Does it automatically apply changes to my database?

No, it provides structured proposals including a summary, impact analysis, and verification steps, allowing developers to review and execute changes through their own migration workflows.

Which database systems does this skill support?

It is designed to work with major relational and non-relational systems including PostgreSQL, MySQL, SQLite, and other SQL-based environments.

Can it help with N+1 query problems?

Yes, one of its core responsibilities is identifying inefficient query patterns like N+1 and suggesting batching, improved joins, or pagination to resolve them.

Is the Database Optimizer safe for production use?

Yes, it follows a conservative 'safety-first' approach, requiring context discovery and impact measurement before suggesting any changes, and always provides a rollback plan.

How does it handle large-scale schema changes?

It analyzes data volume and growth patterns to suggest migrations with low-risk execution paths, such as partitioning or materialized views, while always prioritizing data preservation.

Database Optimizer

Name: Database Optimizer
Author: Masked-Kunsiquat

byMasked-Kunsiquat

0•

Gestión de Bases de Datos

Optimizes database performance and scalability through safe query rewriting, strategic indexing, and system configuration tuning.

The Database Optimizer is a specialized Claude Code skill designed to identify and resolve performance bottlenecks in database systems like PostgreSQL, MySQL, and SQLite. It operates with a 'measurement-first' philosophy, ensuring that any changes to queries, indexes, or schemas are backed by execution plan analysis and data-driven insights. By prioritizing data integrity and operational stability, this skill helps developers eliminate slow queries, reduce lock contention, and implement robust scalability patterns without risking production downtime or data loss.

Características Principales

01Safe query rewriting to eliminate N+1 patterns and inefficient joins

02Schema-level optimization suggestions like partitioning and archival

03Database system configuration tuning for memory and connection pooling

040 GitHub stars

05Data-driven indexing strategies including partial and expression indexes

06In-depth execution plan analysis and bottleneck identification

Casos de Uso

01Designing efficient indexing strategies for rapidly growing application datasets

02Troubleshooting and fixing slow-running production queries causing high latency

03Auditing database schemas to reduce resource contention and improve write throughput

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add masked-kunsiquat/crm-orbit2 database-optimizer

For use in Claude.ai and ChatGPT

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