daffy0208/ai-dev-standards/quality-assurance
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Comprehensive quality assurance combining testing strategy, code quality enforcement, and validation gates. Consolidated from testing-strategist, code-quality-enforcer, and validation-gate-checker.
Install
npx vskill@latest install daffy0208/ai-dev-standards/quality-assuranceSemi-extensibleMentions customization, but needs skill-specific knowledge. Read the extensible skills standard
SKILL.md
Quality Assurance
Overview
Quality Assurance is a consolidated skill that combines three critical quality dimensions: comprehensive testing strategy, code quality enforcement, and phase-gate validation. It ensures your code is tested, maintainable, and ready for production at every stage.
Consolidated from:
- testing-strategist - Test pyramid and comprehensive testing
- code-quality-enforcer - Code standards and best practices
- validation-gate-checker - Phase transition validation
When to Use This Skill
Use Quality Assurance when:
- Setting up testing infrastructure for a project
- Conducting code reviews
- Validating readiness to move between project phases
- Establishing quality standards for a team
- Debugging quality issues in production
- Improving code maintainability
- Ensuring production readiness
Key Capabilities
Testing Strategy (from testing-strategist)
- Design test pyramid with optimal coverage
- Define unit, integration, and E2E test strategies
- Set coverage targets and quality metrics
- Choose testing frameworks and tools
- Plan test automation and CI/CD integration
Code Quality (from code-quality-enforcer)
- Enforce coding standards and best practices
- Review code for readability and maintainability
- Identify security vulnerabilities and anti-patterns
- Ensure type safety and error handling
- Refactor code to improve quality scores
Validation Gates (from validation-gate-checker)
- Define phase transition criteria
- Validate readiness for next phase
- Ensure deliverables are complete
- Check compliance with standards
- Prevent premature phase transitions
Workflow
Part 1: Testing Strategy
The Test Pyramid
Structure:
Rationale:
- Unit tests are fast, isolated, cheap to maintain
- Integration tests catch component interaction issues
- E2E tests validate critical user workflows, but are slow and brittle
Unit Tests (70% of tests)
Coverage Targets:
- Critical code (auth, payments, security): 100%
- Business logic: >90%
- Overall codebase: >85%
What to Test:
- Pure functions and business logic
- Edge cases and error conditions
- Input validation
- State management
- Utility functions
Best Practices:
- One test file per source file
- Fast execution (<1ms per test)
- No external dependencies (mock/stub)
- Descriptive test names
- AAA pattern (Arrange, Act, Assert)
Example:
Integration Tests (20% of tests)
What to Test:
- API endpoints with real database
- Multiple components working together
- Third-party service integrations (with mocks)
- Database queries and transactions
- File system operations
Best Practices:
- Test database setup/teardown
- Use test database or transactions
- Mock external services
- Test happy path + key error scenarios
- <5 seconds per test
Example:
E2E Tests (10% of tests)
What to Test:
- Critical user workflows (signup, checkout, etc.)
- Multi-page user journeys
- UI interactions with backend
- Cross-browser compatibility (if needed)
Best Practices:
- Only test critical paths
- Use page object pattern
- Run in CI/CD before deployment
- Accept slower execution (30s-2min per test)
- Use headless browsers in CI
Example:
Testing Tools Recommendations
JavaScript/TypeScript:
- Unit: Jest or Vitest
- Integration: Supertest (API) + Jest
- E2E: Playwright or Cypress
Python:
- Unit: pytest
- Integration: pytest with fixtures
- E2E: Selenium or Playwright
General:
- Coverage: Istanbul (JS), Coverage.py (Python)
- CI/CD: GitHub Actions, CircleCI, GitLab CI
- Mocking: Jest (JS), unittest.mock (Python)
Part 2: Code Quality Enforcement
Code Quality Principles
1. Readability
- Descriptive variable and function names
- Single Responsibility Principle
- Clear, consistent formatting
- Comments for "why", not "what"
2. Maintainability
- DRY (Don't Repeat Yourself)
- SOLID principles
- Type safety (TypeScript, type hints)
- Error handling everywhere
3. Testing
- Unit tests for all functions
- Edge cases covered
- Test names describe behavior
4. Security
- No hardcoded secrets
- Input validation
- SQL injection prevention
- XSS protection
Code Quality Checklist
Before Code Review:
- [ ] No hardcoded secrets or API keys
- [ ] Functions <50 lines (split if longer)
- [ ] Error handling present (try/catch, null checks)
- [ ] All tests passing
- [ ] Type safety (TypeScript strict mode, Python type hints)
- [ ] No console.log or debugging code
- [ ] Descriptive variable names (no x, tmp, data)
- [ ] Comments explain "why", not "what"
- [ ] DRY - no copy-paste code
- [ ] Security best practices (input validation, sanitization)
Code Review Guidelines
What to Look For:
Critical Issues (Must Fix):
- Security vulnerabilities (SQL injection, XSS, secrets)
- Breaking changes without migration
- Missing error handling
- Incorrect logic or algorithm
- Performance bottlenecks
Important Issues (Should Fix):
- Code duplication (DRY violations)
- Poor naming or structure
- Missing tests for new code
- Type safety violations
- Inconsistent formatting
Minor Issues (Nice to Fix):
- Style inconsistencies
- Over-commenting
- Optimization opportunities
- Documentation improvements
Code Quality Score
Scoring System (0-100):
Security (30 points):
- No secrets in code (10 pts)
- Input validation (10 pts)
- Error handling (10 pts)
Readability (25 points):
- Descriptive names (10 pts)
- Clear structure (10 pts)
- Appropriate comments (5 pts)
Testing (25 points):
- Unit test coverage >85% (15 pts)
- Tests for edge cases (10 pts)
Maintainability (20 points):
- DRY compliance (10 pts)
- Function size <50 lines (5 pts)
- Type safety (5 pts)
Grading:
- 90-100: Excellent
- 80-89: Good
- 70-79: Acceptable
- <70: Needs improvement
Part 3: Validation Gates
Validation gates ensure each phase is complete before moving to the next.
