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proffesor-for-testing

qe-quality-assessment

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.

132🍴 27📅 Jan 23, 2026

SKILL.md


name: "QE Quality Assessment" description: "Comprehensive quality gates, metrics analysis, and deployment readiness assessment for continuous quality assurance."

QE Quality Assessment

Purpose

Guide the use of v3's quality assessment capabilities including automated quality gates, metrics aggregation, trend analysis, and deployment readiness evaluation.

Activation

  • When evaluating code quality
  • When setting up quality gates
  • When assessing deployment readiness
  • When tracking quality metrics
  • When generating quality reports

Quick Start

# Run quality assessment
aqe quality assess --scope src/ --gates all

# Check deployment readiness
aqe quality deploy-ready --environment production

# Generate quality report
aqe quality report --format dashboard --period 30d

# Compare quality between releases
aqe quality compare --from v1.0 --to v2.0

Agent Workflow

// Comprehensive quality assessment
Task("Assess code quality", `
  Evaluate quality for src/:
  - Code complexity (cyclomatic, cognitive)
  - Test coverage and mutation score
  - Security vulnerabilities
  - Code smells and technical debt
  - Documentation coverage
  Generate quality score and recommendations.
`, "qe-quality-analyzer")

// Deployment readiness check
Task("Check deployment readiness", `
  Evaluate if release v2.1.0 is ready for production:
  - All tests passing
  - Coverage thresholds met
  - No critical vulnerabilities
  - Performance benchmarks passed
  - Documentation updated
  Provide go/no-go recommendation.
`, "qe-deployment-advisor")

Quality Dimensions

1. Code Quality Metrics

await qualityAnalyzer.assessCode({
  scope: 'src/**/*.ts',
  metrics: {
    complexity: {
      cyclomatic: { max: 15, warn: 10 },
      cognitive: { max: 20, warn: 15 }
    },
    maintainability: {
      index: { min: 65 },
      duplication: { max: 3 }  // percent
    },
    documentation: {
      publicAPIs: { min: 80 },
      complexity: { min: 70 }
    }
  }
});

2. Quality Gates

await qualityGate.evaluate({
  gates: {
    coverage: { min: 80, blocking: true },
    complexity: { max: 15, blocking: false },
    vulnerabilities: { critical: 0, high: 0, blocking: true },
    duplications: { max: 3, blocking: false },
    techDebt: { maxRatio: 5, blocking: false }
  },
  action: {
    onPass: 'proceed',
    onFail: 'block-merge',
    onWarn: 'notify'
  }
});

3. Deployment Readiness

await deploymentAdvisor.assess({
  release: 'v2.1.0',
  criteria: {
    testing: {
      unitTests: 'all-pass',
      integrationTests: 'all-pass',
      e2eTests: 'critical-pass',
      performanceTests: 'baseline-met'
    },
    quality: {
      coverage: 80,
      noNewVulnerabilities: true,
      noRegressions: true
    },
    documentation: {
      changelog: true,
      apiDocs: true,
      releaseNotes: true
    }
  }
});

Quality Score Calculation

quality_score:
  components:
    test_coverage:
      weight: 0.25
      metrics: [statement, branch, function]

    code_quality:
      weight: 0.20
      metrics: [complexity, maintainability, duplication]

    security:
      weight: 0.25
      metrics: [vulnerabilities, dependencies]

    reliability:
      weight: 0.20
      metrics: [bug_density, flaky_tests, error_rate]

    documentation:
      weight: 0.10
      metrics: [api_coverage, readme, changelog]

  scoring:
    A: 90-100
    B: 80-89
    C: 70-79
    D: 60-69
    F: 0-59

Quality Dashboard

interface QualityDashboard {
  overallScore: number;  // 0-100
  grade: 'A' | 'B' | 'C' | 'D' | 'F';
  dimensions: {
    name: string;
    score: number;
    trend: 'improving' | 'stable' | 'declining';
    issues: Issue[];
  }[];
  gates: {
    name: string;
    status: 'pass' | 'fail' | 'warn';
    value: number;
    threshold: number;
  }[];
  trends: {
    period: string;
    scores: number[];
    alerts: Alert[];
  };
  recommendations: Recommendation[];
}

CI/CD Integration

# Quality gate in pipeline
quality_check:
  stage: verify
  script:
    - aqe quality assess --gates all --output report.json
  rules:
    - if: $CI_PIPELINE_SOURCE == "merge_request_event"
  artifacts:
    reports:
      quality: report.json
  allow_failure:
    exit_codes:
      - 1  # Warnings only

Coordination

Primary Agents: qe-quality-analyzer, qe-deployment-advisor, qe-metrics-collector Coordinator: qe-quality-coordinator Related Skills: qe-coverage-analysis, qe-security-compliance

Score

Total Score

85/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

+10
説明文

100文字以上の説明がある

+10
人気

GitHub Stars 100以上

+5
最近の活動

1ヶ月以内に更新

+10
フォーク

10回以上フォークされている

+5
Issue管理

オープンIssueが50未満

+5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

+5

Reviews

💬

Reviews coming soon