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scrum-master

Analyze Jira-exported sprint JSON data to forecast velocity and track agile-health indicators.

Updated Aug 23, 2026
Search Tags:#retrospective#agile#forecasting#health#scrum#velocity
One-click install
npx skills add https://github.com/ContractorKeith/openclaw-home --skill scrum-master-contractorkeith
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scrum-master
Source: https://github.com/ContractorKeith/openclaw-home/tree/main/workspace-william/skills/project-management/scrum-master
Command: npx skills add https://github.com/ContractorKeith/openclaw-home --skill scrum-master-contractorkeith

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Scrum teams often lack objective data to forecast velocity and gauge team health, making planning and coaching reactive rather than proactive.

Core Features & Use Cases

  • Automated sprint analysis: velocity forecasting, health scoring, and retrospective tracking to surface improvement opportunities.
  • Jira-export-ready: consumes sprint JSON exports and produces structured reports for stakeholders.
  • Use Case: A Scrum Master uses the scripts to forecast sprint completion, identify health gaps, and track action-item progress across sprints.

Quick Start

Analyze sprint data JSON to generate velocity forecasts and health 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 using Jira export data?▼

Sprint velocity forecasting analyzes Jira-exported sprint JSON data to calculate historical throughput and project future completion rates. The velocity_analyzer.py script processes sprint records to generate structured velocity forecasts for sprint planning and stakeholder reporting.

What is agile team-health scoring and how does it work?▼

Agile team-health scoring evaluates sprint data to identify workflow gaps and track agile-health indicators. The sprint_health_scorer.py script ingests sprint JSON exports and produces structured health reports, enabling proactive coaching and targeted bottleneck resolution.

Do I need Python 3 to run sprint health and retrospective analysis scripts?▼

Yes, Python 3 is required to execute the velocity_analyzer.py, sprint_health_scorer.py, and retrospective_analyzer.py scripts. These Python scripts process Jira sprint JSON exports to generate velocity forecasts, health reports, and retrospective improvement insights.

Can I track retrospective action-item progress across multiple sprints?▼

Retrospective tracking surfaces improvement opportunities by analyzing action-item progress across sprints. The retrospective_analyzer.py script processes sprint JSON data to measure improvement velocity and generate structured insights for continuous agile coaching.

What's the best way to prepare Jira sprint data for velocity forecasting?▼

Jira sprint data must be exported as JSON files to run velocity forecasting and health scoring. Once exported, the Python scripts directly consume the sprint JSON to produce structured stakeholder reports without requiring live database connections or API integrations.

Why use data-driven scripts instead of manual spreadsheets for sprint health reporting?▼

Data-driven sprint health scripts automate the analysis of JSON exports to objectively gauge team health and forecast velocity. This replaces reactive manual spreadsheet tracking with proactive, structured reporting that identifies agile-health gaps and improvement opportunities across sprints.

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