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Agent Skill · AI 工具

qa-expert(质量保证专家)

qa-expert 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。

qa-expert 是AI 工具类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描有提醒项,按安装量在AI 工具类的 2,536 个 Skill 里排第 167。

总安装 14,223周安装 581GitHub Stars 956下载 4,602核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:qa-expert(质量保证专家)
来源仓库:https://github.com/daymade/claude-code-skills
仓库路径:skills/qa-expert
安装命令:
npx skills add https://github.com/daymade/claude-code-skills --skill qa-expert
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/daymade/claude-code-skills --skill qa-expert

这个 Skill 是做什么的

AI 工具类 Skill 用来扩展助手本身的能力,例如接模型、接检索、接外部服务。

qa-expert 建立符合 Google Testing Standards 与 OWASP 的安全测试体系。提供 AAA 模式测试用例模板、P0-P4 严重度分级与覆盖率统计工具。集成静态扫描、动态渗透与模糊测试,覆盖前端、后端与 API 安全域。每日生成测试摘要与每周质量趋势报告,支持持续改进闭环。

适用于新项目初始化或遗留系统加固,快速搭建可落地的质量门禁。

来源仓库内路径:skills/qa-expert

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/daymade/claude-code-skills --skill qa-expert;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

qa-expert 怎么安装?

在终端执行 npx skills add https://github.com/daymade/claude-code-skills --skill qa-expert。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

qa-expert 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

qa-expert 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

qa-expert 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

qa-expert 用的人多吗?

公开数据是累计安装 14,223 次,近一周安装 581 次,下载 4,602 次,GitHub 956 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

qa-expert 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理AI 工具类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

AI 工具类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
executing-plans

执行计划 · Codex、Claude

1,515,336173,110只读MIT通过
verification-before-completion

完成前的验证 · Codex、Claude

1,319,472173,121权限未标注MIT通过
subagent-driven-development

子 Agent 驱动开发 · Codex、Claude

1,312,416173,138只读MIT通过
copy-editing

复制编辑 · Codex、Claude

1,209,57625,632只读MIT通过
paywall-upgrade-cro

付费专区升级 cro · Codex、Claude

1,030,17625,617只读MIT通过
qa-expert

质量保证专家 · 本页

14,223956需要联网MIT有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

QA Expert

Establish world-class QA testing processes for any software project using proven methodologies from Google Testing Standards and OWASP security best practices.

When to Use This Skill

Trigger this skill when:

  • Setting up QA infrastructure for a new or existing project
  • Writing standardized test cases (AAA pattern compliance)
  • Executing comprehensive test plans with progress tracking
  • Implementing security testing (OWASP Top 10)
  • Filing bugs with proper severity classification (P0-P4)
  • Generating QA reports (daily summaries, weekly progress)
  • Calculating quality metrics (pass rate, coverage, gates)
  • Preparing QA documentation for third-party team handoffs
  • Enabling autonomous LLM-driven test execution

Quick Start

One-command initialization:

python scripts/init_qa_project.py <project-name> [output-directory]

What gets created:

  • Directory structure (tests/docs/, tests/e2e/, tests/fixtures/)
  • Tracking CSVs (TEST-EXECUTION-TRACKING.csv, BUG-TRACKING-TEMPLATE.csv)
  • Documentation templates (BASELINE-METRICS.md, WEEKLY-PROGRESS-REPORT.md)
  • Master QA Prompt for autonomous execution
  • README with complete quickstart guide

For autonomous execution (recommended): See references/master_qa_prompt.md - single copy-paste command for 100x speedup.

Core Capabilities

1. QA Project Initialization

Initialize complete QA infrastructure with all templates:

python scripts/init_qa_project.py <project-name> [output-directory]

Creates directory structure, tracking CSVs, documentation templates, and master prompt for autonomous execution.

Use when: Starting QA from scratch or migrating to structured QA process.

2. Test Case Writing

Write standardized, reproducible test cases following AAA pattern (Arrange-Act-Assert):

  1. Read template: assets/templates/TEST-CASE-TEMPLATE.md
  2. Follow structure: Prerequisites (Arrange) → Test Steps (Act) → Expected Results (Assert)
  3. Assign priority: P0 (blocker) → P4 (low)
  4. Include edge cases and potential bugs

Test case format: TC-[CATEGORY]-[NUMBER] (e.g., TC-CLI-001, TC-WEB-042, TC-SEC-007)

Reference: See references/google_testing_standards.md for complete AAA pattern guidelines and coverage thresholds.

