
test-reporting-analytics
by proffesor-for-testing
Agentic QE Fleet is an open-source AI-powered quality engineering platform designed for use with Claude Code, featuring specialized agents and skills to support testing activities for a product at any stage of the SDLC. Free to use, fork, build, and contribute. Based on the Agentic QE Framework created by Dragan Spiridonov.
SKILL.md
name: test-reporting-analytics description: "Advanced test reporting, quality dashboards, predictive analytics, trend analysis, and executive reporting for QE metrics. Use when communicating quality status, tracking trends, or making data-driven decisions." category: analytics priority: high tokenEstimate: 850 agents: [qe-quality-analyzer, qe-quality-gate, qe-deployment-readiness] implementation_status: optimized optimization_version: 1.0 last_optimized: 2025-12-03 dependencies: [] quick_reference_card: true tags: [reporting, analytics, dashboards, metrics, trends, predictive]
Test Reporting & Analytics
<default_to_action> When building test reports:
- DEFINE audience (dev team vs executives)
- CHOOSE key metrics (max 5-7)
- SHOW trends (not just snapshots)
- HIGHLIGHT actions (what to do about it)
- AUTOMATE generation
Dashboard Quick Setup:
+------------------+------------------+------------------+
| Tests Passed | Code Coverage | Flaky Tests |
| 1,247/1,250 ✅ | 82.3% ⬆️ +2.1% | 1.2% ⬇️ -0.3% |
+------------------+------------------+------------------+
| Critical Bugs | Deploy Freq | MTTR |
| 0 open ✅ | 12x/day ⬆️ | 2.3h ⬇️ |
+------------------+------------------+------------------+
Key Metrics by Audience:
- Dev Team: Pass rate, flaky %, execution time, coverage gaps
- QE Team: Defect detection rate, test velocity, automation ROI
- Leadership: Escaped defects, deployment frequency, quality cost </default_to_action>
Quick Reference Card
Essential Metrics
| Category | Metric | Target |
|---|---|---|
| Execution | Pass Rate | >98% |
| Execution | Flaky Test % | <2% |
| Execution | Suite Duration | <10 min |
| Coverage | Line Coverage | >80% |
| Coverage | Branch Coverage | >70% |
| Quality | Escaped Defects | <5/release |
| Quality | MTTR | <4 hours |
| Efficiency | Automation Rate | >90% |
Trend Indicators
| Symbol | Meaning | Action |
|---|---|---|
| ⬆️ | Improving | Continue current approach |
| ⬇️ | Declining | Investigate root cause |
| ➡️ | Stable | Maintain or improve |
| ⚠️ | Threshold breach | Immediate attention |
Report Types
Real-Time Dashboard
Live quality status for CI/CD
- Build status (green/red)
- Test results (pass/fail counts)
- Coverage delta
- Flaky test alerts
Sprint Summary
## Sprint 47 Quality Summary
### Metrics
| Metric | Value | Trend |
|--------|-------|-------|
| Tests Added | +47 | ⬆️ |
| Coverage | 82.3% | ⬆️ +2.1% |
| Bugs Found | 12 | ➡️ |
| Escaped | 0 | ✅ |
### Highlights
- ✅ Zero escaped defects
- ⚠️ E2E suite now 45min (target: 30min)
### Actions
1. Optimize slow E2E tests
2. Add coverage for payment module
Executive Report
## Monthly Quality Report - Oct 2025
### Executive Summary
✅ Production uptime: 99.97% (target: 99.95%)
✅ Deploy frequency: 12x/day (up from 8x)
⚠️ Coverage: 82.3% (target: 85%)
### Business Impact
- Automation saves 120 hrs/month
- Bug cost: $150/bug found vs $5,000 escaped
- Estimated annual savings: $450K
### Recommendations
1. Invest in performance testing tooling
2. Hire senior QE for mobile coverage
Predictive Analytics
// Predict test failures
const prediction = await Task("Predict Failures", {
codeChanges: prDiff,
historicalData: last90Days,
model: 'gradient-boosting'
}, "qe-quality-analyzer");
// Returns:
// {
// failureProbability: 0.73,
// likelyFailingTests: ['payment.test.ts'],
// suggestedAction: 'Review payment module carefully',
// confidence: 0.89
// }
// Trend analysis with anomaly detection
const trends = await Task("Analyze Trends", {
metrics: ['passRate', 'coverage', 'flakyRate'],
period: '30d',
detectAnomalies: true
}, "qe-quality-analyzer");
Agent Integration
// Generate comprehensive quality report
const report = await Task("Generate Quality Report", {
period: 'sprint',
audience: 'executive',
includeROI: true,
includeTrends: true
}, "qe-quality-analyzer");
// Real-time quality gate check
const gateResult = await Task("Quality Gate Check", {
metrics: currentMetrics,
thresholds: qualityPolicy,
environment: 'production'
}, "qe-quality-gate");
Agent Coordination Hints
Memory Namespace
aqe/reporting/
├── dashboards/* - Dashboard configurations
├── reports/* - Generated reports
├── trends/* - Trend analysis data
└── predictions/* - Predictive model outputs
Fleet Coordination
const reportingFleet = await FleetManager.coordinate({
strategy: 'quality-reporting',
agents: [
'qe-quality-analyzer', // Metrics aggregation
'qe-quality-gate', // Threshold validation
'qe-deployment-readiness' // Release readiness
],
topology: 'parallel'
});
Related Skills
- quality-metrics - Metric definitions
- shift-right-testing - Production metrics
- consultancy-practices - Client reporting
Remember
Measure to improve. Report to communicate.
Good reports:
- Answer "so what?" (actionable insights)
- Show trends (not just snapshots)
- Match audience needs
- Automate where possible
Data without action is noise. Action without data is guessing.
Score
Total Score
Based on repository quality metrics
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Reviews
Reviews coming soon

