ai-performance

Scan codebases for performance anti-patterns across multiple languages.

54|3|Updated Feb 4, 2026
One-click install
npx skills add https://github.com/arcasilesgroup/ai-engineering --skill ai-performance
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ai-performance
Source: https://github.com/arcasilesgroup/ai-engineering/tree/main/.claude/skills/ai-performance
Command: npx skills add https://github.com/arcasilesgroup/ai-engineering --skill ai-performance

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses performance bottlenecks in code, such as N+1 query issues, inefficient algorithms, memory leaks, and I/O inefficiencies, across multiple programming languages.

Core Features & Use Cases

  • Multi-stack Performance Scanning: Detects N+1 queries, O(n^2) patterns, memory leaks, bundle size issues, and I/O bottlenecks.
  • Automated Detection: Uses static analysis and heuristics to identify performance anti-patterns.
  • Use Case: A developer suspects a web application is slow due to inefficient database queries. They can use this skill to automatically scan the codebase, identify N+1 query patterns in the ORM, and receive specific recommendations for optimization.

Quick Start

Run the ai-performance skill to scan the current project for performance issues.

Frequently Asked Questions about ai-performance

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

FAQPage Schema
How do I find N+1 queries and performance bottlenecks in my codebase?

To find N+1 queries and performance bottlenecks, scan your codebase using static analysis and heuristics. This detects anti-patterns including memory leaks and I/O inefficiencies across multiple languages, scoring each finding by impact to provide specific remediation guidance.

What types of performance anti-patterns can code profiling heuristics detect?

Code profiling heuristics detect performance anti-patterns such as N+1 queries, O(n^2) algorithmic complexity, memory leaks, bundle size issues, and I/O inefficiencies across Python, .NET, TypeScript/React, Rust, and SQL codebases.

Does automated performance scanning support Rust and TypeScript/React projects?

Yes, automated performance scanning supports Rust and TypeScript/React projects. It also analyzes Python, .NET, and SQL codebases to identify algorithmic complexity, memory leaks, and inefficient database queries using static analysis.

How do I optimize slow web application database queries caused by ORM patterns?

To optimize slow database queries caused by ORM patterns, scan your codebase to identify N+1 query issues. The scan scores these performance bottlenecks by impact and provides specific recommendations for optimization to resolve the inefficiencies.

What is the best way to identify memory leaks and O(n^2) patterns across multiple stacks?

The best way to identify memory leaks and O(n^2) patterns across multiple stacks is running an automated static analysis scan. It detects these algorithmic complexity and memory issues, evaluates their impact, and outputs targeted remediation guidance.