qe-quality-metrics
Measure quality effectively with actionable metrics. Use when establishing quality dashboards, defining KPIs, or evaluating test effectiveness.
Best use case
qe-quality-metrics is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Measure quality effectively with actionable metrics. Use when establishing quality dashboards, defining KPIs, or evaluating test effectiveness.
Teams using qe-quality-metrics should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/qe-quality-metrics/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How qe-quality-metrics Compares
| Feature / Agent | qe-quality-metrics | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Measure quality effectively with actionable metrics. Use when establishing quality dashboards, defining KPIs, or evaluating test effectiveness.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# 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 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
```typescript
// 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
```json
{
"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
```typescript
// 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
```typescript
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](../agentic-quality-engineering/) - Agent coordination
- [cicd-pipeline-qe-orchestrator](../cicd-pipeline-qe-orchestrator/) - Quality gates
- [risk-based-testing](../risk-based-testing/) - Risk-informed metrics
- [shift-right-testing](../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.Related Skills
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