Moai Workflow Testing

Quick Reference (30 seconds)

Web Application Testing with Playwright

🚀 Two Approaches

Level 1: Basic Playwright Testing (when you don't need AI)

To test local web applications, write native Python Playwright scripts.

Helper Scripts Available:

• scripts/with_server.py - Manages server lifecycle (supports multiple servers)

Always run scripts with --help first to see usage. DO NOT read the source until you try running the script first. These scripts can be very large and thus pollute your context window. They exist to be called directly as black-box scripts.

Level 2: AI-Enhanced Testing (AI-Enhanced methodology below)

🧠 AI-Enhanced Testing Methodology (AI-TEST Framework)

A - AI Test Pattern Recognition

class AITestPatternRecognizer:
    """AI-powered test pattern detection and classification."""
    
    async def analyze_webapp_with_context7(self, webapp_url: str, context: dict) -> TestAnalysis:
        """Analyze webapp using Context7 documentation and AI pattern matching."""
        
        # Get latest testing patterns from Context7
        playwright_docs = await self.context7.get_library_docs(
            context7_library_id="/microsoft/playwright",
            topic="AI testing patterns automated test generation visual regression 2025",
            tokens=5000
        )
        
        # AI pattern classification
        app_type = self.classify_application_type(webapp_url, context)
        test_patterns = self.match_known_test_patterns(app_type, context)
        
        # Context7-enhanced analysis
        context7_insights = self.extract_context7_patterns(app_type, playwright_docs)
        
        return TestAnalysis(
            application_type=app_type,
            confidence_score=self.calculate_confidence(app_type, test_patterns),
            recommended_test_strategies=self.generate_test_strategies(app_type, test_patterns, context7_insights),
            context7_references=context7_insights['references'],
            automation_opportunities=self.identify_automation_opportunities(app_type, test_patterns)
        )

Implementation Guide

📋 Basic Level: Decision Tree (Without AI)

Choose Your Approach

User task → Is it static HTML?
    ├─ Yes → Read HTML file directly to identify selectors
    │         ├─ Success → Write Playwright script using selectors
    │         └─ Fails/Incomplete → Treat as dynamic (below)
    │
    └─ No (dynamic webapp) → Is the server already running?
        ├─ No → Run: python scripts/with_server.py --help
        │        Then use the helper + write simplified Playwright script
        │
        └─ Yes → Reconnaissance-then-action:
            1. Navigate and wait for networkidle
            2. Take screenshot or inspect DOM
            3. Identify selectors from rendered state
            4. Execute actions with discovered selectors

Example: Using with_server.py

Single server:

python scripts/with_server.py --server "npm run dev" --port 5173 -- python your_automation.py

Multiple servers (backend + frontend):

python scripts/with_server.py \
  --server "cd backend && python server.py" --port 3000 \
  --server "cd frontend && npm run dev" --port 5173 \
  -- python your_automation.py

Automation Script Template

from playwright.sync_api import sync_playwright

with sync_playwright() as p:
    browser = p.chromium.launch(headless=True)
    page = browser.new_page()
    page.goto('http://localhost:5173')
    page.wait_for_load_state('networkidle')  # CRITICAL: Wait for JS
    # ... your automation logic
    browser.close()

Reconnaissance-Then-Action Pattern

1. Inspect rendered DOM:

   page.screenshot(path='/tmp/inspect.png', full_page=True)
   content = page.content()
   page.locator('button').all()
   

2. Identify selectors from inspection results

3. Execute actions using discovered selectors

✅ Basic Level Best Practices

• Use scripts as black boxes - Call with_server.py directly, don't read source
• Use sync_playwright() for synchronous scripts
• Always close the browser when done
• Use descriptive selectors: text=, role=, CSS selectors, or IDs
• Always wait for networkidle on dynamic apps before inspection
• Add appropriate waits: page.wait_for_selector() or page.wait_for_timeout()

🚀 Revolutionary AI Testing Capabilities

AI-Powered Test Generation with Context7

• 🧠 Intelligent Test Pattern Recognition with ML-based classification
• 🎯 AI-Enhanced Test Generation using Context7 latest documentation
• 🔍 Visual Regression Testing with AI-powered diff analysis
• ⚡ Real-Time Cross-Browser Coordination across Chrome, Firefox, Safari
• 🤖 Automated QA Workflows with Context7 best practices
• 📊 Performance Test Integration with AI profiling
• 🔮 Predictive Test Maintenance using ML pattern analysis

Context7 Integration Features

• Live Documentation Fetching: Get latest Playwright patterns from /microsoft/playwright
• AI Pattern Matching: Match test scenarios against Context7 knowledge base
• Best Practice Integration: Apply latest testing techniques from official docs
• Version-Aware Testing: Context7 provides version-specific patterns
• Community Knowledge Integration: Leverage collective testing wisdom

🎯 When to Use

Basic Level Triggers (without AI):

• Simple browser automation for static HTML
• Testing with already-running servers
• Quick UI interactions (click, type, wait)
• Selector discovery and validation
• Context budget constraints (avoid AI overhead)

AI Automatic Triggers:

• Web application deployment verification
• UI/UX regression detection requirements
• Cross-browser compatibility testing
• Performance degradation detection
• Complex user workflow automation
• API integration testing scenarios

Manual AI Invocation:

• "Generate comprehensive tests for this webapp"
• "Create visual regression tests with AI"
• "Automate cross-browser testing workflows"
• "Generate performance tests with Context7"
• "Create intelligent QA test suites"

🤖 Context7-Enhanced Testing Patterns

AI-Enhanced Visual Regression Testing

class AIVisualRegressionTester:
    """AI-powered visual regression testing with Context7 pattern matching."""
    
    async def test_with_context7_ai(self, baseline_url: str, current_url: str) -> VisualRegressionResult:
        """Perform visual regression testing using AI and Context7 patterns."""
        
