scrum-master
Advanced Scrum Master skill for data-driven agile team analysis and coaching. Use when the user asks about sprint planning, velocity tracking, retrospectives, standup facilitation, backlog grooming, story points, burndown charts, blocker resolution, or agile team health. Runs Python scripts to analyse sprint JSON exports from Jira or similar tools: velocity_analyzer.py for Monte Carlo sprint forecasting, sprint_health_scorer.py for multi-dimension health scoring, and retrospective_analyzer.py for action-item and theme tracking. Produces confidence-interval forecasts, health grade reports, and
Profile →npx skills add alirezarezvani/claude-skills --skill scrum-master --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Scrum Master Expert Data-driven Scrum Master skill combining sprint analytics, probabilistic forecasting, and team development coaching. The unique value is in the three Python analysis scripts and their workflows — refer to `references/` and `assets/` for deeper framework detail. --- ## Table of Contents - [Analysis Tools & Usage](#analysis-tools-usage) - [Input Requirements](#input-requirements) - [Sprint Execution Workflows](#sprint-execution-workflows) - [Team Development Workflow](#team-development-workflow) - [Key Metrics & Targets](#key-metrics-targets) - [Limitations](#limitations) --- ## Analysis Tools & Usage ### 1. Velocity Analyzer (`scripts/velocity_analyzer.py`) Runs rolling averages, linear-regression trend detection, and Monte Carlo simulation over sprint history. ```bash # Text report python velocity_analyzer.py sprint_data.json --format text # JSON output for downstream processing python velocity_analyzer.py sprint_data.json --format json > analysis.json ``` **Outputs**: velocity trend (improving/stable/declining), coefficient of variation, 6-sprint Monte Carlo forecast at 50 / 70 / 85 / 95% confidence intervals, anomaly flags with root-cause suggestions. **Vali
- Table of Contents
- Analysis Tools & Usage
- 1. Velocity Analyzer (scripts/velocityanalyzer.py)
- 2. Sprint Health Scorer (scripts/sprinthealthscorer.py)
- 3. Retrospective Analyzer (scripts/retrospectiveanalyzer.py)
- Input Requirements
- Sprint Execution Workflows
- Sprint Planning
- Daily Standup
- Sprint Review
- Sprint Retrospective
- Team Development Workflow
- Assessment
- Intervention
Text report python velocity_analyzer.py sprint_data.json --format text JSON output for downstream processing python velocity_analyzer.py sprint_data.json --format json > analysis.json python sprint_health_scorer.py sprint_data.json --format text python retrospective_analyzer.py sprint_data.json --format text python sprint_health_scorer.py sprint_data.json --format text > health.txt python retrospective_analyzer.py sprint_data.json --format text > retro.txt python sprint_health_scorer.py team_data.json > health_assessment.txt python retrospective_analyzer.py team_data.json > retro_insights.txt
What does the scrum-master skill do?
Advanced Scrum Master skill for data-driven agile team analysis and coaching. Use when the user asks about sprint planning, velocity tracking, retrospectives, standup facilitation, backlog grooming, story points, burndown charts, blocker resolution, or agile team health. Runs Python scripts to analyse sprint JSON exports from Jira or similar tools: velocity_analyzer.py for Monte Carlo sprint forecasting, sprint_health_scorer.py for multi-dimension health scoring, and retrospective_analyzer.py for action-item and theme tracking. Produces confidence-interval forecasts, health grade reports, and
How do I install it?
Run `npx skills add alirezarezvani/claude-skills --skill scrum-master --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 alirezarezvani/claude-skills, a repository with 23,791 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.