Does it monitor live production environments?

This skill focuses on code-level analysis and identifying potential hotspots within the source files during development, debugging, or code review phases.

Can it suggest specific code changes?

Yes, it provides detailed recommendations such as switching to asynchronous operations, using more efficient data structures, or refactoring O(n^2) algorithms.

How does this skill help with CPU bottlenecks?

It analyzes your codebase to find inefficient loops, expensive regex patterns, and synchronous blocks, providing specific optimization steps to reduce processor load.

Is it limited to a specific programming language?

No, while examples include Python and Java, the skill is designed to analyze logic and patterns across various languages supported by the Claude environment.

CPU Performance Monitor

Name: CPU Performance Monitor
Author: intent-solutions-io

byintent-solutions-io

Analíticas y Monitorización

Monitors and analyzes application CPU usage patterns to identify performance bottlenecks and optimize algorithmic efficiency.

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This skill empowers developers to detect and resolve processor-intensive operations within their codebase by analyzing execution patterns, spotting inefficient loops, and identifying synchronous blocking calls. It provides actionable recommendations for algorithmic improvements, asynchronous processing, and regex optimization, making it an essential tool for performance tuning, reducing latency, and improving overall application throughput during the development lifecycle.

Características Principales

Identification of CPU hotspots and performance bottlenecks
Detection of synchronous blocking operations in async code
Regex performance profiling and optimization suggestions
Detailed reporting on processor utilization patterns
0 GitHub stars
Analysis of algorithmic complexity and Big O efficiency

Casos de Uso

Optimizing high-latency scripts and server-side applications
Troubleshooting performance regressions in CI/CD pipelines
Refactoring computationally expensive functions for better scale

Acerca de

Características Principales

Identification of CPU hotspots and performance bottlenecks
Detection of synchronous blocking operations in async code
Regex performance profiling and optimization suggestions
Detailed reporting on processor utilization patterns
0 GitHub stars
Analysis of algorithmic complexity and Big O efficiency

Casos de Uso

Optimizing high-latency scripts and server-side applications
Troubleshooting performance regressions in CI/CD pipelines
Refactoring computationally expensive functions for better scale