What does the Performance Oracle skill do?

It acts as an automated performance engineer within Claude Code, scanning your files for bottlenecks, inefficient algorithms, and resource leaks.

Can it help with slow database queries?

Yes, it specifically identifies N+1 query problems, missing indexes, and unnecessary data fetching that slows down database interactions.

How does it rank the severity of performance issues?

It uses a P1 to P3 scale: P1 for critical production blockers (like OOM crashes), P2 for important inefficiencies, and P3 for minor micro-optimizations.

Does it provide optimized code snippets?

Yes, for every issue identified, the skill provides a comparison between the current code and an optimized version with an explanation of the expected improvement.

Does it support complexity analysis?

Yes, the skill calculates Big O notation (e.g., O(n²) vs O(n)) to help you understand how your code will perform as data volume increases.

Performance Oracle

Name: Performance Oracle
Author: jovermier

byjovermier

Analytics & Monitoring

Analyzes codebases to identify performance bottlenecks, algorithmic inefficiencies, and scalability concerns for optimal execution.

About

Performance Oracle is a specialized Claude Code skill designed to act as a performance engineer, meticulously auditing your codebase for issues that impact speed and resource consumption. It identifies critical problems such as N+1 database queries, memory leaks, inefficient algorithms with high complexity, and sub-optimal caching strategies. By providing detailed optimization reports complete with severity ratings and ready-to-use refactored code, it helps developers build high-performance systems capable of scaling to support thousands of users and large datasets.

Key Features

Big O algorithmic complexity analysis and linear optimization
Structured performance reports with P1 to P3 severity ratings
0 GitHub stars
Identification of memory leaks and inefficient resource allocations
I/O optimization for blocking operations and payload reduction
Detection of N+1 database queries and missing table indexes

Use Cases

Debugging slow API response times and database-heavy operations
Conducting a pre-production scalability audit for complex new features
Refactoring legacy code to reduce CPU usage and memory footprint

About

Key Features

Big O algorithmic complexity analysis and linear optimization
Structured performance reports with P1 to P3 severity ratings
0 GitHub stars
Identification of memory leaks and inefficient resource allocations
I/O optimization for blocking operations and payload reduction
Detection of N+1 database queries and missing table indexes

Use Cases

Debugging slow API response times and database-heavy operations
Conducting a pre-production scalability audit for complex new features
Refactoring legacy code to reduce CPU usage and memory footprint