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--- a/skills/query-expert/scripts/analyze_performance.sh
+++ b/skills/query-expert/scripts/analyze_performance.sh
@@ -0,0 +1,297 @@
+#!/bin/bash
+
+# Query Expert - Performance Analyzer
+# Analyze EXPLAIN output and provide optimization recommendations
+
+set -e
+
+RED='\033[0;31m'
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+BLUE='\033[0;34m'
+NC='\033[0m'
+
+print_info() {
+    echo -e "${BLUE}ℹ $1${NC}"
+}
+
+print_warning() {
+    echo -e "${YELLOW}⚠ $1${NC}"
+}
+
+print_success() {
+    echo -e "${GREEN}✓ $1${NC}"
+}
+
+echo ""
+echo "╔════════════════════════════════════════════════════════════╗"
+echo "║                                                            ║"
+echo "║          Query Expert - Performance Analyzer              ║"
+echo "║                                                            ║"
+echo "╚════════════════════════════════════════════════════════════╝"
+echo ""
+
+print_info "Performance Analysis Guide"
+echo ""
+
+cat << 'EOF'
+## PostgreSQL EXPLAIN Analysis
+
+### Run EXPLAIN
+```sql
+EXPLAIN ANALYZE
+SELECT * FROM orders WHERE customer_id = 123;
+```
+
+### What to Look For:
+
+**Seq Scan (Table Scan) ❌**
+→ Reading entire table
+→ Fix: Add index on filtered column
+→ CREATE INDEX idx_orders_customer ON orders(customer_id);
+
+**Index Scan ✅**
+→ Using index efficiently
+→ Good performance for specific rows
+
+**Bitmap Heap Scan ✅**
+→ Good for returning multiple rows
+→ Efficient index usage
+
+**Nested Loop ⚠️**
+→ Can be slow with large datasets
+→ Consider: Hash Join or Merge Join
+
+**Hash Join ✅**
+→ Good for large joins
+→ Requires memory
+
+**Cost Numbers**
+→ Higher = slower
+→ Compare before/after optimization
+→ cost=0.00..35.50 rows=10
+
+**Actual Time**
+→ Real execution time
+→ actual time=0.023..0.156 rows=10 loops=1
+
+---
+
+## MySQL EXPLAIN Analysis
+
+### Run EXPLAIN
+```sql
+EXPLAIN SELECT * FROM orders WHERE customer_id = 123;
+```
+
+### Type Column:
+
+**ALL ❌**
+→ Full table scan
+→ Fix: Add index
+
+**index ⚠️**
+→ Full index scan
+→ Better than ALL, but could improve
+
+**range ✅**
+→ Index range scan
+→ Good for WHERE with >, <, BETWEEN
+
+**ref ✅✅**
+→ Index lookup
+→ Excellent performance
+
+**eq_ref ✅✅✅**
+→ Unique index lookup
+→ Best performance
+
+**const ✅✅✅**
+→ Constant lookup (primary key)
+→ Fastest possible
+
+### Extra Column:
+
+**Using filesort ⚠️**
+→ Sorting in memory/disk
+→ Fix: Add index on ORDER BY columns
+
+**Using temporary ⚠️**
+→ Creating temporary table
+→ Fix: Optimize GROUP BY or DISTINCT
+
+**Using index ✅**
+→ Covering index (index-only scan)
+→ Excellent performance
+
+**Using where ✅**
+→ Filtering after read
+→ Normal for WHERE clauses
+
+---
+
+## MongoDB Explain Analysis
+
+### Run Explain
+```javascript
+db.orders.find({ customer_id: 123 }).explain("executionStats")
+```
+
+### What to Look For:
+
+**COLLSCAN ❌**
+→ Full collection scan
+→ Fix: Create index
+→ db.orders.createIndex({ customer_id: 1 })
+
+**IXSCAN ✅**
+→ Index scan
+→ Good performance
+
+**executionTimeMillis**
+→ Total execution time
+→ < 100ms good, > 1000ms needs optimization
+
+**nReturned vs totalDocsExamined**
+→ Efficiency ratio
+→ Ideally close to 1:1
+→ If totalDocsExamined >> nReturned, add index
