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postgres-expert

Diagnose and optimize PostgreSQL performance with EXPLAIN ANALYZE and VACUUM tuning.

2|1|Updated Jan 16, 2026
Search Tags:#performance#security#sql#partitioning#replication#postgres#explain
One-click install
npx skills add https://github.com/tundraray/overture --skill postgres-expert-tundraray
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: postgres-expert
Source: https://github.com/tundraray/overture/tree/main/postgres-expert/skills/postgres-expert
Command: npx skills add https://github.com/tundraray/overture --skill postgres-expert-tundraray

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

PostgreSQL environments often struggle with optimizing query performance, replication configuration, partitioning strategy design, hardening security, and maintaining advanced features. This Skill provides a structured approach to diagnose, design, and implement best practices across EXPLAIN analyses, JSONB operations, VACUUM tuning, transaction isolation, and performance monitoring.

Core Features & Use Cases

  • Diagnose and optimize queries with EXPLAIN ANALYZE, pg_stat_statements, and planner tuning for work_mem, autovacuum, and index choices.
  • Design robust replication, partitioning strategies, and security hardening for production PostgreSQL clusters, including logical and physical replication patterns.
  • Use cases include optimizing large-scale databases, JSONB path operations, maintenance emergencies with concrete numbers, and clear trade-offs to avoid regressions.

Quick Start

Run an initial EXPLAIN ANALYZE pass on the slowest query, identify bottlenecks, adjust configuration incrementally, re-run analysis, and document changes.

Frequently Asked Questions about postgres-expert

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

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

To optimize slow PostgreSQL queries, run EXPLAIN ANALYZE to identify bottlenecks, adjust work_mem and autovacuum configurations incrementally, re-run the analysis, and document changes to avoid regressions while targeting measurable numeric performance goals.

What is the best way to tune PostgreSQL VACUUM and autovacuum for large databases?▼

Tuning PostgreSQL VACUUM requires adjusting autovacuum parameters based on workload size, targeting maintenance emergencies with concrete numbers and clear trade-offs to ensure reliability and prevent bloat in large-scale databases.

How do I design robust PostgreSQL partitioning and replication strategies?▼

Designing PostgreSQL partitioning and replication involves structuring logical and physical replication patterns for production clusters, ensuring robust data distribution and high availability while applying explicit version constraints and security hardening.

Can I use JSONB path operations for performance optimization in PostgreSQL?▼

JSONB path operations can be optimized in PostgreSQL by diagnosing performance with EXPLAIN ANALYZE, tuning planner choices, and applying concrete version requirements and trade-offs to manage large-scale JSONB data efficiently.

Does PostgreSQL security hardening require explicit version constraints?▼

PostgreSQL security hardening requires explicit version constraints to ensure recommendations include concrete version requirements, measurable numeric targets, and failure modes, preventing compatibility issues and regressions across production clusters.

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