predictive Forecasting: Uses Monte Carlo simulations for reliable sprint completion forecasts.
  • Team Health Scoring: Assesses team well-being across multiple dimensions.
  • Retrospective Analysis: Tracks action items, themes, and sentiment trends.
  • Use Case: A Scrum Master can use this Skill to generate a comprehensive report on the team's velocity predictability, identify key areas for improvement based on health scores, and get actionable recommendations for the next retrospective.

Quick Start

Analyze the provided sprint data JSON file using the scrum master skill to generate a detailed health report.

Frequently Asked Questions about scrum-master

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

FAQPage Schema
How do I analyze Scrum team performance using Jira sprint data exports?▼

Assess team health by processing your sprint data exports to calculate health scores across multiple dimensions, tracking retrospective themes, and analyzing sentiment trends for actionable insights.

Can I use Monte Carlo simulations for sprint completion forecasts?▼

Yes, you can generate probabilistic sprint completion forecasts using Monte Carlo simulations applied to your historical sprint data to predict future team velocity and delivery reliability.

Does this Scrum analysis tool work with raw JSON data exports from Jira?▼

Yes, this tool processes raw JSON data exports from Jira, parsing sprint metrics to deliver data-driven agile coaching, retrospective analysis, and objective team health assessments for high-performing teams.

What is the best way to track velocity predictability for agile teams?▼

The best way to track velocity predictability is by analyzing historical sprint data exports to measure variance in completed work, generating probabilistic forecasts and comprehensive health reports for your team.

How do I prepare retrospective action items and sentiment trends for a Scrum team?▼

Prepare retrospective insights by processing sprint data to track action item completion, identify recurring themes, and measure sentiment trends over time to guide continuous improvement and coaching.

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