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database-optimizer

Analyze query plans and workload mix to identify database bottlenecks.

22|2|Updated Mar 24, 2026
Search Tags:#performance#indexing#database#risk-management#tuning#query-plans#workload-analysis
One-click install
npx skills add https://github.com/jshsakura/awesome-opencode-skills --skill database-optimizer-jshsakura
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: database-optimizer
Source: https://github.com/jshsakura/awesome-opencode-skills/tree/main/skills/database-optimizer
Command: npx skills add https://github.com/jshsakura/awesome-opencode-skills --skill database-optimizer-jshsakura

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps data-driven teams identify and remedy database performance bottlenecks by analyzing query plans, access paths, and workload characteristics.

Core Features & Use Cases

  • Map hot queries, access patterns, and write/read mixes to locate performance bottlenecks.
  • Identify dominant bottleneck sources such as planner choices, indexing, joins, locking, or schema shape.
  • Recommend the smallest high-leverage improvement with explicit tradeoffs and a clear rollback path.

Quick Start

Analyze a current workload to identify the primary bottleneck and propose the smallest high-impact change with validation steps.

Frequently Asked Questions about database-optimizer

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

FAQPage Schema
How do I identify the primary bottleneck in my database workload?▼

Analyze query plans, access paths, and workload mix to locate database workload bottlenecks in indexing, joins, locking, or schema design for typical OLTP or mixed environments.

What is the best way to propose minimal high-leverage database tuning changes?▼

Apply evidence-led database tuning by analyzing read/write mixes to recommend the smallest high-leverage improvement with explicit tradeoffs, validation criteria, and rollback considerations.

Can I use query plan analysis for mixed workloads and OLTP systems?▼

Yes, query plan analysis applies to typical OLTP or mixed workloads to identify dominant bottleneck sources such as planner choices, indexing, joins, locking, or schema shape.

How do I ensure safe production deployment when applying database indexing changes?▼

Ensure safe production deployment by describing required measurements, validation criteria, and rollback considerations alongside the proposed database indexing and schema design improvements.

Why does my database performance degrade under heavy locking and joins?▼

Performance degrades when locking and joins become dominant bottleneck sources, identified by mapping hot queries and access patterns to locate workload bottlenecks and propose minimal changes.

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