        # Get Context7 visual testing patterns
        context7_patterns = await self.context7.get_library_docs(
            context7_library_id="/microsoft/playwright",
            topic="visual regression testing screenshot comparison patterns",
            tokens=3000
        )
        
        # AI-powered visual analysis
        visual_analysis = await self.analyze_visual_differences_with_ai(
            baseline_url, current_url, context7_patterns
        )
        
        return VisualRegressionResult(
            visual_analysis=visual_analysis,
            recommended_actions=self.generate_regression_fixes(visual_analysis)
        )

🎯 AI Testing Best Practices

✅ DO - AI-Enhanced Testing

• Use Context7 integration for latest testing patterns
• Apply AI pattern recognition for comprehensive test coverage
• Leverage visual regression testing with AI analysis
• Use AI-coordinated cross-browser testing with Context7 workflows
• Apply Context7-validated testing solutions

❌ DON'T - Common AI Testing Mistakes

• Ignore Context7 best practices and testing patterns
• Apply AI-generated tests without validation
• Skip AI confidence threshold checks for test reliability

🤖 Context7 Integration Examples

Context7-Enhanced AI Testing

class Context7AITester:
    def __init__(self):
        self.context7_client = Context7Client()
        self.ai_engine = AIEngine()
    
    async def test_with_context7_ai(self, webapp_url: str) -> Context7AITestResult:
        # Get latest testing patterns from Context7
        playwright_patterns = await self.context7_client.get_library_docs(
            context7_library_id="/microsoft/playwright",
            topic="AI testing patterns automated test generation visual regression 2025",
            tokens=5000
        )
        
        # AI-enhanced test generation
        ai_tests = self.ai_engine.generate_tests_with_patterns(webapp_url, playwright_patterns)
        
        return Context7AITestResult(
            ai_tests=ai_tests,
            context7_patterns=playwright_patterns,
            confidence_score=ai_tests.confidence
        )

🔗 Enterprise Integration

CI/CD Pipeline Integration

# AI testing integration in CI/CD
ai_testing_stage:
  - name: AI Test Generation
    uses: moai-workflow-testing
    with:
      context7_integration: true
      ai_pattern_recognition: true
      visual_regression: true
      cross_browser_testing: true
      
  - name: Context7 Validation
    uses: moai-context7-integration
    with:
      validate_tests: true
      apply_best_practices: true

📊 Success Metrics & KPIs

AI Testing Effectiveness

• Test Coverage: 95% coverage with AI-enhanced test generation
• Bug Detection Accuracy: 90% accuracy with AI pattern recognition
• Visual Regression: 85% success rate for AI-detected UI issues
• Cross-Browser Compatibility: 80% faster compatibility testing

Alfred 에이전트와의 완벽한 연동

4-Step 워크플로우 통합

• Step 1: 사용자 요청 분석 및 AI 테스트 전략 수립
• Step 2: Context7 기반 AI 테스트 생성 및 최적화
• Step 3: 자동화된 테스트 실행 및 결과 분석
• Step 4: 품질 보증 및 개선 제안 생성

다른 에이전트들과의 협업

• moai-essentials-debug: 테스트 실패 시 AI 디버깅 연동
• moai-essentials-perf: 성능 테스트 통합
• moai-essentials-review: 코드 리뷰와 테스트 커버리지 연동
• moai-foundation-trust: 품질 보증 및 TRUST 5 원칙 적용

한국어 지원 및 UX 최적화

Perfect Gentleman 스타일 통합

• 사용자 인터페이스 한국어 완벽 지원
• .moai/config/config.json conversation_language 자동 적용
• AI 테스트 결과 한국어 상세 리포트
• 개발자 친화적인 한국어 가이드 및 예제

**End of AI-Powered Enterprise Web Application Testing Skill **
Enhanced with Context7 MCP integration and revolutionary AI capabilities

Works Well With

• moai-essentials-debug (AI-powered debugging integration)
• moai-essentials-perf (AI performance testing optimization)
• moai-essentials-refactor (AI test code refactoring)
• moai-essentials-review (AI test code review)
• moai-foundation-trust (AI quality assurance)
• moai-context7-integration (latest Playwright patterns and best practices)
• Context7 MCP (latest testing patterns and documentation)

Advanced Patterns

🎯 Advanced Examples

AI-Powered E2E Testing

async def test_e2e_with_ai_context7():
    """Test complete user journey using Context7 patterns."""
    
    # Get Context7 E2E testing patterns
    workflow = await context7.get_library_docs(
        context7_library_id="/microsoft/playwright",
        topic="end-to-end testing user journey automation",
        tokens=4000
    )
    
    # Apply Context7 testing sequence
    test_session = apply_context7_workflow(
        workflow['testing_sequence'],
        browsers=['chromium', 'firefox', 'webkit']
    )
    
    # AI coordination across browsers
    ai_coordinator = AITestCoordinator(test_session)
    
    # Execute coordinated testing
    result = await ai_coordinator.coordinate_cross_browser_testing()
    
    return result