Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Quelldateien prüfen
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Ein direkter Befehl überspringt den Prüf-Prompt. Prüfen Sie die Quelle, bevor Sie ihn ausführen.
// API clientconst requestId = headers['X-Request-ID'] || generateRequestId();
// Include in all logs
logger.info('Processing request', { request_id: requestId });
// Include in header when calling downstream servicesawaitfetch(url, {
headers: { 'X-Request-ID': requestId }
});
# Stream all service logs
docker compose logs -f
# Specific service only
docker compose logs -f api
# Filter errors only
docker compose logs -f | grep '"level":"ERROR"'# Track specific Request ID
docker compose logs -f | grep 'req_abc123'
QA Automation Workflow
1. Start Environment
# Start development environment
docker compose up -d
# Start log monitoring (Claude Code monitors)
docker compose logs -f
2. Manual UX Testing
User tests actual features in browser:
1. Sign up attempt
2. Login attempt
3. Use core features
4. Test edge cases
3. Claude Code Log Analysis
Claude Code in real-time:
1. Monitor log stream
2. Detect error patterns
3. Detect abnormal response times
4. Track entire flow via Request ID
5. Auto-document issues
# Feature Test Results - Cycle N## Summary-**Date**: YYYY-MM-DD
-**Feature**: {feature name}
-**Pass Rate**: N%
-**Tests**: X passed / Y total
## Results
| Test Case | Status | Notes |
|-----------|--------|-------|
| Test 1 | ✅ | |
| Test 2 | ❌ | {error description} |
| Test 3 | ⏭️ | {skip reason} |
## Bugs Found### BUG-001: {Title}-**Root Cause**: {description}
-**Fix**: {what was changed}
-**Files**: `path/to/file.py:123`## Next Cycle Plan- {what to test next}
Checklist
Logging Infrastructure
JSON log format applied
Request ID generation and propagation
Log level settings per environment
Docker logging configuration
Backend Logging
Logging middleware implemented
All API calls logged (including 200 OK)
Business logic logging
Detailed error logging
Frontend Logging
Logger module implemented
API client integration
Error boundary logging
QA Workflow
Docker Compose configured
Real-time monitoring ready
Issue documentation template ready
Auto-Apply Rules
When Building Logging Infrastructure
When implementing API/Backend:
Suggest logging middleware creation
Suggest JSON format logger setup
Add Request ID generation/propagation logic
When implementing Frontend:
Suggest Logger module creation
Suggest logging integration with API client
Suggest including Request ID header
When Performing QA
On test request:
Guide to run docker compose logs -f
Request manual UX testing from user
Real-time log monitoring
Document issues immediately when detected
Provide fix suggestions
Issue Detection Thresholds
Severity
Condition
Action
Critical
level: ERROR or status: 5xx
Immediate report
Critical
duration_ms > 3000
Immediate report
Critical
3+ consecutive failures
Immediate report
Warning
status: 401, 403
Warning report
Warning
duration_ms > 1000
Warning report
Info
Missing log fields
Note for improvement
Info
Request ID not propagated
Note for improvement
Required Logging Locations
Backend (FastAPI/Express)
✅ Request start (method, path, params)
✅ Request complete (status, duration_ms)
✅ Major business logic steps
✅ Detailed info on errors
✅ Before/after external API calls
✅ DB queries (in development)
Frontend (Next.js/React)
✅ API call start
✅ API response received (status, duration)
✅ Detailed info on errors
✅ Important user actions
