菜单
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.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill test-reporting-analytics命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Ruflo is a multi-agent orchestration platform for AI coding agents (Claude Code, Cursor, Codex, Copilot, Gemini, Amp, +12 more). Use this skill when the user wants to (1) install/init ruflo in a project, (2) run multi-agent swarms with hierarchical coordination, (3) use ruflo's 314+ MCP tools for memory, routing, hooks, sub-agents, or workflows, (4) check ruflo status/version/doctor health, or (5) discover which of ruflo's 30+ plugins fits their task.
Build dependency-aware execution plans for complex Agentic QE, Ruflo, integration, migration, or multi-stream engineering programs. Use when Codex must turn research or requirements into phased work, select a small AQE fleet, map critical paths and parallel streams, define acceptance gates, or sequence risky changes. Use aqe-plan-quality instead when the primary output is only a test or quality plan.
Conduct evidence-first technical research for Agentic QE, Ruflo, related ruvnet projects, or external tools. Use when Codex must investigate a repository, compare current upstream changes, trace dependencies and history, distinguish verified facts from inference, or synthesize findings into actionable engineering recommendations. Do not use for a simple known-answer lookup or an implementation-only task.
正在显示 SKILL.md
基于 SOC 职业分类
| 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 |
| last_optimized | "2025-12-03T00:00:00.000Z" |
| dependencies | [] |
| quick_reference_card | true |
| tags | ["reporting","analytics","dashboards","metrics","trends","predictive"] |
| trust_tier | 3 |
| validation | {"schema_path":"schemas/output.json","validator_path":"scripts/validate-config.json","eval_path":"evals/test-reporting-analytics.yaml"} |
<default_to_action> When building test reports:
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:
| 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% |
| Symbol | Meaning | Action |
|---|---|---|
| ⬆️ | Improving | Continue current approach |
| ⬇️ | Declining | Investigate root cause |
| ➡️ |
| Stable |
| Maintain or improve |
| ⚠️ | Threshold breach | Immediate attention |
Live quality status for CI/CD
- Build status (green/red)
- Test results (pass/fail counts)
- Coverage delta
- Flaky test alerts
## 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
## 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
// 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");
// 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");
aqe/reporting/
├── dashboards/* - Dashboard configurations
├── reports/* - Generated reports
├── trends/* - Trend analysis data
└── predictions/* - Predictive model outputs
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'
});
Measure to improve. Report to communicate.
Good reports:
Data without action is noise. Action without data is guessing.