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get-available-resources

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

Updated Jan 10, 2026
Search Tags:#performance#optimization#resources#memory#gpu#cpu#disk
One-click install
npx skills add https://github.com/robinbarvaag/poynt --skill get-available-resources-robinbarvaag
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: get-available-resources
Source: https://github.com/robinbarvaag/poynt/tree/main/.github/skills/get-available-resources
Command: npx skills add https://github.com/robinbarvaag/poynt --skill get-available-resources-robinbarvaag

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps you understand and leverage your available computational resources (CPU, GPU, memory, disk) to make informed decisions about how to run your scientific tasks efficiently.

Core Features & Use Cases

  • Resource Detection: Automatically detects CPU cores, GPU availability (NVIDIA, AMD, Apple Silicon), RAM, and disk space.
  • Strategic Recommendations: Provides tailored advice on whether to use parallel processing, GPU acceleration, out-of-core computing, or memory-efficient strategies.
  • Use Case: Before starting a large data analysis or model training, run this Skill to determine the optimal number of parallel workers or if you can leverage your GPU.

Quick Start

Run the resource detection script to generate a JSON file with system resource information 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 detect available CPU, GPU, memory, and disk space for parallel processing?▼

Detect available CPU, GPU, memory, and disk space by running the resource detection script to generate a JSON file with system information and tailored parallel processing recommendations.

Can I use this resource detection tool with Apple Silicon, AMD, and NVIDIA GPUs?▼

Yes, resource detection supports NVIDIA, AMD, and Apple Silicon GPUs across macOS, Linux, and Windows platforms to provide strategic GPU acceleration recommendations.

What's the best way to determine if I need out-of-core computing for my data analysis?▼

Determine if you need out-of-core computing by reviewing the generated strategic recommendations, which analyze your detected memory and disk space against your computational approach requirements.

How do I check system resources before starting large model training tasks?▼

Check system resources before large model training by running the detection script to evaluate CPU cores, RAM, and GPU availability, enabling you to set optimal parallel worker counts.

Does the resource detection script require any specific Python dependencies to work?▼

Yes, the resource detection script requires the psutil Python dependency to accurately detect and report available system resources like CPU, memory, and disk space.

Why should I analyze available memory and disk space before running computational tasks?▼

Analyzing available memory and disk space helps you decide between memory-efficient strategies, out-of-core computing, or parallel processing, preventing system overload during large computational tasks.

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