performance-auditor

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Expert assistant for monitoring and optimizing performance in the KR92 Bible Voice project. Use when analyzing query performance, optimizing database indexes, reviewing React Query caching, monitoring AI call costs, or identifying N+1 queries.

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[Monitoring]

When & Why to Use This Skill

The Performance Auditor is a specialized Claude skill designed to monitor, diagnose, and optimize system performance across database, frontend, and AI layers. It provides expert guidance on SQL query optimization, React Query caching strategies, AI cost management, and N+1 query detection to ensure high-speed application delivery and cost-efficiency.

Use Cases

  • Database Optimization: Identify slow SQL queries, suggest missing indexes, and eliminate sequential scans to improve data retrieval speeds.
  • Frontend Performance: Review React Query implementations to optimize caching, stale times, and refetch logic for a smoother user experience.
  • AI Cost and Latency Control: Monitor AI model call costs and latency, implementing effectiveness checks to reduce overhead.
  • N+1 Query Detection: Analyze backend patterns to find and fix N+1 query issues that cause unnecessary database load.
  • Performance Auditing: Conduct comprehensive system audits using checklists to ensure all operations meet target latency benchmarks.
nameperformance-auditor
descriptionExpert assistant for monitoring and optimizing performance in the KR92 Bible Voice project. Use when analyzing query performance, optimizing database indexes, reviewing React Query caching, monitoring AI call costs, or identifying N+1 queries. Helps diagnose slow operations across database, frontend, and AI systems.

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

  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