Performance Auditor

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:

How to Use This Skill

1. Identify your performance issue (database, frontend, AI, or N+1)
2. Read the appropriate reference file above
3. Run SQL scripts or code patterns from scripts/ if needed
4. Check references/learnings.md if results seem unexpected

Key Tools

• Database analysis: Read references/sql-queries.md then run scripts/analyze-queries.sql
• N+1 detection: See references/n+1-detection.md and scripts/detect-n+1.js
• Cache optimization: See references/react-query-patterns.md for staleTime/gcTime strategy
• AI monitoring: See references/ai-monitoring.md for latency and cost tracking

Context Files

For codebase structure reference:

• Docs/context/db-schema-short.md - Database tables and indexes
• Docs/context/supabase-map.md - Edge functions to monitor