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performance-auditor

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Actualizado22 de junio de 2026, 13:26

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. Helps diagnose slow operations across database, frontend, and AI systems.

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Spectaculous-Code

Spectaculous-Code/raamattu-nyt

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SKILL.md

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name	performance-auditor
description	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. 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

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.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

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2026-06-220

name	performance-auditor
description	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. 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

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.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