Scrum Master Agent

A production-ready Scrum Master assistant designed for SaaS startups and application engineering teams. This skill provides intelligent sprint analytics, capacity planning, backlog prioritization, and actionable insights with token-efficient, context-aware output formatting.

Capabilities

Sprint Management

•Sprint Planning: Capacity-based story allocation with velocity tracking
•Backlog Grooming: Priority scoring with effort/value/risk analysis
•Sprint Health Monitoring: Real-time burndown tracking with predictive alerts
•Velocity Analysis: Historical trend analysis with forecasting

Team Operations

•Daily Standups: Ultra-lightweight progress summaries (50-100 tokens)
•Capacity Planning: Team availability calculation with holiday/PTO handling
•Sprint Retrospectives: Action items extraction with sentiment analysis
•Risk Detection: Automated alerts for scope creep, velocity drops, blocked tasks

Multi-Tool Integration

•Linear: Native JSON import with Linear-specific field mapping
•Jira: REST API adapter with custom field support
•GitHub Projects: GraphQL integration with issue/PR tracking
•Azure DevOps: Work item queries with sprint hierarchy

Notification Integration

•Slack Notifications: Token-efficient webhook integration with rich block formatting
•MS Teams Notifications: Adaptive Card integration for Microsoft Teams channels
•Optional/Disabled by Default: No setup required to use skill, notifications opt-in
•User Choice: Select Slack or Teams via configuration or environment variables
•Concise Summaries: 50-100 token notifications with top 3 risks only

Intelligent Output Design

•Context Detection: Automatically adapts to Claude AI Desktop vs Claude Code
•Token Efficiency: Summary-first approach with progressive disclosure
•Conditional Alerts: Only shows warnings/risks when they exist
•Format Optimization: Markdown tables for Claude AI, ASCII charts for CLI

Input Requirements

Supported Formats

•

JSON (Recommended):

json

{
  "tool": "linear|jira|github|azure",
  "sprint_name": "Sprint 45",
  "start_date": "2025-11-05",
  "end_date": "2025-11-19",
  "team_capacity": 80,
  "stories": [...]
}

•

CSV:

csv

story_id,title,points,status,assignee,priority,blocked
STORY-123,User login,5,In Progress,Alice,High,false

•

YAML:

yaml

sprint:
  name: "Sprint 45"
  team:
    - name: Alice
      capacity: 40
    - name: Bob
      capacity: 40

•
Tool-Specific Exports:
- •Linear: Export to JSON from project view
- •Jira: Use REST API or CSV export
- •GitHub Projects: GraphQL query or CSV export
- •Azure DevOps: Work Item Query Results

Required Fields

•Sprint metadata: name, start_date, end_date, team_capacity
•Stories: id, title, points, status, assignee
•Optional: priority, blocked, dependencies, labels, created_date

Data Quality

•Story points must be numeric (Fibonacci or T-shirt sizes)
•Dates in ISO 8601 format (YYYY-MM-DD)
•Status values normalized to: Todo, In Progress, In Review, Done
•Team capacity in story points per sprint

Output Formats

1. Daily Standups (Ultra-Lightweight)

Token Budget: 50-100 tokens

code

🚀 Sprint 45 - Day 7/10

✅ Completed: 3 stories (13 pts)
🔄 In Progress: 5 stories (21 pts)
⚠️ Blocked: 1 story (5 pts) - Needs DB access

Velocity: On track (65% complete, 70% time elapsed)

2. Sprint Planning (Moderate Detail)

Token Budget: 200-500 tokens

code

📊 Sprint 45 Planning Summary

Capacity: 80 pts | Committed: 75 pts | Buffer: 5 pts

High Priority (35 pts):
  - STORY-123: User authentication (8 pts)
  - STORY-124: Payment integration (13 pts)
  - STORY-125: Dashboard redesign (8 pts)

Recommendations:
  1. P0: Address DB access blocker
  2. P1: Reduce scope if velocity drops below 85%
  3. P2: Consider splitting STORY-124 (13 pts is risky)

3. Sprint Review (Full Report)

Token Budget: 500-1000 tokens

Includes:

•Velocity trends (ASCII chart for CLI, table for Claude AI)
•Burndown analysis with predictive completion date
•Team performance metrics (throughput, cycle time)
•Risk alerts (conditional - only if issues exist)
•Prioritized recommendations (P0/P1/P2)

