profile

Profile Swift applications with xctrace and parse hotspots via Python.

4|Updated Nov 22, 2025
One-click install
npx skills add https://github.com/r1cA18/dotfiles --skill profile-r1ca18
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: profile
Source: https://github.com/r1cA18/dotfiles/tree/main/skills/swift-dev-toolkit/skills/profile
Command: npx skills add https://github.com/r1cA18/dotfiles --skill profile-r1ca18

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python3, and includes scripts (resource) components.

What problem does it solve?

This Skill helps developers identify and resolve performance bottlenecks in their Swift applications by leveraging the command-line interface of Xcode's Instruments tool.

Core Features & Use Cases

  • Record Performance Data: Capture CPU usage, memory allocations, and system events using xctrace.
  • Analyze Hotspots: Parse trace data to pinpoint functions consuming the most resources.
  • Iterative Optimization: Facilitates a loop of profiling, code adjustment, and re-profiling to measure improvements.
  • Use Case: A developer notices their app is sluggish. They use this Skill to profile a specific user flow, identify a slow method in DataManager, optimize it, and then re-profile to confirm the performance gain.

Quick Start

Profile the application named 'MyApp' on a simulator for 5 seconds and save the trace to /tmp/profile.trace.

Frequently Asked Questions about profile

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

FAQPage Schema
How do I profile Swift application performance using xctrace?

You can profile Swift application performance using xctrace by recording CPU usage, memory allocations, and system events, then executing a Python script to parse the trace data and identify top hotspots.

Can I use Instruments CLI to analyze memory allocations on a simulator?

Yes, Instruments CLI supports profiling memory allocations and CPU bottlenecks on both simulators and physical devices, capturing system traces to help analyze resource consumption for your Swift applications.

What is the best way to identify CPU bottlenecks in a Swift app?

The best way to identify CPU bottlenecks is to record performance data with xctrace during a specific user flow, then parse the trace output to pinpoint functions consuming the most resources.

Do I need python3 to parse xctrace results?

Yes, you need python3 installed, as the Skill relies on a Python script to automatically parse the recorded trace data and extract the top performance hotspots for optimization.

How does iterative optimization work after profiling a Swift app?

Iterative optimization involves profiling your Swift app to find slow methods, adjusting the code to improve performance, and then re-profiling with xctrace to measure the resource consumption improvements.

When should I use xctrace instead of other profiling tools?

You should use xctrace when you need to automate performance profiling via the command line, capturing CPU and memory traces on simulators or physical devices without manual Xcode GUI interaction.