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system-profile

Profile Python scripts, processes, functions, or systems for CPU, memory, GPU, and interconnect usage.

Updated Apr 29, 2026
Search Tags:#performance#profiling#instrumentation#gpu#cpu#profile
One-click install
npx skills add https://github.com/jkfee/Auto-Research --skill system-profile-jkfee
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: system-profile
Source: https://github.com/jkfee/Auto-Research/tree/main/skills/system-profile
Command: npx skills add https://github.com/jkfee/Auto-Research --skill system-profile-jkfee

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Proactively identify bottlenecks by profiling a target's CPU, memory, GPU, and interconnect usage and delivering actionable insights.

Core Features & Use Cases

  • Profile arbitrary targets (scripts, processes, functions, or entire systems) and summarize results.
  • Generate structured performance reports with actionable recommendations.
  • Produce instrumentation changelog and artifacts under ./profile_output/.

Quick Start

Profile a target and generate a structured performance report.

Frequently Asked Questions about system-profile

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

FAQPage Schema
How do I profile a Python script to find CPU and memory bottlenecks?▼

Profiling a Python script with this Skill captures CPU, memory, interconnect, and GPU usage to identify bottlenecks. It generates a structured performance report with actionable recommendations and saves artifacts under the ./profile_output directory.

Can I profile a running process or just Python scripts?▼

Profiling applies to running processes, Python scripts, modules, functions, and entire systems. It targets the specified process to summarize CPU, memory, interconnect, and GPU performance metrics into an output-rich report.

Does profiling support GPU and interconnect usage analysis?▼

GPU and interconnect profiling are supported alongside CPU and memory analysis. The Skill profiles the specified target and summarizes the results to reveal hardware-level bottlenecks and deliver actionable insights.

What is the best way to add instrumentation when profiling a system?▼

The best way to add instrumentation is using the optional step-by-step instrumentation feature. It profiles the target, collects artifacts under ./profile_output, and produces an instrumentation changelog detailing the applied modifications.

How do I get actionable recommendations after profiling my code?▼

Actionable recommendations are included in the generated structured performance report. After profiling the specified target, the Skill summarizes the results and highlights bottlenecks to guide your optimization efforts.

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