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database-optimizer

Analyze slow queries and tune PostgreSQL and MySQL configurations.

Updated Aug 23, 2026
Search Tags:#indexing#database#postgresql#optimization#mysql#query-tuning#analyze
One-click install
npx skills add https://github.com/KaiBoo404/agent-skills-with-project-template --skill database-optimizer-kaiboo404
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: database-optimizer
Source: https://github.com/KaiBoo404/agent-skills-with-project-template/tree/main/.agents/skills/database-optimizer
Command: npx skills add https://github.com/KaiBoo404/agent-skills-with-project-template --skill database-optimizer-kaiboo404

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Optimizes database performance by analyzing slow queries, designing efficient indexing strategies, and tuning configuration parameters to reduce latency and improve throughput across PostgreSQL and MySQL.

Core Features & Use Cases

  • Analyze slow queries and execution plans to identify bottlenecks and misconfigurations.
  • Design and implement indexing strategies (including covering and partial indexes) to accelerate common workloads.
  • Tune database configurations (memory, WAL, autovacuum, parallelism) with safe, incremental changes and thorough validation.
  • Apply guidance to real-world scenarios such as high-traffic OLTP workloads, large analytical queries, and replication setups to maintain stable performance.

Quick Start

Analyze a representative slow query or workload and generate an optimization plan with concrete index, SQL, and configuration changes.

Frequently Asked Questions about database-optimizer

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

FAQPage Schema
How do I analyze slow PostgreSQL and MySQL queries to find bottlenecks?▼

Analyze slow PostgreSQL and MySQL queries by evaluating execution plans with EXPLAIN ANALYZE to identify bottlenecks and misconfigurations. The process isolates inefficient query paths to guide targeted tuning and performance improvements.

What is the best way to design database indexes without hurting write performance?▼

Design database indexes by selecting covering and partial indexes to accelerate common workloads. This approach intentionally avoids over-indexing, ensuring that read performance gains do not degrade write throughput or database scalability.

Can I tune database configuration parameters for high-traffic OLTP workloads?▼

Yes, you can tune database configuration parameters for high-traffic OLTP workloads by adjusting memory, WAL, autovacuum, and parallelism settings. Changes are applied safely through safe incremental validation to maintain stable performance.

Does query tuning work for both large analytical queries and replication setups?▼

Query tuning works for large analytical queries and replication setups by applying execution-plan analysis and index strategies to real-world scenarios. This maintains stable, scalable performance across diverse database workloads and traffic patterns.

How do I partition large database tables to improve query tuning results?▼

Partition large database tables as part of a comprehensive optimization plan to improve query tuning results. Partitioning manages large analytical queries and high-traffic workloads by reducing scan overhead and accelerating execution times.

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