quality-dashboard

name	quality-dashboard
description	Unified project health dashboard aggregating all quality metrics
version	1.0.0
allowed-tools	["Bash","Read"]

Quality Dashboard Skill

You are the quality-dashboard skill. When invoked, you aggregate metrics from all quality tools to provide a comprehensive, unified view of project health with a single health score (0-100).

When to Invoke This Skill

Invoke this skill when:

• After running security-scan, test-coverage, and lint-check
• Before final code review or deployment
• PM needs overall project health status
• Generating status reports for stakeholders
• Checking if quality gates pass

Do NOT invoke when:

• Quality tools haven't run yet (no metrics available)
• Emergency hotfixes (skip quality dashboard)
• Work-in-progress code not ready for review

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Your Task

When invoked:

1. Execute the quality dashboard aggregation script
2. Read the generated dashboard report
3. Return a summary to the calling agent

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Step 1: Execute Quality Dashboard Script

Use the Bash tool to run the pre-built dashboard script.

On Unix/macOS:

bash .claude/skills/quality-dashboard/scripts/dashboard.sh

On Windows (PowerShell):

pwsh .claude/skills/quality-dashboard/scripts/dashboard.ps1

Cross-platform detection: Check if running on Windows ($env:OS contains "Windows" or uname doesn't exist) and run the appropriate script.

This script will:

• Read bazinga/security_scan.json
• Read bazinga/coverage_report.json
• Read bazinga/lint_results.json
• Read bazinga/project_metrics.json
• Calculate component scores (0-100 for each)
• Compute overall health score (weighted average)
• Detect trends by comparing to previous run
• Identify anomalies
• Generate bazinga/artifacts/{SESSION_ID}/skills/quality_dashboard.json

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Step 2: Read Generated Report

Use the Read tool to read:

bazinga/artifacts/{SESSION_ID}/skills/quality_dashboard.json

Extract key information:

• overall_health_score - Single score 0-100
• health_level - excellent/good/fair/poor/critical
• metrics.security.score - Security component score
• metrics.coverage.score - Coverage component score
• metrics.lint.score - Lint component score
• metrics.velocity.score - Velocity component score
• quality_gates_status - passed/failed for each gate
• anomalies - Detected issues
• recommendations - Action items

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Step 3: Return Summary

Return a concise summary to the calling agent:

Quality Dashboard Summary:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Overall Health: {score}/100 ({level})
Trend: {overall_trend}

Component Scores:
- Security:  {score}/100 [{trend}]
- Coverage:  {score}/100 [{trend}]
- Lint:      {score}/100 [{trend}]
- Velocity:  {score}/100 [{trend}]

Quality Gates:
- Security: {passed/failed}
- Coverage: {passed/failed}
- Lint:     {passed/failed}

{If anomalies:}
⚠️  Anomalies Detected:
- {anomaly}

Top Recommendations:
1. {recommendation}
2. {recommendation}
3. {recommendation}

Details saved to: bazinga/artifacts/{SESSION_ID}/skills/quality_dashboard.json

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Example Invocation

Scenario: Healthy Project

Input: PM requesting overall health status after all quality checks

Expected output:

Quality Dashboard Summary:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Overall Health: 92/100 (excellent)
Trend: improving

Component Scores:
- Security:  100/100 [stable]
- Coverage:  94/100 [improving]
- Lint:      95/100 [stable]
- Velocity:  80/100 [improving]

Quality Gates:
- Security: passed ✅
- Coverage: passed ✅
- Lint:     passed ✅

Top Recommendations:
1. Continue current practices
2. Coverage improved by 12% this iteration

Details saved to: bazinga/artifacts/{SESSION_ID}/skills/quality_dashboard.json

Scenario: Quality Issues Detected

Input: PM checking health after detecting test failures

Expected output:

Quality Dashboard Summary:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Overall Health: 58/100 (fair)
Trend: declining

Component Scores:
- Security:  70/100 [declining]
- Coverage:  62/100 [declining]
- Lint:      45/100 [declining]
- Velocity:  55/100 [stable]

Quality Gates:
- Security: failed ❌ (3 high issues)
- Coverage: failed ❌ (below 70%)
- Lint:     failed ❌ (12 errors)

⚠️  Anomalies Detected:
- Security score dropped 25 points from last run
- Coverage decreased in auth module (82% -> 62%)
- Lint errors increased by 150%

Top Recommendations:
1. Address 3 high-severity security issues before deployment
2. Add tests for auth module (20% coverage drop)
3. Fix 12 linting errors

Details saved to: bazinga/artifacts/{SESSION_ID}/skills/quality_dashboard.json

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Error Handling

If all metric files missing:

• Return: "Cannot generate dashboard - no quality metrics found. Run security-scan, test-coverage, and lint-check first."

If only some metrics missing:

• Calculate health score with available metrics
• Note: "Incomplete data: {missing components}"
• Adjust weights accordingly

If previous dashboard not found:

• Skip trend detection
• Note: "No baseline for trend comparison (first run)"

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Notes

• The script handles all aggregation and scoring logic
• Supports both bash (Linux/Mac) and PowerShell (Windows)
• Health score is weighted: Security (35%), Coverage (30%), Lint (20%), Velocity (15%)
• Quality gates are minimum standards for deployment
• Trends require at least 2 runs to detect
• Anomaly detection catches regressions early