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get-available-resources

Detect CPU, GPU, memory, and disk resources and recommend computational strategies.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps users understand and leverage their available computational resources (CPU, GPU, memory, disk) to make informed decisions about how to run complex scientific 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, GPU acceleration, and large data handling.
  • Use Case: Before starting a large-scale data analysis, run this skill to determine if you can use multi-processing, if you need Dask for out-of-core computation, or if a GPU is available for faster model training.

Quick Start

Run the resource detection script to get a JSON report of your system's capabilities.

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, and memory resources before running a computational task?▼

You can detect available system resources by running a Python script that uses psutil to identify CPU cores, GPU availability, RAM, and disk space, returning a JSON report of your system's capabilities.

What is the best way to determine if my system supports GPU acceleration for model training?▼

To determine GPU acceleration support, run a resource detection script that automatically identifies GPU availability across NVIDIA, AMD, and Apple Silicon architectures, providing actionable hardware acceleration recommendations.

Can I use psutil to generate recommendations for parallel processing and out-of-core computing?▼

Yes, psutil gathers system information on CPU cores and memory, which the script uses to generate strategic recommendations for parallel processing, out-of-core computing with Dask, and GPU acceleration based on your hardware.

Do I need to install any dependencies to detect disk space and available memory?▼

You need to install the psutil Python library to detect disk space and available memory, as the script relies on this dependency to gather and report system resource information.

When should I use out-of-core computing strategies for large-scale data analysis?▼

You should use out-of-core computing strategies when the resource detection script reports insufficient RAM for your dataset, prompting strategic recommendations to handle large data that exceeds available memory.

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