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performance-auditor

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Atualizado22 de junho de 2026 às 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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Ocupações relacionadasSOC

Baseado na classificação ocupacional SOC

Desenvolvedores de softwareInformática e Matemática·SOC 15-1252

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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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Expert assistant for creating and maintaining Supabase Edge Functions for the KR92 Bible Voice project. Use when (1) creating new Edge Functions, (2) setting up CORS and error handling, (3) integrating shared modules from _shared/, (4) adding JWT validation, (5) configuring environment variables, (6) auditing or updating dependency versions across functions. Triggers include "edge function", "create function", "serverless", "deno function", "update edge imports", "version drift".

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