gh-djankies-claude-configs-prisma-6/skills/optimizing-query-performance/SKILL.md

name, description, allowed-tools, version

name	description	allowed-tools	version
optimizing-query-performance	Optimize queries with indexes, batching, and efficient Prisma operations for production performance.	Read, Write, Edit, Bash	1.0.0

Query optimization requires strategic indexing, efficient batching, and monitoring to prevent common production anti-patterns.

Key capabilities: Strategic index placement (@@index, @@unique) · Efficient batch operations (createMany, transactions) · Query analysis & N+1 prevention · Field selection optimization & cursor pagination

**Phase 1 — Identify:** Enable query logging; analyze patterns/execution times; identify missing indexes, N+1 problems, or inefficient batching

Phase 2 — Optimize: Add indexes for filtered/sorted fields; replace loops with batch operations; select only needed fields; use cursor pagination for large datasets

Phase 3 — Validate: Measure execution time before/after; verify index usage with EXPLAIN ANALYZE; monitor connection pool under load

Quick Reference

Index Strategy:

Scenario	Index Type	Example
Single field filter	@@index([field])	@@index([status])
Multiple field filter	@@index([field1, field2])	@@index([userId, status])
Sort + filter	@@index([filterField, sortField])	@@index([status, createdAt])

Batch Operations:

Operation	Slow (Loop)	Fast (Batch)
Insert	for...await create()	createMany()
Update	for...await update()	updateMany()
Delete	for...await delete()	deleteMany()

Performance Gains: Indexes (10-100x) · Batch ops (50-100x for 1000+ records) · Cursor pagination (constant vs O(n))

**MUST:** Add indexes for WHERE/ORDER BY/FK fields with frequent queries; use createMany for 100+ records; cursor pagination for deep pagination; select only needed fields; monitor query duration in production

SHOULD: Test indexes with production data; chunk 100k+ batches into smaller sizes; use @@index([field1, field2]) for multi-field filters; remove unused indexes

NEVER: Add indexes without performance measurement; offset pagination beyond page 100 on large tables; fetch all

fields when only needing few; loop with individual creates/updates; ignore slow query warnings

**Measure Performance:** ```typescript const start = Date.now() const result = await prisma.user.findMany({ ... }) console.log(`Query took ${Date.now() - start}ms`) ``` Expected: 50-90% improvement for indexed queries, 50-100x for batch operations

Verify Index Usage: Run EXPLAIN ANALYZE; confirm "Index Scan" vs "Seq Scan"

Monitor Production: Track P95/P99 latency; expect reduced slow query frequency

Check Write Performance: Writes may increase 10-30% per index if rarely-used; consider removal

References

• Index Strategy: references/index-strategy.md — indexing patterns and trade-offs
• Batch Operations: references/batch-operations.md — bulk operations and chunking
• Query Monitoring: references/query-monitoring.md — logging setup and slow query analysis
• Field Selection: references/field-selection.md — select vs include patterns and N+1 prevention
• Optimization Examples: references/optimization-examples.md — real-world improvements
• Next.js Integration: Next.js plugin for App Router-specific patterns
• Serverless: CLIENT-serverless-config skill for connection pooling