Project Status Manager - Comprehensive Health Monitoring

Purpose

This skill is the primary reporting and monitoring tool for the lead-developer. It provides a comprehensive, system-wide health check by aggregating data from the two most critical sources of truth: the task "database" (process health) and the QA test reports (product health). The unified report enables data-driven decision making and proactive risk management.

When to Use

• Daily Standups: Generate current project status for team alignment
• Stakeholder Reporting: Provide comprehensive progress reports to stakeholders
• Health Monitoring: Identify project risks and quality issues early
• Trend Analysis: Track project health metrics over time
• Decision Support: Inform strategic decisions with objective data
• Quality Gates: Validate project readiness for milestones

R&D Workflow

This skill follows the "Reduce and Delegate" philosophy:

1. Agent Role: Primary monitoring tool for the lead-developer (Orchestrator)
2. Data Sources: Two high-truth-value sources (task database + QA reports)
3. Delegation: Agent MUST delegate all complex aggregation to ProjectWorkflowManager.generate_status_report()
4. Deterministic Process: Script performs reliable data synthesis and analysis

Input Requirements

The skill accepts optional configuration parameters:

{
  "include_trends": true,
  "trend_days": 14,
  "risk_threshold": "medium",
  "include_predictions": true,
  "forecast_days": 7,
  "quality_gates": {
    "min_test_pass_rate": 80,
    "max_failed_tasks": 5,
    "min_completion_rate": 60
  }
}

Parameters Explained

• include_trends: Include historical trend analysis in the report
• trend_days: Number of days to analyze for trends (default: 14)
• risk_threshold: Minimum risk level to include in report (low/medium/high/critical)
• include_predictions: Include predictive analytics and forecasts
• forecast_days: Number of days to forecast project metrics
• quality_gates: Thresholds for quality gate validation

Output Format

Returns comprehensive project health report:

{
  "generated_at": "2025-01-01T12:00:00Z",
  "report_period": {
    "start_date": "2024-12-18",
    "end_date": "2025-01-01",
    "trend_analysis_days": 14
  },
  "tasks": {
    "total": 77,
    "by_status": {
      "completed": 23,
      "in_progress": 15,
      "in_sprint": 12,
      "failed": 2,
      "pending": 25
    },
    "by_assignee": {
      "gdscript-engineer": 18,
      "asset-pipeline-engineer": 15,
      "ui-engineer": 12,
      "unassigned": 32
    },
    "by_sprint": {
      "Sprint-01": 15,
      "Sprint-02": 12,
      "none": 50
    },
    "unestimated": 8,
    "overdue": [],
    "completion_rate": 29.9,
    "sprint_progress": {
      "current_sprint": "Sprint-02",
      "sprint_completion": 45.8,
      "sprint_capacity_utilization": 83.3
    }
  },
  "qa": {
    "tests_run": 245,
    "failures": 8,
    "errors": 3,
    "pass_rate": 95.5,
    "coverage": {
      "line_coverage": 82.3,
      "branch_coverage": 76.8,
      "function_coverage": 89.1
    },
    "last_run": "2025-01-01T11:30:00Z",
    "test_trend": "improving"
  },
  "health_indicators": {
    "overall_health": "good",
    "task_completion_rate": 29.9,
    "test_pass_rate": 95.5,
    "burndown_health": "good",
    "quality_trend": "improving",
    "velocity_trend": "stable"
  },
  "risk_indicators": [
    {
      "type": "task_distribution",
      "level": "medium",
      "description": "32 tasks remain unassigned",
      "impact": "potential resource bottlenecks",
      "recommendation": "Assign tasks to team members or adjust capacity planning"
    },
    {
      "type": "quality",
      "level": "low",
      "description": "8 test failures detected",
      "impact": "code quality issues requiring attention",
      "recommendation": "Address failing tests before next release"
    }
  ],
  "trend_analysis": {
    "completion_rate_trend": "increasing",
    "velocity_trend": "stable",
    "quality_trend": "improving",
    "risk_trend": "stable"
  },
  "predictions": {
    "estimated_completion": "2025-03-15",
    "confidence_level": 75,
    "risk_factors": [
      "unassigned_tasks",
      "new requirements"
    ]
  },
  "quality_gates": {
    "status": "pass",
    "gates_checked": [
      {
        "name": "min_test_pass_rate",
        "threshold": 80,
        "actual": 95.5,
        "status": "pass"
      },
      {
        "name": "max_failed_tasks",
        "threshold": 5,
        "actual": 2,
        "status": "pass"
      },
      {
        "name": "min_completion_rate",
        "threshold": 60,
        "actual": 29.9,
        "status": "fail"
      }
    ]
  },
  "recommendations": [
    "Assign unassigned tasks to balance team workload",
    "Focus on completing in-progress tasks before starting new ones",
    "Address test failures to maintain code quality standards",
    "Consider breaking down large tasks for better progress tracking"
  ]
}

