performance-audit

N+1 queries occur when a single query triggers multiple follow-up queries in a loop, multiplying database load. This Skill detects N+1 patterns by analyzing your backend code and provides specific fixes like eager loading, batching, or JOIN optimization to consolidate queries into fewer, more efficient calls.

Unpaginated findAll queries load entire tables into memory, consuming resources and causing timeouts as data grows. This Skill identifies unpaginated endpoints and guides you through adding limit/offset pagination or cursor-based strategies to retrieve data in manageable chunks.

Full-table scans bypass indexes and read every row, degrading performance under load. This Skill analyzes your queries to locate scans, then recommends query rewrites, LIKE pattern optimization, and index usage to ensure queries target specific rows efficiently.

Yes. This Skill identifies AI service latency bottlenecks and suggests timeout mitigation strategies, including retry logic, caching, and request optimization to prevent cascading failures in controllers and scheduled jobs.

Run this performance audit before scaling to map all bottlenecks across N+1 queries, unpaginated access, full-table scans, and AI latency. It ranks issues by impact, helping you fix top bottlenecks first and avoid expensive infrastructure scaling.

Yes. This Skill covers Redis caching usage as part of its optimization guidance, showing when and how to cache query results and reduce repeated database hits across batch processing, controller endpoints, and scheduled jobs.