style: formatted the docs with prettier

docs/csp-metrics-api.md

@@ -59,7 +59,7 @@ GET /api/csp-metrics
 #### Query Parameters
 
 | Parameter        | Type    | Description                                                                     | Default | Example                |
-| ---------------- | ------- | ------------------------- | ------- | ---------------------- |
+| ---------------- | ------- | ------------------------------------------------------------------------------- | ------- | ---------------------- |
 | `timeRange`      | string  | Time range for metrics                                                          | `24h`   | `?timeRange=7d`        |
 | `format`         | string  | Response format                                                                 | `json`  | `?format=csv`          |
 | `groupBy`        | string  | Group results by field                                                          | `hour`  | `?groupBy=directive`   |

docs/database-connection-pooling.md

@@ -45,14 +45,17 @@ DATABASE_URL="postgresql://user:pass@host:5432/db?connection_limit=20&pool_timeo
 ### Fixed Issues
 
 1.  **Multiple PrismaClient Instances**:
+
 - ❌ Before: Each scheduler created its own PrismaClient
 - ✅ After: All modules use singleton pattern from `lib/prisma.ts`
 
 2.  **No Connection Management**:
+
 - ❌ Before: No graceful shutdown or connection cleanup
 - ✅ After: Proper cleanup on process termination
 
 3.  **No Monitoring**:
+
 - ❌ Before: No visibility into connection usage
 - ✅ After: Health check endpoint and connection metrics
 

docs/scheduler-architecture.md

@@ -380,22 +380,26 @@ csv-import-scheduler-eu:
 ### From Current Architecture
 
 1.  **Phase 1: Extract Schedulers**
+
 - ✅ Create BaseSchedulerService
 - ✅ Implement CsvImportSchedulerService
 - ✅ Create SchedulerManager
 - ⏳ Implement remaining scheduler services
 
 2.  **Phase 2: Deployment Options**
+
 - ✅ Add ServerSchedulerIntegration for backwards compatibility
 - ✅ Create StandaloneSchedulerRunner
 - ✅ Add health check endpoints
 
 3.  **Phase 3: Container Support**
+
 - ⏳ Create Dockerfile for scheduler containers
 - ⏳ Add Kubernetes manifests
 - ⏳ Implement distributed coordination
 
 4.  **Phase 4: Production Migration**
+
 - ⏳ Deploy separate scheduler containers
 - ⏳ Monitor performance and stability
 - ⏳ Gradually increase horizontal scaling

docs/security-monitoring.md

@@ -9,6 +9,7 @@ The Security Monitoring and Alerting System provides comprehensive real-time sec
 ### Core Components
 
 1.  **Security Monitoring Service** (`lib/securityMonitoring.ts`)
+
 - Real-time event processing
 - Anomaly detection algorithms
 - Alert generation and management
@@ -16,17 +17,20 @@ The Security Monitoring and Alerting System provides comprehensive real-time sec
 - Threat level assessment
 
 2.  **Enhanced Security Logging** (`enhancedSecurityLog`)
+
 - Integrates with existing audit logger
 - Processes events through monitoring system
 - Triggers immediate threat detection
 
 3.  **API Endpoints** (`app/api/admin/security-monitoring/`)
+
 - `/api/admin/security-monitoring` - Main metrics and configuration
 - `/api/admin/security-monitoring/alerts` - Alert management
 - `/api/admin/security-monitoring/export` - Data export
 - `/api/admin/security-monitoring/threat-analysis` - Threat analysis
 
 4.  **Dashboard UI** (`app/platform/security/page.tsx`)
+
 - Real-time security metrics
 - Active alerts management
 - Threat analysis visualization
@@ -69,16 +73,19 @@ enum AlertType {
 The system implements several anomaly detection algorithms:
 
 1.  **Geographic Anomaly Detection**
+
 - Detects logins from unusual countries
 - Compares against historical user patterns
 - Confidence scoring based on deviation
 
 2.  **Temporal Anomaly Detection**
+
 - Identifies activity spikes during unusual hours
 - Compares current activity to historical averages
 - Configurable thresholds for different event types
 
 3.  **Behavioral Anomaly Detection**
+
 - Multiple failed login attempts
 - Rapid succession of actions
 - Pattern deviation analysis
@@ -348,21 +355,25 @@ await enhancedSecurityLog(
 ### Planned Features
 
 1.  **Machine Learning Integration**
+
 - Behavioral pattern recognition
 - Adaptive threshold adjustment
 - Predictive threat modeling
 
 2.  **Advanced Analytics**
+
 - Threat intelligence integration
 - Cross-correlation analysis
 - Risk trend analysis
 
 3.  **Integration Enhancements**
+
 - SIEM system connectors
 - Webhook customization
 - Mobile app notifications
 
 4.  **Automated Response**
+
 - IP blocking automation
 - Account suspension workflows
 - Incident response orchestration