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sql-optimization

Optimize SQL queries across MySQL, PostgreSQL, SQL Server, and Oracle databases.

Updated Mar 18, 2026
Search Tags:#performance#indexing#optimization#sql#query-tuning#cross-database#execution-plan
One-click install
npx skills add https://github.com/angryconsultant/Copilot-CLI --skill sql-optimization-angryconsultant
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sql-optimization
Source: https://github.com/angryconsultant/Copilot-CLI/tree/main/skills/sql-optimization
Command: npx skills add https://github.com/angryconsultant/Copilot-CLI --skill sql-optimization-angryconsultant

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Identify and address SQL performance bottlenecks across multiple database engines, providing practical tuning guidance for queries, indexing, and workload management.

Core Features & Use Cases

  • Cross-database performance analysis and tuning guidance for MySQL, PostgreSQL, SQL Server, Oracle, and others
  • Query rewriting, indexing strategies, and pagination optimizations to improve latency and resource usage
  • Use Case: optimize a slow reporting query across a data warehouse spanning multiple DB engines

Quick Start

Analyze the current SQL workload and return an optimized query plan with indexing recommendations.

Frequently Asked Questions about sql-optimization

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

FAQPage Schema
How do I optimize slow SQL queries across different database engines?▼

You can optimize slow SQL queries by analyzing execution plans and applying indexing, query rewriting, and pagination techniques to reduce latency and resource usage across MySQL, PostgreSQL, SQL Server, and Oracle.

What is the best way to improve SQL performance for a data warehouse reporting workload?▼

Improving SQL performance for reporting workloads involves identifying bottlenecks, rewriting inefficient queries, and implementing proper indexing strategies to handle cross-database data retrieval more efficiently.

Does this SQL optimization approach work with both MySQL and PostgreSQL?▼

Yes, this SQL optimization approach works universally across multiple database engines including MySQL, PostgreSQL, SQL Server, and Oracle to analyze workloads and provide targeted tuning guidance.

How do I analyze an execution plan to identify SQL performance bottlenecks?▼

Analyzing an execution plan involves reviewing query execution paths to pinpoint performance bottlenecks, which then guides the application of indexing strategies, batch operations, and query rewriting for optimization.

Can I get indexing recommendations for complex cross-database queries?▼

Yes, you can receive indexing recommendations and optimized query plans for complex cross-database queries by analyzing your current SQL workload and addressing performance bottlenecks across multiple database engines.

When should I use query rewriting instead of adding indexes for SQL query tuning?▼

Query rewriting is preferred when execution plan analysis reveals inefficient query logic or poor pagination, whereas adding indexes directly targets data retrieval bottlenecks to improve overall SQL latency.

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