docs: fix markdown formatting and improve git hook security

- Fix markdown list spacing (MD030) in performance, audit logs, and CSP docs
- Remove ineffective while loop in commit-msg hook that caused subshell issues
- Improve fetchWithRetry function with proper retry limits and exponential backoff
- Update CSP metrics retention documentation for consistency

docs/database-performance-optimizations.md

@@ -6,10 +6,10 @@ This document outlines the comprehensive database performance optimizations impl
 
 The optimization focuses on the most frequently queried patterns in the application, particularly around:
 
--   AI processing request tracking and batching
--   Session analytics and filtering
--   Security audit log analysis
--   Multi-tenant data isolation performance
+  - AI processing request tracking and batching
+  - Session analytics and filtering
+  - Security audit log analysis
+  - Multi-tenant data isolation performance
 
 ## Applied Optimizations
 
@@ -31,9 +31,9 @@ INCLUDE ("processingStatus", "batchId", "requestedAt", "sessionId");
 
 **Impact**:
 
--   ~70% faster batch job queries
--   Reduced I/O for cost analysis reports
--   Improved scheduler performance
+  - ~70% faster batch job queries
+  - Reduced I/O for cost analysis reports
+  - Improved scheduler performance
 
 ### 2. Session Analytics Optimizations
 
@@ -54,9 +54,9 @@ INCLUDE ("startTime", "messagesSent");
 
 **Impact**:
 
--   ~85% faster dashboard load times
--   Efficient date range filtering
--   Optimized sentiment analysis queries
+  - ~85% faster dashboard load times
+  - Efficient date range filtering
+  - Optimized sentiment analysis queries
 
 ### 3. Security Audit Log Optimizations
 
@@ -77,9 +77,9 @@ INCLUDE ("eventType", "severity", "userId", "companyId");
 
 **Impact**:
 
--   ~90% faster security monitoring
--   Efficient threat detection
--   Improved compliance reporting
+  - ~90% faster security monitoring
+  - Efficient threat detection
+  - Improved compliance reporting
 
 ### 4. Message Processing Optimizations
 
@@ -95,8 +95,8 @@ INCLUDE ("content");
 
 **Impact**:
 
--   ~60% faster conversation loading
--   Reduced memory usage for message queries
+  - ~60% faster conversation loading
+  - Reduced memory usage for message queries
 
 ### 5. Processing Pipeline Optimizations
 
@@ -118,29 +118,29 @@ INCLUDE ("sessionId", "errorMessage", "retryCount", "startedAt");
 
 **Impact**:
 
--   ~75% faster processing monitoring
--   Efficient error tracking
--   Improved retry logic performance
+  - ~75% faster processing monitoring
+  - Efficient error tracking
+  - Improved retry logic performance
 
 ## Index Strategy Principles
 
 ### 1. Composite Index Design
 
--   **Leading column**: Most selective filter (usually companyId for multi-tenancy)
--   **Secondary columns**: Common WHERE clause filters
--   **Covering columns**: SELECT list columns via INCLUDE
+  - **Leading column**: Most selective filter (usually companyId for multi-tenancy)
+  - **Secondary columns**: Common WHERE clause filters
+  - **Covering columns**: SELECT list columns via INCLUDE
 
 ### 2. Partial Indexes
 
--   Used for error analysis and specific status filtering
--   Reduces index size and maintenance overhead
--   Improves write performance
+  - Used for error analysis and specific status filtering
+  - Reduces index size and maintenance overhead
+  - Improves write performance
 
 ### 3. Covering Indexes
 
--   Include frequently accessed columns to avoid table lookups
--   Reduces I/O for read-heavy operations
--   Particularly effective for dashboard queries
+  - Include frequently accessed columns to avoid table lookups
+  - Reduces I/O for read-heavy operations
+  - Particularly effective for dashboard queries
 
 ## Query Pattern Analysis
 
@@ -166,29 +166,29 @@ INCLUDE ("sessionId", "errorMessage", "retryCount", "startedAt");
 
 ### Index Monitoring
 
--   Monitor index usage with `pg_stat_user_indexes`
--   Track bloat with `pg_stat_user_tables`
--   Regular ANALYZE after bulk operations
+  - Monitor index usage with `pg_stat_user_indexes`
+  - Track bloat with `pg_stat_user_tables`
+  - Regular ANALYZE after bulk operations
 
 ### Write Performance Impact
 
--   Composite indexes add ~15% write overhead
--   Offset by dramatic read performance gains
--   Monitored via slow query logs
+  - Composite indexes add ~15% write overhead
+  - Offset by dramatic read performance gains
+  - Monitored via slow query logs
 
 ### Storage Impact
 
--   Indexes add ~25% to total storage
--   Covering indexes reduce need for table scans
--   Partial indexes minimize storage overhead
+  - Indexes add ~25% to total storage
+  - Covering indexes reduce need for table scans
+  - Partial indexes minimize storage overhead
 
 ## Migration Safety
 
 ### CONCURRENTLY Operations
 
--   All indexes created with `CREATE INDEX CONCURRENTLY`
--   No table locks during creation
--   Production-safe deployment
+  - All indexes created with `CREATE INDEX CONCURRENTLY`
+  - No table locks during creation
+  - Production-safe deployment
 
 ### Rollback Strategy
 
@@ -238,18 +238,18 @@ LIMIT 10;
 
 ### Monitoring Strategy
 
--   Set up automated index usage monitoring
--   Track slow query evolution
--   Monitor storage growth patterns
--   Implement performance alerting
+  - Set up automated index usage monitoring
+  - Track slow query evolution
+  - Monitor storage growth patterns
+  - Implement performance alerting
 
 ## Conclusion
 
 These database optimizations provide:
 
--   **70-90% improvement** in query performance
--   **Reduced server load** through efficient indexing
--   **Better user experience** with faster dashboards
--   **Scalable foundation** for future growth
+  - **70-90% improvement** in query performance
+  - **Reduced server load** through efficient indexing
+  - **Better user experience** with faster dashboards
+  - **Scalable foundation** for future growth
 
 The optimizations are designed to be production-safe and monitoring-friendly, ensuring both immediate performance gains and long-term maintainability.