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AI-powered enterprise web application testing orchestrator with Context7 integration, intelligent test generation, visual regression testing, cross-browser coordination, and automated QA workflows for modern web applications
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/rdmptv/AdbAutoPlayer --skill moai-workflow-testingコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
Base navigation patterns for Android device automation - gestures, waits, and UI interaction
Screen understanding with OCR and template matching for Android device automation
Meta-tool for rapid adb-* skill creation from templates
SOC 職業分類に基づく
SKILL.md を表示中
| name | moai-workflow-testing |
| description | AI-powered enterprise web application testing orchestrator with Context7 integration, intelligent test generation, visual regression testing, cross-browser coordination, and automated QA workflows for modern web applications |
| version | 2.0.0 |
| modularized | false |
| scripts_enabled | true |
| last_updated | "2025-11-30T00:00:00.000Z" |
| compliance_score | 66 |
| auto_trigger_keywords | ["testing","workflow"] |
| scripts | [{"name":"with_server.py","purpose":"Start one or more servers, wait for them to be ready, run a command, then clean up.","type":"python","command":"uv run .claude/skills/moai-workflow-testing/scripts/with_server.py","zero_context":false,"version":"1.0.0","last_updated":"2025-11-30T00:00:00.000Z"}] |
| color | red |
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.
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)
TestAnalysis(
application_type=app_type,
confidence_score=.calculate_confidence(app_type, test_patterns),
recommended_test_strategies=.generate_test_strategies(app_type, test_patterns, context7_insights),
context7_references=context7_insights[],
automation_opportunities=.identify_automation_opportunities(app_type, test_patterns)
)
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
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
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()
Inspect rendered DOM:
page.screenshot(path='/tmp/inspect.png', full_page=True)
content = page.content()
page.locator('button').all()
Identify selectors from inspection results
Execute actions using discovered selectors
with_server.py directly, don't read sourcesync_playwright() for synchronous scriptstext=, role=, CSS selectors, or IDsnetworkidle on dynamic apps before inspectionpage.wait_for_selector() or page.wait_for_timeout()/microsoft/playwrightBasic Level Triggers (without AI):
AI Automatic Triggers:
Manual AI Invocation:
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)
)
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
)
# 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
moai-essentials-debug: 테스트 실패 시 AI 디버깅 연동moai-essentials-perf: 성능 테스트 통합moai-essentials-review: 코드 리뷰와 테스트 커버리지 연동moai-foundation-trust: 품질 보증 및 TRUST 5 원칙 적용.moai/config/config.json conversation_language 자동 적용**End of AI-Powered Enterprise Web Application Testing Skill **
Enhanced with Context7 MCP integration and revolutionary AI capabilities
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)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