performance-profiling

Guide profiling workflows to locate performance bottlenecks in Python and JavaScript code.

9|5|Updated Aug 8, 2025

Search Tags:#bottlenecks #benchmark #flamegraph #profile #py-spy #cprofile

Ready to run

npx skills add https://github.com/AnExiledDev/CodeForge --skill performance-profiling-anexileddev

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: performance-profiling
Source: https://github.com/AnExiledDev/CodeForge/tree/main/.devcontainer/plugins/devs-marketplace/plugins/code-directive/skills/performance-profiling
Command: npx skills add https://github.com/AnExiledDev/CodeForge --skill performance-profiling-anexileddev

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Locates performance bottlenecks in code by guiding measurement and profiling workflows.

Core Features & Use Cases

Guided profiling lifecycle: baseline, profile, analyze, and verify improvements with recommended tools.
Multi-language & system coverage: applicable to Python, JavaScript, and system-level profiling to expose CPU and memory hotspots.
Use Cases: identify hot paths, reduce latency, and validate optimization strategies with flamegraphs and reports.

Quick Start

Run a targeted profiling session on your project to reveal hot paths and memory hotspots.

Frequently Asked Questions about performance-profiling

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

FAQPage Schema

How do I find performance bottlenecks in my Python application?▼

You locate performance bottlenecks by running a guided profiling workflow that baselines execution, profiles hot paths with tools like cProfile or py-spy, and analyzes reports to pinpoint CPU hotspots.

What is the best way to profile JavaScript code for latency issues?▼

Profiling JavaScript for latency involves using guided measurement workflows with Chrome DevTools to expose CPU and memory hotspots, identify hot paths, and validate optimization strategies.

Can I use py-spy to generate a flamegraph for my system-level workflows?▼

Yes, py-spy can generate flamegraphs for system-level workflows, as the profiling lifecycle supports multi-language and system coverage to expose memory and CPU hotspots in real-world apps.

How do I benchmark and validate code improvements after optimizing a hot path?▼

You benchmark and validate improvements by applying targeted hot-path optimization, then measuring and verifying performance gains against the initial baseline to ensure latency reduction.

Does this profiling workflow support both Python and JavaScript environments?▼

Yes, this profiling workflow supports both Python and JavaScript environments, applying measurement and optimization techniques across both languages to benchmark and fix bottlenecks in real-world apps.