Deterministic Data Synthesis Process

The ProjectWorkflowManager backend implements this analysis process:

Phase 1: Task Database Analysis (Process Health)

1. Status Aggregation: Count tasks by status (pending, in_progress, in_sprint, failed, completed)
2. Assignee Distribution: Analyze workload distribution across team members
3. Sprint Analysis: Evaluate current and historical sprint performance
4. Dependency Analysis: Identify blocking dependencies and critical paths
5. Estimation Analysis: Track unestimated tasks and estimation accuracy

Phase 2: QA Report Analysis (Product Health)

1. Test Execution: Parse JUnit XML reports for test results
2. Coverage Analysis: Extract code coverage metrics from test reports
3. Quality Trends: Track quality metrics over time
4. Failure Analysis: Categorize and analyze test failures
5. Performance Metrics: Monitor test execution performance

Phase 3: Health Indicator Calculation

1. Completion Rate: Calculate percentage of completed tasks
2. Quality Metrics: Synthesize test pass rates and coverage
3. Velocity Tracking: Monitor team velocity and burndown progress
4. Risk Assessment: Identify project-level risks and indicators
5. Trend Analysis: Calculate historical trends and changes

Phase 4: Predictive Analytics

1. Completion Forecasting: Estimate project completion dates
2. Risk Prediction: Identify potential future risks based on current trends
3. Resource Planning: Forecast future resource needs
4. Quality Prediction: Predict quality trends based on current metrics

Health Indicator Framework

Overall Health Score

The system calculates an overall health score based on multiple factors:

• Task Health (40%): Completion rate, sprint progress, task distribution
• Quality Health (35%): Test pass rate, coverage, failure trends
• Velocity Health (15%): Team velocity consistency, burndown progress
• Risk Health (10%): Risk indicators, dependency health

Health Categories

• Excellent: All indicators green, no significant risks
• Good: Most indicators green, minor issues identified
• Warning: Some indicators yellow, moderate risks present
• Critical: Multiple indicators red, significant risks requiring immediate attention

Risk Assessment Framework

Risk Categories

1. Task Distribution Risks: Unbalanced workloads, unassigned tasks
2. Quality Risks: Falling test pass rates, coverage gaps
3. Schedule Risks: Delayed tasks, dependency blocks
4. Resource Risks: Team capacity issues, skill gaps
5. Technical Risks: Integration issues, architectural problems

Risk Scoring

• Critical: Immediate impact on project success, requires urgent action
• High: Significant impact if not addressed within 1-2 weeks
• Medium: Moderate impact, should be addressed in current sprint
• Low: Minor impact, can be addressed during routine maintenance

Trend Analysis Features

Historical Trends

• Completion Rate: Track project completion over time
• Team Velocity: Monitor velocity consistency and changes
• Quality Metrics: Track test pass rates and coverage trends
• Risk Evolution: Monitor how risk indicators change over time

Predictive Analytics

• Completion Forecasting: Estimate project completion dates with confidence intervals
• Velocity Prediction: Forecast future team velocity based on historical data
• Quality Forecasting: Predict quality trends based on current metrics
• Risk Prediction: Identify potential future risks based on trend analysis

Quality Gates Integration

Gate Definitions

The skill integrates with configurable quality gates:

• Minimum Test Pass Rate: Ensure code quality standards
• Maximum Failed Tasks: Limit work-in-progress and failures
• Minimum Completion Rate: Ensure adequate project progress
• Coverage Thresholds: Maintain adequate test coverage

Gate Validation

• Real-time Validation: Check gates against current metrics
• Historical Validation: Validate gates against historical trends
• Trend Validation: Ensure gates are being met consistently over time

Integration Points

With sprint-planner

• Capacity Planning: Use status data for future sprint planning
• Velocity Tracking: Monitor team velocity for capacity estimation
• Risk Assessment: Identify risks that impact sprint planning

With qa-engineer

• Quality Metrics: Aggregate test results for health reporting
• Failure Analysis: Analyze test failures for risk identification
• Coverage Tracking: Monitor code coverage trends

With requirements-engineer

• Requirements Coverage: Track requirements implementation progress
• Traceability Health: Monitor requirements traceability status
• Gap Analysis: Identify requirements not yet implemented

Report Generation Features

Executive Summary

• High-level project health overview
• Key metrics and trends
• Critical risks and recommendations
• Quality gate status

Detailed Analysis

• Comprehensive task breakdown by status, assignee, and sprint
• Detailed QA metrics and coverage analysis
• Risk indicators with mitigation strategies
• Trend analysis with visualizations

Actionable Insights

• Specific recommendations for improvement
• Risk mitigation strategies
• Resource allocation suggestions
• Process improvement opportunities

This skill provides the lead-developer with a comprehensive, data-driven view of project health that enables proactive management and informed decision making throughout the migration process.