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qe-quality-metrics

qe-quality-metrics

github.com/proffesor-for-testingTesting & quality51981 installsUpdated today
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About qe-quality-metrics

qe-quality-metrics is a skill for selecting quality measures, designing dashboards, and setting quality gates for testing and engineering teams. It emphasizes outcomes such as bug escape rate, MTTD, and MTTR, and trends rather than activity counts.

Key features

  1. 01Select outcome-focused quality measures
  2. 02Track DORA metrics and quality trends
  3. 03Configure quality gate thresholds
  4. 04Design quality dashboards
  5. 05Identify vanity metric pitfalls

Use cases

  1. 01Build a quality metrics dashboard
  2. 02Set gates that block unqualified changes
  3. 03Evaluate test effectiveness and escaped defects
  4. 04Compare quality trends across time periods

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill qe-quality-metrics

After installing, type/qe-quality-metricsin Claude Code to confirm it loaded.

Details

From the project README

Quality Metrics

<default_to_action> When measuring quality or building dashboards:

  1. MEASURE outcomes (bug escape rate, MTTD) not activities (test count)
  2. FOCUS on DORA metrics: Deployment frequency, Lead time, MTTD, MTTR, Change failure rate
  3. AVOID vanity metrics: 100% coverage means nothing if tests don't catch bugs
  4. SET thresholds that drive behavior (quality gates block bad code)
  5. TREND over time: Direction matters more than absolute numbers

Quick Metric Selection:

  • Speed: Deployment frequency, lead time for changes
  • Stability: Change failure rate, MTTR
  • Quality: Bug escape rate, defect density, test effectiveness
  • Process: Code review time, flaky test rate

Critical Success Factors:

  • Metrics without action are theater
  • What you measure is what you optimize
  • Trends matter more than snapshots </default_to_action>

Quick Reference Card

When to Use
  • Building quality dashboards
  • Defining quality gates
  • Evaluating testing effectiveness
  • Justifying quality investments
Meaningful vs Vanity Metrics
✅ Meaningful❌ Vanity
Bug escape rateTest case count
MTTD (detection)Lines of test code
MTTR (recovery)Test executions
Change failure rateCoverage % (alone)
Lead time for changesRequirements traced
DORA Metrics
MetricEliteHighMediumLow
Deploy FrequencyOn-demandWeeklyMonthlyYearly
Lead Time< 1 hour< 1 week< 1 month> 6 months
Change Failure Rate< 5%< 15%< 30%> 45%
MTTR< 1 hour< 1 day< 1 week> 1 month
Quality Gate Thresholds
MetricBlocking ThresholdWarning
Test pass rate100%-
Critical coverage> 80%> 70%
Security critical0-
Performance p95< 200ms< 500ms
Flaky tests< 2%< 5%

Core Metrics

Bug Escape Rate
Bug Escape Rate = (Production Bugs / Total Bugs Found) × 100

Target: < 10% (90% caught before production)
Test Effectiveness
Test Effectiveness = (Bugs Found by Tests / Total Bugs) × 100

Target: > 70%
Defect Density
Defect Density = Defects / KLOC

Good: < 1 defect per KLOC
Mean Time to Detect (MTTD)
MTTD = Time(Bug Reported) - Time(Bug Introduced)

Target: < 1 day for critical, < 1 week for others

Dashboard Design

// Agent generates quality dashboard
await Task("Generate Dashboard", {
  metrics: {
    delivery: ['deployment-frequency', 'lead-time', 'change-failure-rate'],
    quality: ['bug-escape-rate', 'test-effectiveness', 'defect-density'],
    stability: ['mttd', 'mttr', 'availability'],
    process: ['code-review-time', 'flaky-test-rate', 'coverage-trend']
  },
  visualization: 'grafana',
  alerts: {
    critical: { bug_escape_rate: '>20%', mttr: '>24h' },
    warning: { coverage: '<70%', flaky_rate: '>5%' }
  }
}, "qe-quality-analyzer");

Quality Gate Configuration

{
  "qualityGates": {
    "commit": {
      "coverage": { "min": 80, "blocking": true },
      "lint": { "errors": 0, "blocking": true }
    },
    "pr": {
      "tests": { "pass": "100%", "blocking": true },
      "security": { "critical": 0, "blocking": true },
      "coverage_delta": { "min": 0, "blocking": false }
    },
    "release": {
      "e2e": { "pass": "100%", "blocking": true },
      "performance_p95": { "max_ms": 200, "blocking": true },
      "bug_escape_rate": { "max": "10%", "blocking": false }
    }
  }
}

Agent-Assisted Metrics

// Calculate quality trends
await Task("Quality Trend Analysis", {
  timeframe: '90d',
  metrics: ['bug-escape-rate', 'mttd', 'test-effectiveness'],
  compare: 'previous-90d',
  predictNext: '30d'
}, "qe-quality-analyzer");

// Evaluate quality gate
await Task("Quality Gate Evaluation", {
  buildId: 'build-123',
  environment: 'staging',
  metrics: currentMetrics,
  policy: qualityPolicy
}, "qe-quality-gate");

Agent Coordination Hints

Memory Namespace
aqe/quality-metrics/
├── dashboards/*         - Dashboard configurations
├── trends/*             - Historical metric data
├── gates/*              - Gate evaluation results
└── alerts/*             - Triggered alerts
Fleet Coordination
const metricsFleet = await FleetManager.coordinate({
  strategy: 'quality-metrics',
  agents: [
    'qe-quality-analyzer',         // Trend analysis
    'qe-test-executor',            // Test metrics
    'qe-coverage-analyzer',        // Coverage data
    'qe-production-intelligence',  // Production metrics
    'qe-quality-gate'              // Gate decisions
  ],
  topology: 'mesh'
});

Common Traps

TrapProblemSolution
Coverage worship100% coverage, bugs still escapeMeasure bug escape rate instead
Test count focusMany tests, slow feedbackMeasure execution time
Activity metricsBusy work, no outcomesMeasure outcomes (MTTD, MTTR)
Point-in-timeSnapshot without contextTrack trends over time

Related Skills


Remember

Measure outcomes, not activities. Bug escape rate > test count. MTTD/MTTR > coverage %. Trends > snapshots. Set gates that block bad code. What you measure is what you optimize.

With Agents: Agents track metrics automatically, analyze trends, trigger alerts, and make gate decisions. Use agents to maintain continuous quality visibility.

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