Measure quality effectively with actionable metrics. Use when establishing quality dashboards, defining KPIs, or evaluating test effectiveness.
<default_to_action> When measuring quality or building dashboards:
Quick Metric Selection:
Critical Success Factors:
| ✅ Meaningful | ❌ Vanity |
|---|---|
| Bug escape rate | Test case count |
| MTTD (detection) | Lines of test code |
| MTTR (recovery) | Test executions |
| Change failure rate | Coverage % (alone) |
| Lead time for changes | Requirements traced |
| Metric | Elite | High | Medium | Low |
|---|---|---|---|---|
| Deploy Frequency | On-demand | Weekly | Monthly | Yearly |
| 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 |
| Metric | Blocking Threshold | Warning |
|---|---|---|
| Test pass rate | 100% | - |
| Critical coverage | > 80% | > 70% |
| Security critical | 0 | - |
| Performance p95 | < 200ms | < 500ms |
| Flaky tests | < 2% | < 5% |
Bug Escape Rate = (Production Bugs / Total Bugs Found) × 100
Target: < 10% (90% caught before production)
Test Effectiveness = (Bugs Found by Tests / Total Bugs) × 100
Target: > 70%
Defect Density = Defects / KLOC
Good: < 1 defect per KLOC
MTTD = Time(Bug Reported) - Time(Bug Introduced)
Target: < 1 day for critical, < 1 week for others
// 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");
{
"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 }
}
}
}
// 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");
aqe/quality-metrics/
├── dashboards/* - Dashboard configurations
├── trends/* - Historical metric data
├── gates/* - Gate evaluation results
└── alerts/* - Triggered alerts
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'
});
| Trap | Problem | Solution |
|---|---|---|
| Coverage worship | 100% coverage, bugs still escape | Measure bug escape rate instead |
| Test count focus | Many tests, slow feedback | Measure execution time |
| Activity metrics | Busy work, no outcomes | Measure outcomes (MTTD, MTTR) |
| Point-in-time | Snapshot without context | Track trends over time |
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.