postgres-tuning

Optimize PostgreSQL 17/18+ performance by tuning async I/O and analyzing query plans.

14|5|Updated Jan 29, 2026

Search Tags:#indexing #postgresql #performance tuning #query analysis #database optimization #autovacuum #aio

Ready to run

npx skills add https://github.com/oakoss/agent-skills --skill postgres-tuning

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: postgres-tuning
Source: https://github.com/oakoss/agent-skills/tree/main/skills/postgres-tuning
Command: npx skills add https://github.com/oakoss/agent-skills --skill postgres-tuning

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses slow query performance and inefficient database operations in PostgreSQL, helping you diagnose and resolve bottlenecks related to I/O, indexing, and configuration.

Core Features & Use Cases

Performance Tuning: Optimizes PostgreSQL 17/18+ performance across I/O, query execution, indexing, and maintenance.
Diagnostic Tools: Leverages advanced monitoring views like pg_stat_io and pg_stat_statements for in-depth analysis.
Use Case: When users report slow response times for critical application features, this Skill can analyze query plans, identify missing indexes, and suggest configuration adjustments to improve database throughput and reduce latency.

Quick Start

Use the postgres-tuning skill to analyze slow queries and suggest index optimizations.

Frequently Asked Questions about postgres-tuning

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

FAQPage Schema

How do I analyze slow PostgreSQL queries and identify missing indexes?▼

To analyze slow PostgreSQL queries, use EXPLAIN BUFFERS to review query plans and identify missing indexes. This approach diagnoses I/O bottlenecks and refines index strategies to improve overall database throughput.

What is the best way to resolve PostgreSQL I/O bottlenecks and database bloat?▼

The best way to resolve PostgreSQL I/O bottlenecks and database bloat is by tuning async I/O and managing autovacuum. Utilizing advanced monitoring views like pg_stat_io helps pinpoint inefficiencies and reduce latency.

Does this PostgreSQL performance tuning approach support older database versions?▼

This performance tuning approach specifically targets PostgreSQL 17 and 18+ versions. It leverages newer monitoring views like pg_stat_io and async I/O configuration parameters not available in older database releases.

How does pg_stat_statements help with PostgreSQL database optimization?▼

pg_stat_statements aids PostgreSQL database optimization by providing in-depth analysis of query execution statistics. Combined with pg_stat_io, it helps diagnose inefficient database operations, slow queries, and configuration bottlenecks.

When should I tune autovacuum to fix slow PostgreSQL query performance?▼

You should tune autovacuum to fix slow PostgreSQL query performance when experiencing database bloat and inefficient operations. Adjusting autovacuum configurations resolves maintenance bottlenecks and restores query execution speed.