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Agent skill

Qe Quality Metrics

by proffesor-for-testing in proffesor-for-testing/agentic-qe

Measure quality effectively with actionable metrics. An agent skill from proffesor-for-testing/agentic-qe.

MITAuto-check passedTesting & QA

Install Qe Quality Metrics

skills CLI
$ npx skills add proffesor-for-testing/agentic-qe --skill qe-quality-metrics -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install proffesor-for-testing/agentic-qe qe-quality-metrics --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/proffesor-for-testing/agentic-qe.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.kiro/skills/qe-quality-metrics .claude/skills/qe-quality-metrics && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
qe-quality-metrics
GitHub stars
495
Token cost
~1.5k tokens
SKILL.md length
370 words
Files
1
Skills in repo
93
Repo updated
First seen
Licence
MIT

At a glance

Measure quality effectively with actionable metrics. An agent skill from proffesor-for-testing/agentic-qe.

  • Works in 5 steps: MEASURE outcomes (bug escape rate, MTTD)… → FOCUS on DORA metrics: Deployment… → AVOID vanity metrics: 100% coverage… → …
  • Establishing quality dashboards
  • SKILL.md covers Quick Reference Card, Core Metrics, Dashboard Design and Quality Gate Configuration, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Qe Quality Metrics is an agent skill from proffesor-for-testing/agentic-qe. Measure quality effectively with actionable metrics. Use when establishing quality dashboards, defining KPIs, or evaluating test effectiveness.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Testing & QA, covering OKRs and executive reporting. The repository describes itself as: Agentic QE Fleet is an open-source AI-powered QA/QE platform designed for use with Coding Agents (works best with Claude Code) featuring specialized agents and skills to support… The licence is MIT.

When your agent uses it

  • Establishing quality dashboards
  • Evaluating test effectiveness

Example prompts

  • “/qe-quality-metrics”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  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

What it can do on your machine

Read from SKILL.md and the folder at commit 1363bc7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript and json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Qe Quality Metrics loads about 1.5k tokens when it runs. Until then it costs about 41 tokens; SKILL.md has 370 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~41
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from proffesor-for-testing/agentic-qe at commit 1363bc7, republished under its MIT licence (© proffesor-for-testing). 370 words, ~1,537 tokens.

Download SKILL.mdSave it as .claude/skills/qe-quality-metrics/SKILL.md (or your agent's skills folder).
name
qe-quality-metrics
description
Measure quality effectively with actionable metrics. Use when establishing quality dashboards, defining KPIs, or evaluating test effectiveness.
inclusion
auto
tags
metrics, dora, quality-gates, dashboards, kpis, measurement

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
Show full SKILL.md (161 more words)Show less
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
// 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

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.

© proffesor-for-testing, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .kiro/skills/qe-quality-metrics of proffesor-for-testing/agentic-qe.

Open the folder on GitHubat commit 1363bc7

Compare with similar skills

Qe Quality Metrics next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Qe Quality Metrics compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Qe Quality Metrics this skillproffesor-for-testing/agentic-qe495—~1.5kAutomated safety check: PassMIT
QA Metricspetrkindlmann/qa-skills170—~5.3kAutomated safety check: PassMIT
High Token ModeLomnus-ai/TokenBurner173—~9.1kAutomated safety check: PassMIT
Web Application Testinganthropics/skills180k51 repos~966Automated safety check: PassApache-2.0
Diagnosing Bugsfossasia/eventyay-interpretation1.6k32 repos~2.1kAutomated safety check: PassApache-2.0
TDDpietheinstrengholt/rssmonster56430 repos~906Automated safety check: PassMIT

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Categories

Questions about Qe Quality Metrics

What does Qe Quality Metrics do?

Measure quality effectively with actionable metrics. An agent skill from proffesor-for-testing/agentic-qe. Qe Quality Metrics is an agent skill from proffesor-for-testing/agentic-qe. Measure quality effectively with actionable metrics.

When should I use Qe Quality Metrics?

Qe Quality Metrics fits situations like: establishing quality dashboards; evaluating test effectiveness.

How do I install Qe Quality Metrics in Claude Code?

Run `npx skills add proffesor-for-testing/agentic-qe --skill qe-quality-metrics -a claude-code`. Or copy the skill folder (.kiro/skills/qe-quality-metrics in proffesor-for-testing/agentic-qe) into .claude/skills/qe-quality-metrics in your project. Claude Code loads it when a task matches its description.

How do I install Qe Quality Metrics in Codex?

Run `npx skills add proffesor-for-testing/agentic-qe --skill qe-quality-metrics -a codex`. Or copy the skill folder (.kiro/skills/qe-quality-metrics in proffesor-for-testing/agentic-qe) into .agents/skills/qe-quality-metrics in your project. Codex loads it when a task matches its description.

Can I use Qe Quality Metrics in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add proffesor-for-testing/agentic-qe --skill qe-quality-metrics -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qe-quality-metrics, .gemini/skills/qe-quality-metrics, .github/skills/qe-quality-metrics and .opencode/skills/qe-quality-metrics in your project.

What does Qe Quality Metrics need to run?

SKILL.md names no scripts, command-line tools or credentials: Qe Quality Metrics is instructions for the agent only.

Does Qe Quality Metrics access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Qe Quality Metrics safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Qe Quality Metrics use?

Qe Quality Metrics is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Qe Quality Metrics use?

About 1.5k tokens (SKILL.md is roughly 6.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Qe Quality Metrics?

Skills that share tags, products or a category with Qe Quality Metrics: QA Metrics (petrkindlmann/qa-skills, 170 stars), High Token Mode (Lomnus-ai/TokenBurner, 173 stars), Web Application Testing (anthropics/skills, 180k stars) and Diagnosing Bugs (fossasia/eventyay-interpretation, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Qe Quality Metrics?

proffesor-for-testing (a GitHub user) maintains it in proffesor-for-testing/agentic-qe, which has 495 GitHub stars. The repository holds 93 skills in this directory. The repository was last updated on October 9, 2026.

Source: proffesor-for-testing/agentic-qe on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.