Agent skill · data analytics · jeremylongshore
profiling-application-performance
Execute this skill enables AI assistant to profile application performance,
Why this skill is useful
Adds specific performance profiling techniques and metrics analysis for Node.js, Python, and Java applications that the AI wouldn't reliably generate on its own.
What it needs
Requires bash installed locally. About 2k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Application Profiler Profile application performance across Node.js, Python, and Java stacks by analyzing CPU usage, memory allocation, and execution hotspots to pinpoint optimization targets. Overview This skill empowers Claude to analyze application performance, pinpoint bottlenecks, and recommend optimizations. By leveraging the application-profiler plugin, it provides insights into CPU usage, memory allocation, and execution time, enabling targeted improvements. How It Works 1. Identify Application Stack: Determines the application's technology (e.g., Node.js, Python, Java). 2. Locate Entry Points: Identifies main application entry points and critical execution paths. 3. Analyze Performance Metrics: Examines CPU usage, memory allocation, and execution time to detect bottlenecks. 4. Generate Profile: Compiles the analysis into a comprehensive performance profile, highlighting areas for optimization. When to Use This Skill This skill activates when you need to: Analyze application performance for bottlenecks. Identify CPU-intensive operations and memory leaks. Optimize application execution time. Examples Example 1: Identifying Memory Leaks User request: "Analyze my Node.js application for memory leaks." The skill will: 1. Activate the application-profiler plugin. 2. Analyze the application's memory allocation patterns. 3. Generate a profile highlighting potential memory leaks. Example 2: Optimizing CPU Usage User request: "Profile my Python script and find the most CPU-intensive functions." The skill will: 1. Activate the application-profiler plugin. 2. Analyze the script's CPU usage. 3. Generate a profile identifying the functions consuming the most CPU time. Best Practices Code Instrumentation: Ensure the application code is instrumented for accurate profiling. Realistic Workloads: Use realistic workloads during profiling to simulate real-world scenarios. Iterative Optimization: Apply optimizations iteratively and re-profile to measure improvements. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/profiling-application-performance--940772