Performance Auditor
Expert performance optimization for the Raamattu Nyt application across database, frontend, and AI systems.
Quick Start
Choose your performance concern:
- Database performance: Slow queries, missing indexes, sequential scans → See
references/sql-queries.md - React Query optimization: Caching strategy, stale times, unnecessary refetches → See
references/react-query-patterns.md - AI performance: Latency, costs, cache effectiveness → See
references/ai-monitoring.md - N+1 query detection: Finding and fixing N+1 patterns → See
references/n+1-detection.md - Optimization checklist: Complete performance audit → See
references/checklist.md - Common gotchas: Known issues and pitfalls → See
references/learnings.md
Performance Targets
Reference targets for healthy performance:
| Operation | Target | |-----------|--------| | Single verse lookup | <20ms | | Chapter load | <50ms | | Text search | <100ms | | AI translation | <500ms | | Page load (FCP) | <1.5s | | API response | <200ms |
How to Use This Skill
- Identify your performance issue (database, frontend, AI, or N+1)
- Read the appropriate reference file above
- Run SQL scripts or code patterns from
scripts/if needed - Check
references/learnings.mdif results seem unexpected
Key Tools
- Database analysis: Read
references/sql-queries.mdthen runscripts/analyze-queries.sql - N+1 detection: See
references/n+1-detection.mdandscripts/detect-n+1.js - Cache optimization: See
references/react-query-patterns.mdfor staleTime/gcTime strategy - AI monitoring: See
references/ai-monitoring.mdfor latency and cost tracking
Context Files
For codebase structure reference:
Docs/context/db-schema-short.md- Database tables and indexesDocs/context/supabase-map.md- Edge functions to monitor