+
+**Index Usage**
+→ indexName: "customer_id_1" ✅
+→ indexName: null ❌ (no index used)
+
+---
+
+## Index Recommendations
+
+### When to Create Index:
+
+1. **WHERE Clause**
+   CREATE INDEX idx_table_column ON table(column);
+
+2. **JOIN Columns**
+   CREATE INDEX idx_table_join_col ON table(join_column);
+
+3. **ORDER BY**
+   CREATE INDEX idx_table_sort ON table(sort_column);
+
+4. **Composite Index (order matters!)**
+   CREATE INDEX idx_multi ON table(col1, col2, col3);
+   → Works for: col1 | col1,col2 | col1,col2,col3
+   → NOT for: col2 | col3 | col2,col3
+
+5. **Covering Index**
+   CREATE INDEX idx_covering ON table(filter_col) INCLUDE (select_cols);
+   → Index contains all needed columns
+   → Fastest possible (index-only scan)
+
+### When NOT to Index:
+
+- Small tables (< 1000 rows)
+- Columns with low cardinality (few distinct values)
+- Frequently updated columns
+- Large text/blob columns
+
+---
+
+## Query Optimization Checklist
+
+Performance Issues:
+[ ] Check EXPLAIN plan
+[ ] Look for table scans (Seq Scan, ALL, COLLSCAN)
+[ ] Identify missing indexes
+[ ] Check JOIN types (Nested Loop on large tables)
+[ ] Look for filesort or temporary tables
+[ ] Verify index usage (Using index)
+
+Optimizations:
+[ ] Create indexes on WHERE columns
+[ ] Create indexes on JOIN columns  
+[ ] Use composite indexes (correct order)
+[ ] Add covering indexes for frequent queries
+[ ] Use LIMIT to reduce result set
+[ ] Avoid SELECT * (select only needed columns)
+[ ] Avoid functions on indexed columns
+[ ] Use EXISTS instead of IN (subqueries)
+[ ] Filter early (before JOIN)
+[ ] Use appropriate JOIN type
+
+Monitoring:
+[ ] Run EXPLAIN ANALYZE before optimization
+[ ] Create indexes
+[ ] Run EXPLAIN ANALYZE after optimization
+[ ] Compare execution time and cost
+[ ] Test with production-like data volume
+[ ] Monitor slow query log
+
+---
+
+## Example Optimization
+
+### Before (Slow)
+```sql
+-- EXPLAIN shows: Seq Scan, cost=1000.00
+SELECT * FROM orders WHERE customer_id = 123;
+```
+
+### Optimization Steps
+```sql
+-- 1. Create index
+CREATE INDEX idx_orders_customer ON orders(customer_id);
+
+-- 2. Optimize query (avoid SELECT *)
+SELECT order_id, total, created_at
+FROM orders
+WHERE customer_id = 123
+ORDER BY created_at DESC
+LIMIT 100;
+
+-- 3. Check improvement
+EXPLAIN ANALYZE
+SELECT order_id, total, created_at
+FROM orders
+WHERE customer_id = 123
+ORDER BY created_at DESC
+LIMIT 100;
+```
+
+### After (Fast)
+```
+→ Index Scan using idx_orders_customer
+→ cost=0.29..15.50 (95% improvement!)
+→ actual time=0.015..0.023
+```
+
+---
+
+## Tools
+
+**PostgreSQL:**
+- EXPLAIN ANALYZE
+- pg_stat_statements extension
+- pgBadger (log analyzer)
+
+**MySQL:**
+- EXPLAIN
+- SHOW PROFILE
+- MySQL Workbench Performance Dashboard
+
+**MongoDB:**
+- explain("executionStats")
+- MongoDB Compass (GUI)
+- Database Profiler
+
+---
+
+EOF
+
+print_success "Performance analysis guide displayed"
+echo ""
+print_info "Next Steps:"
+echo "  1. Run EXPLAIN on your slow query"
+echo "  2. Identify the bottleneck (table scan, no index, etc.)"
+echo "  3. Apply recommended optimization"
+echo "  4. Re-run EXPLAIN to verify improvement"
+echo "  5. Test with production data volume"
+echo ""