get-available-resources

Detect CPU, GPU, memory, and disk resources and generate computational strategy recommendations.

557|98|Updated Nov 7, 2025
One-click install
npx skills add https://github.com/jimmc414/Kosmos --skill get-available-resources-jimmc414
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: get-available-resources
Source: https://github.com/jimmc414/Kosmos/tree/main/kosmos-claude-scientific-skills/scientific-skills/get-available-resources
Command: npx skills add https://github.com/jimmc414/Kosmos --skill get-available-resources-jimmc414

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps users understand their available computational resources (CPU, GPU, memory, disk) to make informed decisions about how to run computationally intensive tasks efficiently.

Core Features & Use Cases

  • Resource Detection: Automatically identifies CPU cores, GPU availability (NVIDIA, AMD, Apple Silicon), RAM, and disk space.
  • Strategic Recommendations: Provides actionable advice on using parallel processing, memory-efficient strategies, and GPU acceleration.
  • Use Case: Before training a large machine learning model, use this Skill to determine if a GPU is available and how many CPU cores can be used for data preprocessing.

Quick Start

Run the resource detection script to generate a JSON file with system insights and recommendations.

Frequently Asked Questions about get-available-resources

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

FAQPage Schema
How do I check available CPU, GPU, memory, and disk resources before running intensive compute tasks?

To check available system resources like CPU, GPU, memory, and disk space, you can use a detection script that leverages psutil to generate a JSON report with current hardware availability and insights.

How do I know if my system supports GPU acceleration for machine learning?

Detecting GPU availability for acceleration involves scanning your system for NVIDIA, AMD, or Apple Silicon GPUs. This resource detection process reports available hardware so you can confirm GPU support for machine learning.

What's the best way to determine if I should use parallel processing or out-of-core computing?

Determining whether to use parallel processing or out-of-core computing requires analyzing your available CPU cores and memory. A resource detection script provides strategic recommendations based on your specific system constraints.

Does the resource detection script require psutil to retrieve system information?

Yes, the resource detection script requires psutil to retrieve system information. This dependency is necessary to accurately detect available CPU cores, RAM, and disk space for generating computational recommendations.

Can I detect available RAM and disk space to decide on memory-efficient strategies?

You can detect available RAM and disk space to inform memory-efficient strategies. The detection script reports current memory and disk metrics, helping you decide if out-of-core computing is needed for large datasets.