How does the CPU Usage Monitor identify hotspots?

It scans the codebase for computationally expensive patterns, inefficient loops, and complex regex that typically consume high CPU cycles, providing a roadmap for optimization.

Does it support multiple programming languages?

The skill is language-agnostic and can analyze various languages including Python, Java, JavaScript, and C++ to find CPU-intensive operations and synchronous blocking calls.

Can it detect blocking calls in async environments?

Absolutely. It helps identify synchronous blocking operations that might be hindering event loop performance in asynchronous applications like Node.js or FastAPI.

Can this skill help with Big O complexity?

Yes, it analyzes code structure to identify areas with high algorithmic complexity (like O(n²) loops) and suggests more efficient data structures or alternative algorithms.

CPU Usage & Performance Monitor

Name: CPU Usage & Performance Monitor
Author: BbgnsurfTech

byBbgnsurfTech

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분석 및 모니터링

Analyzes and optimizes application CPU usage to eliminate performance bottlenecks and improve processor execution efficiency.

소개

This skill enables Claude to perform deep analysis of your codebase to identify and resolve CPU-intensive operations. By monitoring usage patterns and analyzing algorithmic complexity, it pinpoints performance hotspots such as inefficient loops, blocking synchronous calls, and poorly optimized regular expressions. It is an essential tool for developers looking to reduce processor load, improve application responsiveness, and optimize infrastructure costs through targeted code refactoring and performance-first implementation patterns.

주요 기능

Analyzes and improves algorithmic complexity (Big O)
Generates specific refactoring suggestions for CPU efficiency
Identifies CPU hotspots and execution bottlenecks
3 GitHub stars
Optimizes inefficient loops and regex patterns
Detects blocking operations in asynchronous code

사용 사례

Troubleshooting application slowdowns during heavy processing
Reducing high CPU usage in Python or Java backends
Optimizing data processing pipelines for better performance

소개

주요 기능

Analyzes and improves algorithmic complexity (Big O)
Generates specific refactoring suggestions for CPU efficiency
Identifies CPU hotspots and execution bottlenecks
3 GitHub stars
Optimizes inefficient loops and regex patterns
Detects blocking operations in asynchronous code

사용 사례

Troubleshooting application slowdowns during heavy processing
Reducing high CPU usage in Python or Java backends
Optimizing data processing pipelines for better performance