4. Retrospective Analysis

Token Budget: 300-500 tokens

code

🔍 Sprint 45 Retrospective

What Went Well:
  - 95% velocity achievement
  - Zero production incidents
  - Early story completion (3 days before deadline)

What Needs Improvement:
  - 2 stories blocked for >2 days
  - Code review delays (avg 18 hours)

Action Items:
  [P0] Establish DB access protocol (Owner: Alice, Due: 11/12)
  [P1] Set 8-hour code review SLA (Owner: Bob, Due: 11/15)
  [P2] Add automated status updates (Owner: Team, Due: 11/20)

5. Optional JSON Export

For tool integration and dashboards:

json

{
  "sprint": "Sprint 45",
  "metrics": {
    "velocity": 75,
    "completion_rate": 0.95,
    "cycle_time_avg": 3.2
  },
  "risks": [...],
  "recommendations": [...]
}

How to Use

Quick Invocations

Daily Standup:

code

@scrum-master-agent

Generate a quick standup summary for Sprint 45 using the attached Linear export.

Sprint Planning:

code

@scrum-master-agent

Help me plan Sprint 46. Team capacity is 80 points. Here's the backlog (CSV attached).
Prioritize based on effort, value, and risk.

Burndown Analysis:

code

@scrum-master-agent

Analyze Sprint 45 burndown. Are we on track? When will we likely finish?
Attached: Jira sprint export (JSON)

Retrospective:

code

@scrum-master-agent

Generate retrospective report for Sprint 45. Focus on blockers and cycle time.
Attached: GitHub Projects export (CSV)

Capacity Planning:

code

@scrum-master-agent

Calculate team capacity for next sprint. Alice is on PTO for 3 days, Bob has 2 days of meetings.
Team size: 4 engineers (40 pts each normally).

Advanced Usage

Multi-Tool Comparison:

code

Compare velocity trends across last 3 sprints using Linear data for Sprint 43-44 and Jira data for Sprint 45.

Risk Analysis:

code

Identify high-risk stories in the backlog. Flag anything with >8 points, blockers, or missing dependencies.

Custom Metrics:

code

Calculate sprint health score based on: velocity (40%), burndown trend (30%), blocked items (20%), team morale (10%).

Scripts

Core Modules

•parse_input.py: Multi-format parser (JSON/CSV/YAML) with tool-specific adapters
•tool_adapters.py: Integration adapters for Linear, Jira, GitHub, Azure DevOps
•calculate_metrics.py: All 6 metric calculations (velocity, burndown, capacity, priority, health, retrospective)
•detect_context.py: Environment detection (Claude AI Desktop vs Claude Code)
•format_output.py: Context-aware report generation with token efficiency
•notify_channels.py: Slack and MS Teams webhook integrations (optional)
•prioritize_backlog.py: Priority scoring with effort/value/risk analysis

Calculation Details

1. Velocity Analysis:

•Historical average over last 3-5 sprints
•Trend analysis (improving/declining/stable)
•Forecasting for next sprint

2. Burndown Tracking:

•Daily story point completion
•Ideal burndown line calculation
•Predictive completion date (linear regression)

3. Capacity Planning:

•Team availability calculation (PTO, holidays, meetings)
•Story point allocation
•Buffer recommendation (10-20% of capacity)

4. Priority Scoring:

•Effort: Story points (normalized 0-10)
•Value: Business impact (High=10, Medium=5, Low=2)
•Risk: Blockers, dependencies, complexity (0-10)
•Formula: priority_score = (value * 2 + (10 - effort) + (10 - risk)) / 4

5. Sprint Health Score:

•Velocity: Actual vs committed (40% weight)
•Burndown: Actual vs ideal (30% weight)
•Blocked Items: Count and duration (20% weight)
•Team Morale: Optional sentiment input (10% weight)
•Scale: 0-100 (90+ = Excellent, 70-89 = Good, 50-69 = Fair, <50 = At Risk)

6. Retrospective Analysis:

•Completed vs committed stories
•Blocked item analysis (count, duration, causes)
•Cycle time metrics (avg time from start to done)
•Action item extraction from retro notes

