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qe-quality-assessment质量评价

Agent Skill

qe-quality-assessment 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,011

周安装

43

GitHub Stars

331

下载量

354
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:qe-quality-assessment(质量评价)
来源仓库:https://github.com/proffesor-for-testing/agentic-qe
仓库路径:skills/qe-quality-assessment
安装命令:
npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill qe-quality-assessment
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill qe-quality-assessment

简介

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合围绕仓库状态、代码变更或协作事项进行整理。
  • 可结合来源仓库、安装命令和原始 README 继续核验具体用法。
  • 安装前建议确认权限范围、维护状态及是否触发联网或文件读写。
  • 注意是否会执行命令或修改协作内容,确保操作合规。

SKILL.md

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

Run History

After each quality assessment, append results to run-history.json in this skill directory:

node -e "
const fs = require('fs');
const h = JSON.parse(fs.readFileSync('.claude/skills/qe-quality-assessment/run-history.json'));
h.runs.push({date: new Date().toISOString().split('T')[0], gate_result: 'PASS_OR_FAIL', failed_checks: []});
fs.writeFileSync('.claude/skills/qe-quality-assessment/run-history.json', JSON.stringify(h, null, 2));
"

Read run-history.json before each run — alert if quality gate failed 3 of last 5 runs.

Skill Composition

  • Before assessment → Run /qe-coverage-analysis and /mutation-testing first
  • If issues found → Use /test-failure-investigator to diagnose failures
  • For PR review → Combine with /code-review-quality for comprehensive review

Gotchas

  • NEVER trust agent-reported pass/fail status — 12 test failures were caught that agents claimed were passing (Nagual pattern, reward 0.92)
  • Completion theater: agent hardcoded version '3.0.0' instead of reading from package.json — verify actual values in output
  • Fix issues in priority waves (P0 → P1 → P2) with verification between each wave — don't fix everything in parallel
  • quality-assessment domain has 53.7% success rate — expect failures and have fallback
  • If HybridMemoryBackend initialization fails, run aqe health to diagnose, or aqe init to re-initialize

Coordination

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

27.94%
按下载量换算99

windsurf

20.77%
按下载量换算74

trae

17.97%
按下载量换算64

OpenCode

10.99%
按下载量换算39

Codex

6.94%
按下载量换算25

Antigravity

3.59%
按下载量换算13

安全审计

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Snyk

通过

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安装前确认

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来源信息

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