detect-n-plus-one

N+1 query detection identifies loops that fetch a list then issue separate queries per item, causing performance bottlenecks. This Skill scans code across languages, traces execution paths, and outputs structured findings with file locations, confidence levels, and batching fixes.

N+1 query detection works across multiple languages including C#, TypeScript, Python, and Java, using language-specific idiom patterns to identify loops coupled with per-item queries in backend services, APIs, and data access layers.

Yes. N+1 query detection applies to any codebase where loops perform per-item queries—across ORMs, raw SQL, and API calls. It traces call paths to verify performance hotspots and proposes batching strategies for your specific query patterns.

N+1 query detection applies semantic and static analysis phases, traces execution call paths to confirm loops leading to per-item queries, and outputs actionable findings with confidence levels so you can prioritize fixes.

Automated N+1 detection systematically scans entire codebases across multiple languages, traces execution flows that manual review misses, and delivers structured findings with precise line locations and recommended batching strategies at scale.

Run N+1 query detection during code review or before deployment to surface performance bottlenecks early. It's especially valuable after adding data access logic, refactoring queries, or scaling backend services where per-item query costs compound.