3. Test Execution & Tracking

Ground Truth Principle (critical):

  • Test case documents (e.g., 02-CLI-TEST-CASES.md) = authoritative source for test steps
  • Tracking CSV = execution status only (do NOT trust CSV for test specifications)
  • See references/ground_truth_principle.md for preventing doc/CSV sync issues

Manual execution:

  1. Read test case from category document (e.g., 02-CLI-TEST-CASES.md) ← always start here
  2. Execute test steps exactly as documented
  3. Update TEST-EXECUTION-TRACKING.csv immediately after EACH test (never batch)
  4. File bug in BUG-TRACKING-TEMPLATE.csv if test fails

Autonomous execution (recommended):

  1. Copy master prompt from references/master_qa_prompt.md
  2. Paste to LLM session
  3. LLM auto-executes, auto-tracks, auto-files bugs, auto-generates reports

Innovation: 100x faster vs manual + zero human error in tracking + auto-resume capability.

4. Bug Reporting

File bugs with proper severity classification:

Required fields:

  • Bug ID: Sequential (BUG-001, BUG-002,...)
  • Severity: P0 (24h fix) → P4 (optional)
  • Steps to Reproduce: Numbered, specific
  • Environment: OS, versions, configuration

Severity classification:

  • P0 (Blocker): Security vulnerability, core functionality broken, data loss
  • P1 (Critical): Major feature broken with workaround
  • P2 (High): Minor feature issue, edge case
  • P3 (Medium): Cosmetic issue
  • P4 (Low): Documentation typo

Reference: See BUG-TRACKING-TEMPLATE.csv for complete template with examples.

5. Quality Metrics Calculation

Calculate comprehensive QA metrics and quality gates status:

python scripts/calculate_metrics.py <path/to/TEST-EXECUTION-TRACKING.csv>

Metrics dashboard includes:

  • Test execution progress (X/Y tests, Z% complete)
  • Pass rate (passed/executed %)
  • Bug analysis (unique bugs, P0/P1/P2 breakdown)
  • Quality gates status (✅/❌ for each gate)

Quality gates (all must pass for release):

GateTargetBlocker
Test Execution100%Yes
Pass Rate≥80%Yes
P0 Bugs0Yes
P1 Bugs≤5Yes
Code Coverage≥80%Yes
Security90% OWASPYes

6. Progress Reporting

Generate QA reports for stakeholders:

Daily summary (end-of-day):

  • Tests executed, pass rate, bugs filed
  • Blockers (or None)
  • Tomorrow's plan

Weekly report (every Friday):

  • Use template: WEEKLY-PROGRESS-REPORT.md (created by init script)
  • Compare against baseline: BASELINE-METRICS.md
  • Assess quality gates and trends

Reference: See references/llm_prompts_library.md for 30+ ready-to-use reporting prompts.

7. Security Testing (OWASP)

Implement OWASP Top 10 security testing:

Coverage targets:

  1. A01: Broken Access Control - RLS bypass, privilege escalation
  2. A02: Cryptographic Failures - Token encryption, password hashing
  3. A03: Injection - SQL injection, XSS, command injection
  4. A04: Insecure Design - Rate limiting, anomaly detection
  5. A05: Security Misconfiguration - Verbose errors, default credentials
  6. A07: Authentication Failures - Session hijacking, CSRF
  7. Others: Data integrity, logging, SSRF

Target: 90% OWASP coverage (9/10 threats mitigated).

Each security test follows AAA pattern with specific attack vectors documented.

Day 1 Onboarding

For new QA engineers joining a project, complete 5-hour onboarding guide:

Read: references/day1_onboarding.md

Timeline:

  • Hour 1: Environment setup (database, dev server, dependencies)
  • Hour 2: Documentation review (test strategy, quality gates)
  • Hour 3: Test data setup (users, CLI, DevTools)
  • Hour 4: Execute first test case
  • Hour 5: Team onboarding & Week 1 planning

Checkpoint: By end of Day 1, environment running, first test executed, ready for Week 1.

