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agency-database-optimizer

Optimize PostgreSQL, MySQL, Supabase, and PlanetScale databases with schema design, query tuning, and indexing.

Updated Apr 11, 2026
Search Tags:#indexing#database#postgresql#migrations#mysql#query-optimization#explain-analyze
One-click install
npx skills add https://github.com/omeraltn/ice_cream_website_testing --skill agency-database-optimizer-omeraltn
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agency-database-optimizer
Source: https://github.com/omeraltn/ice_cream_website_testing/tree/main/.antigravity/agency-database-optimizer
Command: npx skills add https://github.com/omeraltn/ice_cream_website_testing --skill agency-database-optimizer-omeraltn

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Optimize database performance by designing scalable schemas, tuning queries, and implementing efficient indexing.

Core Features & Use Cases

  • Optimized schema design: Creates scalable structural layouts with appropriate constraints and indexing.
  • Query optimization: Uses EXPLAIN ANALYZE, indexing strategies, and query rewrites to speed up critical paths.
  • Migration safety: Provides reversible migrations and zero-downtime deployment patterns.
  • Monitoring & diagnostics: Instruments and monitors long-running queries to maintain performance visibility.

Quick Start

Analyze a slow workload, then deliver an optimized schema design, indexing plan, and a reversible migration strategy.

Frequently Asked Questions about agency-database-optimizer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I optimize slow PostgreSQL queries using EXPLAIN ANALYZE?▼

PostgreSQL query optimization uses EXPLAIN ANALYZE to identify bottlenecks, then applies B-tree, GiST, or GIN indexing and query rewrites to reduce latency on critical execution paths.

What's the best way to run zero-downtime database migrations on MySQL?▼

Zero-downtime migrations use reversible deployment patterns to apply schema changes safely, ensuring high throughput applications maintain availability without locking tables during updates.

When do I need partial indexes for database performance tuning?▼

Partial indexes are needed for query optimization when specific subsets of data are frequently queried, reducing index size and improving speed compared to full table B-tree indexes.

Does this database optimization approach work with Supabase and PlanetScale?▼

Yes, the schema design and indexing strategies apply to cloud-native databases like Supabase and PlanetScale, supporting high throughput and low latency across managed database platforms.

How do I design a scalable database schema for high throughput applications?▼

Scalable schema design balances normalization vs denormalization decisions based on access patterns, implementing appropriate constraints and connection pooling to sustain high throughput.

Why are my complex database joins causing high latency in production?▼

High latency from complex joins often stems from missing or inefficient indexes; using EXPLAIN ANALYZE reveals execution bottlenecks so you can apply targeted B-tree or GIN indexing strategies.

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