Best Practices

Data Quality

•Consistent Story Pointing: Use Fibonacci (1,2,3,5,8,13) or T-shirt sizes (XS=1, S=2, M=3, L=5, XL=8)
•Accurate Status Updates: Update story status daily (automate if possible)
•Blocked Item Tracking: Always document why items are blocked and who can unblock
•Sprint Boundaries: Never change sprint scope after day 3 (exception: critical bugs)

Workflow Integration

•Daily Standups: Generate lightweight summary every morning (automated)
•Sprint Planning: Use priority scoring to allocate top 80% of capacity
•Mid-Sprint Check: Run health score on day 5-7 to catch issues early
•Retrospectives: Generate within 24 hours of sprint end while feedback is fresh

Token Efficiency

•Progressive Disclosure: Start with summary, offer details on request
•Conditional Alerts: Only show risks if they exist (don't report "No issues")
•Lazy Calculation: Compute detailed metrics only when asked
•Caching: Reuse calculations across multiple report types

Team Adoption

•Start Simple: Begin with daily standups, add complexity gradually
•Customize Thresholds: Adjust health score weights based on team values
•Automate Inputs: Set up CI/CD to export tool data automatically
•Iterate: Refine priority scoring based on team feedback

Limitations

Data Requirements

•Requires structured sprint data (not suitable for ad-hoc work)
•Story points must be assigned (can't prioritize unpointed stories)
•Historical data needed for velocity trends (minimum 3 sprints)

Accuracy Considerations

•Priority scoring is heuristic-based, not ML-driven (no predictive analytics)
•Burndown predictions assume linear velocity (doesn't account for holidays, blockers)
•Health score is subjective and depends on accurate weight configuration

Scope Boundaries

•Does NOT: Integrate directly with tools (requires exports)
•Does NOT: Send notifications or update tool state (read-only)
•Does NOT: Replace Scrum Master judgment (augments decision-making)

Tool-Specific Notes

•Linear: Requires manual JSON export (no API key support in this version)
•Jira: Custom fields may need mapping in tool_adapters.py
•GitHub Projects: Beta GraphQL API may change (adapter may need updates)
•Azure DevOps: Work item hierarchy can be complex (flatten in export)

When NOT to Use This Skill

•Kanban workflows: Skill is optimized for Scrum sprints (not continuous flow)
•Non-software projects: Priority scoring assumes software development context
•Single-person teams: Overhead not justified for solo developers
•Ad-hoc work: Requires structured sprint planning and tracking

Installation

Claude Code (Recommended)

bash

cp -r scrum-master-agent ~/.claude/skills/

Claude AI Desktop

Drag the scrum-master-agent.zip file into Claude Desktop.

Claude API

Use the /v1/skills endpoint to upload the skill package.

Notification Setup (Optional)

Notifications are disabled by default and completely optional. The skill works perfectly without any notification setup.

Option 1: Configuration File (Recommended)

bash

# Copy example config
cp config.example.yaml config.yaml

# Edit config.yaml with your webhook URLs
# Set enabled: true
# Choose channel: slack or teams

Option 2: Environment Variables

bash

export NOTIFY_ENABLED=true
export NOTIFY_CHANNEL=slack  # or teams
export SLACK_WEBHOOK_URL=https://hooks.slack.com/services/YOUR/WEBHOOK/URL
export TEAMS_WEBHOOK_URL=https://outlook.office.com/webhook/YOUR/WEBHOOK/URL

Getting Webhook URLs:

Slack:

•Go to https://api.slack.com/messaging/webhooks
•Create app and activate Incoming Webhooks
•Add webhook to workspace and select channel
•Copy webhook URL

Microsoft Teams:

•Open Teams channel
•Click "..." → Connectors → Incoming Webhook
•Configure webhook with name
•Copy webhook URL

Using Notifications:

code

@scrum-master-agent

Generate daily standup summary and send notification to Slack.

Notifications are token-efficient (50-100 tokens max) with:

•Sprint name and status
•Velocity and health metrics
•Top 3 risks only (conditional)
•Rich formatting (Slack blocks, Teams Adaptive Cards)

Version

Version: 1.1.0 (with Notification Support) Last Updated: 2025-11-05 Author: Claude Code Skills Factory License: MIT

Support

For issues, feature requests, or contributions, see the skill's GitHub repository or contact the Skills Factory maintainers.