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get-available-resources

Detects CPU, GPU, memory, and disk resources for scientific computing.

Updated Aug 23, 2026
Search Tags:#parallel processing#scientific computing#GPU detection#system resources#memory info
One-click install
npx skills add https://github.com/ogngnaoh/scientific-agent-skills --skill get-available-resources-ogngnaoh
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: get-available-resources
Source: https://github.com/ogngnaoh/scientific-agent-skills/tree/main/scientific-agent-skills/skills/get-available-resources
Command: npx skills add https://github.com/ogngnaoh/scientific-agent-skills --skill get-available-resources-ogngnaoh

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

It helps scientists and engineers identify available system resources to optimize computational workflows and prevent resource bottlenecks.

Core Features & Use Cases

  • Resource Detection: Automatically detects CPU, GPU, memory, and disk resources.
  • Strategic Recommendations: Provides guidance on parallel processing, memory management, and GPU utilization for scientific tasks.
  • Use Case: Before training a neural network, determine GPU availability and system memory to choose the right libraries and settings.

Quick Start

Run the Python script in scripts/detect_resources.py to generate a JSON report detailing your system's compute capacity and advice on resource-aware processing.

Frequently Asked Questions about get-available-resources

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

FAQPage Schema
How do I detect system resources for scientific computing before running simulations?▼

You can detect system resources for scientific computing by executing a Python script using psutil and subprocess to generate a JSON report detailing CPU, GPU, memory, and disk capacity. This identifies available hardware to optimize workload distribution.

What is the best way to check GPU availability and memory info for machine learning tasks?▼

Checking GPU availability and memory info involves running a resource detection script that scans hardware configurations. It outputs strategic recommendations for GPU utilization and memory management tailored to your specific machine learning tasks.

Can I use Python and psutil to align large-scale data analysis with hardware capabilities?▼

Yes, you can use Python and psutil to align large-scale data analysis with hardware capabilities. The script gathers detailed resource information to help optimize computational workflows and prevent resource bottlenecks.

Does this resource detection approach provide guidance on parallel processing?▼

Yes, the resource detection approach provides strategic recommendations on parallel processing. By understanding your detected system resources, you receive guidance to optimize workload distribution and hardware utilization for scientific tasks.

What limitations should I consider when using subprocess to gather system resources?▼

When using subprocess and psutil to gather system resources, limitations include dependency on local hardware configurations and Python environments. It strictly detects available capacity but does not dynamically allocate resources during runtime.

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