qa-expert

charon-fan/agent-playbook · updated Apr 8, 2026

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$npx skills add https://github.com/charon-fan/agent-playbook --skill qa-expert
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summary

Quality assurance specialist for developing comprehensive testing strategies and quality gates.

skill.md

QA Expert

Quality assurance specialist for developing comprehensive testing strategies and quality gates.

When This Skill Activates

Activates when you:

  • Ask for QA strategy
  • Need quality gates
  • Want to improve test coverage
  • Plan testing approach

Quality Assurance Strategy

1. Risk-Based Testing

Prioritize testing based on risk:

Risk Level Testing Approach
Critical (Money, Security, Data) 100% automation, chaos testing
High (Core features) Full E2E, integration, unit
Medium (Secondary features) Integration, unit
Low (Edge features) Unit tests only

2. Testing Pyramid Allocation

Level % of Tests Focus
E2E 10% Critical user journeys
Integration 30% API interactions
Unit 60% Business logic, utilities

3. Quality Gates

Pre-Commit

- Lint: npm run lint
- Format check: npm run format:check
- Type check: npm run type-check
- Unit tests: npm run test:unit

Pre-Merge

- All tests: npm test
- Coverage threshold: > 80%
- Security scan: npm audit
- License check: npm run check:licenses

Pre-Production

- Full test suite: npm run test:all
- E2E tests: npm run test:e2e
- Performance tests: npm run test:perf
- Security audit: npm audit --audit-level high

Test Categories

Functional Testing

Purpose: Verify features work as specified

  • Happy path testing
  • Edge case testing
  • Boundary value analysis
  • Error handling

Non-Functional Testing

Performance

  • Response time < 200ms (p95)
  • Throughput > 1000 req/s
  • Memory usage stable
  • No memory leaks

Security

  • OWASP Top 10 coverage
  • Penetration testing
  • Dependency vulnerability scan
  • Secrets detection

Compatibility

  • Browser testing (Chrome, Firefox, Safari, Edge)
  • Device testing (Mobile, Desktop, Tablet)
  • OS testing (Windows, macOS, Linux)
  • Version testing (N-1 browser versions)

Regression Testing

  • Previous bugs don't reappear
  • New features don't break existing features
  • Performance doesn't degrade

Exploratory Testing

  • Find unexpected issues
  • Test edge cases
  • User experience issues

Test Planning

Test Plan Template

# Test Plan: [Feature Name]

## Overview
[Feature description]

## Scope
[In scope / Out of scope]

## Test Cases

### Functional
- [ ] TC001: [Description]
- [ ] TC002: [Description]

### Integration
- [ ] TC101: [Description]

### E2E
- [ ] TC201: [Description]

## Test Data
[Required test data]

## Environment
[Test environment setup]

## Schedule
[Testing timeline]

## Exit Criteria
[Definition of done]

Quality Metrics

Code Quality

  • Test Coverage: > 80%
  • Cyclomatic Complexity: < 10 per function
  • Code Duplication: < 5%
  • Technical Debt Ratio: < 5%

Defect Metrics

  • Defect Density: < 1 defect per 1000 LOC
  • Critical Defects: 0
  • High Defects: 0
  • Medium Defects: < 3

Test Metrics

  • Test Pass Rate: > 95%
  • Flaky Tests: 0
  • Test Execution Time: < 10 minutes

Automation Strategy

Automate When

  • Test is run frequently
  • Test has deterministic results
  • Test is stable
  • ROI justifies automation cost

Don't Automate When

  • Test requires human judgment
  • Test is exploratory
  • Test is one-time only
  • Test changes frequently

Bug Report Template

## Bug Summary
[One-line summary]

## Severity
Critical / High / Medium / Low

## Steps to Reproduce
1.
2.
3.

## Expected Behavior
[What should happen]

## Actual Behavior
[What actually happens]

## Environment
- OS:
- Browser:
- Version:

## Attachments
[Screenshots, logs, etc.]

Scripts

Generate test plan:

python scripts/generate_test_plan.py <feature>

Analyze test coverage:

python scripts/coverage_analysis.py

References

  • references/strategy.md - Testing strategies
  • references/gates.md - Quality gate definitions
  • references/metrics.md - QA metrics and KPIs
how to use qa-expert

How to use qa-expert on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add qa-expert
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/charon-fan/agent-playbook --skill qa-expert

The skills CLI fetches qa-expert from GitHub repository charon-fan/agent-playbook and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/qa-expert

Reload or restart Cursor to activate qa-expert. Access the skill through slash commands (e.g., /qa-expert) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.756 reviews
  • Isabella Zhang· Dec 24, 2024

    Solid pick for teams standardizing on skills: qa-expert is focused, and the summary matches what you get after install.

  • Emma Garcia· Dec 20, 2024

    Keeps context tight: qa-expert is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Hassan Liu· Dec 16, 2024

    We added qa-expert from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Tariq Lopez· Dec 12, 2024

    qa-expert has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Dec 4, 2024

    qa-expert fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Nia Desai· Dec 4, 2024

    qa-expert fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yash Thakker· Nov 23, 2024

    qa-expert is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Amina Park· Nov 23, 2024

    qa-expert is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Ren Desai· Nov 19, 2024

    Keeps context tight: qa-expert is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Anaya Johnson· Nov 11, 2024

    Solid pick for teams standardizing on skills: qa-expert is focused, and the summary matches what you get after install.

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