Autonomous Execution (⭐ Recommended)

Enable LLM-driven autonomous QA testing with single master prompt:

Read: references/master_qa_prompt.md

Features:

  • Auto-resume from last completed test (reads tracking CSV)
  • Auto-execute test cases (Week 1-5 progression)
  • Auto-track results (updates CSV after each test)
  • Auto-file bugs (creates bug reports for failures)
  • Auto-generate reports (daily summaries, weekly reports)
  • Auto-escalate P0 bugs (stops testing, notifies stakeholders)

Benefits:

  • 100x faster execution vs manual
  • Zero human error in tracking
  • Consistent bug documentation
  • Immediate progress visibility

Usage: Copy master prompt, paste to LLM, let it run autonomously for 5 weeks.

Adapting for Your Project

Small Project (50 tests)

  • Timeline: 2 weeks
  • Categories: 2-3 (e.g., Frontend, Backend)
  • Daily: 5-7 tests
  • Reports: Daily summary only

Medium Project (200 tests)

  • Timeline: 4 weeks
  • Categories: 4-5 (CLI, Web, API, DB, Security)
  • Daily: 10-12 tests
  • Reports: Daily + weekly

Large Project (500+ tests)

  • Timeline: 8-10 weeks
  • Categories: 6-8 (multiple components)
  • Daily: 10-15 tests
  • Reports: Daily + weekly + bi-weekly stakeholder

Reference Documents

Access detailed guidelines from bundled references:

  • references/day1_onboarding.md - 5-hour onboarding guide for new QA engineers
  • references/master_qa_prompt.md - Single command for autonomous LLM execution (100x speedup)
  • references/llm_prompts_library.md - 30+ ready-to-use prompts for specific QA tasks
  • references/google_testing_standards.md - AAA pattern, coverage thresholds, fail-fast validation
  • references/ground_truth_principle.md - Preventing doc/CSV sync issues (critical for test suite integrity)

Assets & Templates

Test case templates and bug report formats:

  • assets/templates/TEST-CASE-TEMPLATE.md - Complete template with CLI and security examples

Scripts

Automation scripts for QA infrastructure:

  • scripts/init_qa_project.py - Initialize QA infrastructure (one command setup)
  • scripts/calculate_metrics.py - Generate quality metrics dashboard

Common Patterns

Pattern 1: Starting Fresh QA

1. python scripts/init_qa_project.py my-app ./
2. Fill in BASELINE-METRICS.md (document current state)
3. Write test cases using assets/templates/TEST-CASE-TEMPLATE.md
4. Copy master prompt from references/master_qa_prompt.md
5. Paste to LLM → autonomous execution begins

Pattern 2: LLM-Driven Testing (Autonomous)

1. Read references/master_qa_prompt.md
2. Copy the single master prompt (one paragraph)
3. Paste to LLM conversation
4. LLM executes all 342 test cases over 5 weeks
5. LLM updates tracking CSVs automatically
6. LLM generates weekly reports automatically

Pattern 3: Adding Security Testing

1. Read references/google_testing_standards.md (OWASP section)
2. Write TC-SEC-XXX test cases for each OWASP threat
3. Target 90% coverage (9/10 threats)
4. Document mitigations in test cases

Pattern 4: Third-Party QA Handoff

1. Ensure all templates populated
2. Verify BASELINE-METRICS.md complete
3. Package tests/docs/ folder
4. Include references/master_qa_prompt.md for autonomous execution
5. QA team can start immediately (Day 1 onboarding → 5 weeks testing)

Success Criteria

This skill is effective when:

  • ✅ Test cases are reproducible by any engineer
  • ✅ Quality gates objectively measured
  • ✅ Bugs fully documented with repro steps
  • ✅ Progress visible in real-time (CSV tracking)
  • ✅ Autonomous execution enabled (LLM can execute full plan)
  • ✅ Third-party QA teams can start testing immediately

平台分布

Claude Code

27.78%
按下载量换算1,278

Antigravity

22.77%
按下载量换算1,048

OpenCode

18.79%
按下载量换算865

Gemini CLI

11.96%
按下载量换算550

Cursor

8.58%
按下载量换算395

Codex

3.66%
按下载量换算168

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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