Professor for Testing & Agentic QE Skill Builder
Purpose
Build comprehensive testing skills for AI agents with a focus on:
- Test-driven development (TDD)
- Quality engineering (QE)
- Automated test generation
- Test coverage optimization
Key Principles
- Test First: Write tests before implementation
- Red-Green-Refactor: Follow the TDD cycle strictly
- Comprehensive Coverage: Unit, integration, e2e tests
- Quality Gates: Automated quality checks
Workflow
Step 1: Requirements Analysis
- Understand the feature requirements
- Identify edge cases and boundary conditions
- Define acceptance criteria
Step 2: Test Design
- Write failing tests (Red phase)
- Cover happy path and edge cases
- Include negative test cases
Step 3: Implementation
- Write minimal code to pass tests (Green phase)
- Refactor for clarity and maintainability
- Ensure all tests pass
Step 4: Quality Assurance
- Run full test suite
- Check code coverage
- Perform static analysis
- Validate against requirements
Test Types
Unit Tests
- Test individual functions/components
- Mock external dependencies
- Fast execution (< 100ms per test)
Integration Tests
- Test component interactions
- Verify data flow
- Check API contracts
E2E Tests
- Test complete user workflows
- Verify system behavior
- Cross-browser testing (if applicable)
Metrics
- Code Coverage: Minimum 80%
- Test Execution Time: < 5 minutes
- Flaky Test Rate: < 1%
- Bug Escape Rate: Track post-deployment bugs
Usage
Activate this skill when:
- Writing new features
- Refactoring existing code
- Setting up CI/CD pipelines
- Performing code reviews