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

1. Test First: Write tests before implementation
2. Red-Green-Refactor: Follow the TDD cycle strictly
3. Comprehensive Coverage: Unit, integration, e2e tests
4. 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