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sql-pro

Analyzes SQL performance bottlenecks across PostgreSQL, MySQL, SQL Server, and Oracle and proposes targeted optimizations.

Updated Aug 23, 2026
Search Tags:#cross-platform#sql#data-integrity#query-optimization#database-performance#execution-plans#index-design
One-click install
npx skills add https://github.com/mikebronner/development-settings --skill sql-pro-mikebronner
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sql-pro
Source: https://github.com/mikebronner/development-settings/tree/main/.ai/skills/sql-pro
Command: npx skills add https://github.com/mikebronner/development-settings --skill sql-pro-mikebronner

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

SQL performance tuning across PostgreSQL, MySQL, SQL Server, and Oracle to reduce latency, avoid bottlenecks, and ensure scalable data operations.

Core Features & Use Cases

  • Cross-platform query optimization: analyze and optimize queries for multiple RDBMS, taking platform-specific features into account.
  • Index design and statistics strategy: recommend appropriate indexes, partitioning, and statistics adjustments to improve plan quality.
  • Implementation and validation: generate safe execution plans, test against representative workloads, and document changes to preserve data integrity.

Quick Start

Analyze a sample schema, identify bottlenecks, and propose a prioritized set of index and query optimizations.

Frequently Asked Questions about sql-pro

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

FAQPage Schema
How do I identify SQL query bottlenecks across PostgreSQL, MySQL, SQL Server, and Oracle?▼

Identify SQL query bottlenecks across PostgreSQL, MySQL, SQL Server, and Oracle by analyzing execution plans and schema statistics to isolate latency sources. Targeted optimizations are then proposed to address complex joins and varying data volumes while preserving data integrity.

What is the best way to design indexes for complex joins and evolving schemas?▼

The best way to design indexes for complex joins and evolving schemas is to align index strategies with up-to-date statistics and platform-specific partitioning. This ensures safe execution plans and robust error handling while maintaining ANSI SQL compliance.

Why does my SQL query performance degrade when data volume increases?▼

SQL query performance degrades when data volume increases due to outdated statistics, missing appropriate indexes, or inefficient execution plans. Analyzing bottlenecks across PostgreSQL, MySQL, SQL Server, and Oracle helps propose targeted optimizations to ensure scalable data operations.

Can I optimize SQL queries for multiple database platforms using ANSI SQL compliance?▼

You can optimize SQL queries for multiple database platforms using ANSI SQL compliance by applying cross-platform query optimization techniques. This approach analyzes platform-specific features while maintaining correct index design and safe execution plans across PostgreSQL, MySQL, SQL Server, and Oracle.

How to validate execution plans after applying query optimizations?▼

Validate execution plans after applying query optimizations by testing the recommendations against representative workloads with varying data volumes. This implementation and validation phase ensures safe execution plans, robust error handling, and preserved data integrity before finalizing schema changes.

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