quality-metrics — community quality-metrics, ai-news-influencer, community, ide skills

v1.0.0

Sobre este Skill

Ideal para Agentes de IA que necessitam de monitoramento de qualidade avançado e análise de métricas DORA para desenvolvimento de software otimizado. Measure quality effectively with actionable metrics. Use when establishing quality dashboards, defining KPIs, or evaluating test effectiveness.

natea natea
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Updated: 1/13/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 9/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
9/11
Quality Score
56
Canonical Locale
en
Detected Body Locale
en

Ideal para Agentes de IA que necessitam de monitoramento de qualidade avançado e análise de métricas DORA para desenvolvimento de software otimizado. Measure quality effectively with actionable metrics. Use when establishing quality dashboards, defining KPIs, or evaluating test effectiveness.

Por que usar essa habilidade

Habilita os agentes a rastrear indicadores-chave de desempenho, como frequência de implantação, tempo de lead e taxa de falha de alterações, utilizando métricas de engajamento para aprimorar suas estratégias e melhorar a qualidade do código por meio de portas de qualidade e limites.

Melhor para

Ideal para Agentes de IA que necessitam de monitoramento de qualidade avançado e análise de métricas DORA para desenvolvimento de software otimizado.

Casos de Uso Práticos for quality-metrics

Monitorar o Twitter para notícias e tendências relevantes para informar o desenvolvimento
Gerar conteúdo atraente do LinkedIn com base em métricas de qualidade e princípios DORA
Analisar taxas de escape de bugs e tempo médio de detecção (MTTD) para melhoria de processo

! Segurança e Limitações

  • Requer acesso às APIs do Twitter e do LinkedIn para monitoramento de mídia social e geração de conteúdo
  • Concentra-se em métricas DORA, que podem não ser aplicáveis a todos os ambientes ou equipes de desenvolvimento

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is quality-metrics?

Ideal para Agentes de IA que necessitam de monitoramento de qualidade avançado e análise de métricas DORA para desenvolvimento de software otimizado. Measure quality effectively with actionable metrics. Use when establishing quality dashboards, defining KPIs, or evaluating test effectiveness.

How do I install quality-metrics?

Run the command: npx killer-skills add natea/ai-news-influencer/quality-metrics. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for quality-metrics?

Key use cases include: Monitorar o Twitter para notícias e tendências relevantes para informar o desenvolvimento, Gerar conteúdo atraente do LinkedIn com base em métricas de qualidade e princípios DORA, Analisar taxas de escape de bugs e tempo médio de detecção (MTTD) para melhoria de processo.

Which IDEs are compatible with quality-metrics?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for quality-metrics?

Requer acesso às APIs do Twitter e do LinkedIn para monitoramento de mídia social e geração de conteúdo. Concentra-se em métricas DORA, que podem não ser aplicáveis a todos os ambientes ou equipes de desenvolvimento.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add natea/ai-news-influencer/quality-metrics. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use quality-metrics immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

quality-metrics

Install quality-metrics, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

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 rateTest case count
MTTD (detection)Lines of test code
MTTR (recovery)Test executions
Change failure rateCoverage % (alone)
Lead time for changesRequirements traced

DORA Metrics

MetricEliteHighMediumLow
Deploy FrequencyOn-demandWeeklyMonthlyYearly
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

MetricBlocking ThresholdWarning
Test pass rate100%-
Critical coverage> 80%> 70%
Security critical0-
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
1// Agent generates quality dashboard 2await Task("Generate Dashboard", { 3 metrics: { 4 delivery: ['deployment-frequency', 'lead-time', 'change-failure-rate'], 5 quality: ['bug-escape-rate', 'test-effectiveness', 'defect-density'], 6 stability: ['mttd', 'mttr', 'availability'], 7 process: ['code-review-time', 'flaky-test-rate', 'coverage-trend'] 8 }, 9 visualization: 'grafana', 10 alerts: { 11 critical: { bug_escape_rate: '>20%', mttr: '>24h' }, 12 warning: { coverage: '<70%', flaky_rate: '>5%' } 13 } 14}, "qe-quality-analyzer");

Quality Gate Configuration

json
1{ 2 "qualityGates": { 3 "commit": { 4 "coverage": { "min": 80, "blocking": true }, 5 "lint": { "errors": 0, "blocking": true } 6 }, 7 "pr": { 8 "tests": { "pass": "100%", "blocking": true }, 9 "security": { "critical": 0, "blocking": true }, 10 "coverage_delta": { "min": 0, "blocking": false } 11 }, 12 "release": { 13 "e2e": { "pass": "100%", "blocking": true }, 14 "performance_p95": { "max_ms": 200, "blocking": true }, 15 "bug_escape_rate": { "max": "10%", "blocking": false } 16 } 17 } 18}

Agent-Assisted Metrics

typescript
1// Calculate quality trends 2await Task("Quality Trend Analysis", { 3 timeframe: '90d', 4 metrics: ['bug-escape-rate', 'mttd', 'test-effectiveness'], 5 compare: 'previous-90d', 6 predictNext: '30d' 7}, "qe-quality-analyzer"); 8 9// Evaluate quality gate 10await Task("Quality Gate Evaluation", { 11 buildId: 'build-123', 12 environment: 'staging', 13 metrics: currentMetrics, 14 policy: qualityPolicy 15}, "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
1const metricsFleet = await FleetManager.coordinate({ 2 strategy: 'quality-metrics', 3 agents: [ 4 'qe-quality-analyzer', // Trend analysis 5 'qe-test-executor', // Test metrics 6 'qe-coverage-analyzer', // Coverage data 7 'qe-production-intelligence', // Production metrics 8 'qe-quality-gate' // Gate decisions 9 ], 10 topology: 'mesh' 11});

Common Traps

TrapProblemSolution
Coverage worship100% coverage, bugs still escapeMeasure bug escape rate instead
Test count focusMany tests, slow feedbackMeasure execution time
Activity metricsBusy work, no outcomesMeasure outcomes (MTTD, MTTR)
Point-in-timeSnapshot without contextTrack trends over time


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.

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