Phase 1 → Phase 2 (Discovery → Design)
Gate Criteria:
- [ ] PRP document complete and reviewed
- [ ] Problem statement validated with users
- [ ] Success criteria defined and measurable
- [ ] User stories documented (Jobs-to-be-Done)
- [ ] Stakeholder alignment on scope
- [ ] Open questions documented with owners
Deliverables:
- Product Requirements Prompt (PRP)
- User research summary
- Success metrics dashboard
Review Questions:
- Do we understand the user problem?
- Can we measure success?
- Is scope clear and agreed upon?
Phase 2 → Phase 3 (Design → Development)
Gate Criteria:
- [ ] Architecture documented (system diagram)
- [ ] Data model designed (ERD or schema)
- [ ] API contracts defined (if applicable)
- [ ] Security threats identified (threat model)
- [ ] Mitigations planned for critical threats
- [ ] Technology stack approved
- [ ] Infrastructure plan documented
Deliverables:
- Architecture document
- Data model / ERD
- API specification (OpenAPI/Swagger)
- Threat model with mitigations
- Infrastructure diagram
Review Questions:
- Is architecture sound and scalable?
- Are security threats mitigated?
- Do we have required infrastructure access?
Phase 3 → Phase 4 (Development → Testing)
Gate Criteria:
- [ ] All P0 features complete
- [ ] Unit test coverage >80%
- [ ] Code review completed
- [ ] Static analysis (SAST) passed
- [ ] No critical or high severity issues
- [ ] Error handling implemented
- [ ] Logging and monitoring in place
Deliverables:
- Working software (all P0 features)
- Test coverage report
- Code review sign-off
- SAST scan results
Review Questions:
- Are all MVP features complete?
- Is code quality acceptable?
- Are critical bugs resolved?
Phase 4 → Phase 5 (Testing → Deployment)
Gate Criteria:
- [ ] All tests passing (unit, integration, E2E)
- [ ] Test coverage >90%
- [ ] User acceptance testing (UAT) completed
- [ ] Security testing passed (DAST, penetration test)
- [ ] Performance testing passed (load, stress)
- [ ] Documentation complete (user + dev docs)
- [ ] Rollback plan documented
- [ ] Deployment runbook ready
Deliverables:
- Test results (all green)
- UAT sign-off
- Security test report
- Performance test results
- Deployment runbook
Review Questions:
- Are we confident in quality?
- Can we roll back if needed?
- Is production infrastructure ready?
Examples
Example 1: API Testing Strategy
Project: REST API for user management
Test Plan:
Unit Tests (70%):
- Business logic (validation, permissions)
- Data transformations
- Utility functions
- Error handling logic
Integration Tests (20%):
- POST /users (creates user in DB)
- GET /users/:id (retrieves from DB)
- PUT /users/:id (updates in DB)
- DELETE /users/:id (removes from DB)
- Authentication middleware
- Error responses (400, 401, 404, 500)
E2E Tests (10%):
- Full signup flow (create user → verify email → login)
- Password reset flow
- Profile update flow
Tools:
- Jest (unit)
- Supertest (integration)
- Playwright (E2E)
Coverage Target: 90% overall
Example 2: Code Quality Review
Before (Poor Quality - Score: 55/100):
Issues:
- Security: Hardcoded API key (-10 pts)
- Error handling: None (-10 pts)
- Naming: Poor variable names (-10 pts)
- Testing: No tests (-15 pts)
After (Good Quality - Score: 95/100):
This is the start of the file. Read the full SKILL.md on GitHub.
Security
- Security scanPassed, 82 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/quality-assurance/SKILL.md
Popularity
- Repository stars
- 25
- Repository forks
- 7
- 7-day trend score
- 16
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 25 Apr 2026, 6 months ago.
Extension points
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