| name | scrum-master |
| description | "Use — Advanced Scrum Master skill for data-driven agile team analysis and coaching. Use when the user asks about sprint" |
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
1. Velocity Analyzer (scripts/velocity_analyzer.py)
Runs rolling averages, linear-regression trend detection, and Monte Carlo simulation over sprint history.
python velocity_analyzer.py sprint_data.json --format text
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.
Validation: If fewer than 3 sprints are present in the input, stop and prompt the user: "Velocity analysis needs at least 3 sprints. Please provide additional sprint data." 6+ sprints are recommended for statistically significant Monte Carlo results.
2. Sprint Health Scorer (scripts/sprint_health_scorer.py)
Scores team health across 6 weighted dimensions, producing an overall 0–100 grade.
| Dimension | Weight | Target |
|---|
| Commitment Reliability | 25% | >85% sprint goals met |
| Scope Stability | 20% | <15% mid-sprint changes |
| Blocker Resolution | 15% | <3 days average |
| Ceremony Engagement | 15% | >90% participation |
| Story Completion Distribution | 15% | High ratio of fully done stories |
| Velocity Predictability | 10% | CV <20% |
python sprint_health_scorer.py sprint_data.json --format text
Outputs: overall health score + grade, per-dimension scores with recommendations, sprint-over-sprint trend, intervention priority matrix.
Validation: Requires 2+ sprints with ceremony and story-completion data. If data is missing, report which dimensions cannot be scored and ask the user to supply the gaps.
3. Retrospective Analyzer (scripts/retrospective_analyzer.py)
Tracks action-item completion, recurring themes, sentiment trends, and team maturity progression.
python retrospective_analyzer.py sprint_data.json --format text
Outputs: action-item completion rate by priority/owner, recurring-theme persistence scores, team maturity level (forming/storming/norming/performing), improvement-velocity trend.
Validation: Requires 3+ retrospectives with action-item tracking. With fewer, note the limitation and offer partial theme analysis only.
Input Requirements
All scripts accept JSON following the schema in assets/sample_sprint_data.json:
{
"team_info": { "name": "string", "size": "number", "scrum_master": "string" },
"sprints": [
{
"sprint_number": "number",
"planned_points": "number",
"completed_points": "number",
"stories": [...],
"blockers": [...],
"ceremonies": {...}
}
],
"retrospectives": [
{
"sprint_number": "number",
...
Jira and similar tools can export sprint data; map exported fields to this schema before running the scripts. See assets/sample_sprint_data.json for a complete 6-sprint example and assets/expected_output.json for corresponding expected results (velocity avg 20.2 pts, CV 12.7%, health score 78.3/100, action-item completion 46.7%).
Sprint Execution Workflows
Sprint Planning
- Run velocity analysis:
python velocity_analyzer.py sprint_data.json --format text
- Use the 70% confidence interval as the recommended commitment ceiling for the sprint backlog.
- Review the health scorer's Commitment Reliability and Scope Stability scores to calibrate negotiation with the Product Owner.
- If Monte Carlo output shows high volatility (CV >20%), surface this to stakeholders with range estimates rather than single-point forecasts.
- Document capacity assumptions (leave, dependencies) for retrospective comparison.
Daily Standup
- Track participation and help-seeking patterns — feed ceremony data into
sprint_health_scorer.py at sprint end.
- Log each blocker with date opened; resolution time feeds the Blocker Resolution dimension.
- If a blocker is unresolved after 2 days, escalate proactively and note in sprint data.
Sprint Review
- Present velocity trend and health score alongside the demo to give stakeholders delivery context.
- Capture scope-change requests raised during review; record as scope-change events in sprint data for next scoring cycle.
Sprint Retrospective
- Run all three scripts before the session:
python sprint_health_scorer.py sprint_data.json --format text > health.txt
python retrospective_analyzer.py sprint_data.json --format text > retro.txt
- Open with the health score and top-flagged dimensions to focus discussion.
- Use the retrospective analyzer's action-item completion rate to determine how many new action items the team can realistically absorb (target: ≤3 if completion rate <60%).
- Assign each action item an owner and measurable success criterion before closing the session.
- Record new action items in
sprint_data.json for tracking in the next cycle.
Team Development Workflow
Assessment
python sprint_health_scorer.py team_data.json > health_assessment.txt
python retrospective_analyzer.py team_data.json > retro_insights.txt
- Map retrospective analyzer maturity output to the appropriate development stage.
- Supplement with an anonymous psychological safety pulse survey (Edmondson 7-point scale) and individual 1:1 observations.
- If maturity output is
forming or storming, prioritise safety and conflict-facilitation interventions before process optimisation.
Intervention
Apply stage-specific facilitation (details in references/team-dynamics-framework.md):
| Stage | Focus |
|---|
| Forming | Structure, process education, trust building |
| Storming | Conflict facilitation, psychological safety maintenance |
| Norming | Autonomy building, process ownership transfer |
| Performing | Challenge introduction, innovation support |
Progress Measurement
- Sprint cadence: re-run health scorer; target overall score improvement of ≥5 points per quarter.
- Monthly: psychological safety pulse survey; target >4.0/5.0.
- Quarterly: full maturity re-assessment via retrospective analyzer.
- If scores plateau or regress for 2 consecutive sprints, escalate intervention strategy (see
references/team-dynamics-framework.md).
Key Metrics & Targets
| Metric | Target |
|---|
| Overall Health Score | >80/100 |
| Psychological Safety Index | >4.0/5.0 |
| Velocity CV (predictability) | <20% |
| Commitment Reliability | >85% |
| Scope Stability | <15% mid-sprint changes |
| Blocker Resolution Time | <3 days |
| Ceremony Engagement | >90% |
| Retrospective Action Completion | >70% |
Limitations
- Sample size: fewer than 6 sprints reduces Monte Carlo confidence; always state confidence intervals, not point estimates.
- Data completeness: missing ceremony or story-completion fields suppress affected scoring dimensions — report gaps explicitly.
- Context sensitivity: script recommendations must be interpreted alongside organisational and team context not captured in JSON data.
- Quantitative bias: metrics do not replace qualitative observation; combine scores with direct team interaction.
- Team size: techniques are optimised for 5–9 member teams; larger groups may require adaptation.
- External factors: cross-team dependencies and organisational constraints are not fully modelled by single-team metrics.
Related Skills
- Agile Product Owner (
product-team/agile-product-owner/) — User stories and backlog feed sprint planning
- Senior PM (
project-management/senior-pm/) — Portfolio health context informs sprint priorities
For deep framework references see references/velocity-forecasting-guide.md and references/team-dynamics-framework.md. For template assets see assets/sprint_report_template.md and assets/team_health_check_template.md.
Diff History
- v00.33.0: Ingested from claude-skills-main
Why This Skill Exists
Use — Advanced Scrum Master skill for data-driven agile team analysis and coaching.
When to Use
Use this skill when the user asks about sprint
What If Fails
- condition: Recurso ou ferramenta necessária indisponível
