qe-quality-metrics
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
- 01Select outcome-focused quality measures
- 02Track DORA metrics and quality trends
- 03Configure quality gate thresholds
- 04Design quality dashboards
- 05Identify vanity metric pitfalls
Use cases
- 01Build a quality metrics dashboard
- 02Set gates that block unqualified changes
- 03Evaluate test effectiveness and escaped defects
- 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-metricsAfter installing, type/qe-quality-metricsin Claude Code to confirm it loaded.
Details
From the project READMEQuality Metrics
<default_to_action> When measuring quality or building dashboards:
- MEASURE outcomes (bug escape rate, MTTD) not activities (test count)
- FOCUS on DORA metrics: Deployment frequency, Lead time, MTTD, MTTR, Change failure rate
- AVOID vanity metrics: 100% coverage means nothing if tests don't catch bugs
- SET thresholds that drive behavior (quality gates block bad code)
- 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 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 |
DORA Metrics
| 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 |
Quality Gate Thresholds
| Metric | Blocking Threshold | Warning |
|---|---|---|
| Test pass rate | 100% | - |
| Critical coverage | > 80% | > 70% |
| Security critical | 0 | - |
| 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
| 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 |
Related Skills
- agentic-quality-engineering - Agent coordination
- cicd-pipeline-qe-orchestrator - Quality gates
- risk-based-testing - Risk-informed metrics
- shift-right-testing - Production metrics
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.