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get-available-resources

Detect CPU, GPU, memory, and disk resources and generate a .claude_resources.json report.

33.0k|3.2k|Updated Oct 19, 2025
Search Tags:#memory#gpu#cpu#disk#resource-detection#out-of-core#system-resources
One-click install
npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill get-available-resources-k-dense-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: get-available-resources
Source: https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/scientific-skills/get-available-resources
Command: npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill get-available-resources-k-dense-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill detects CPU, GPU, memory, and disk resources on the host and generates a .claude_resources.json file with strategic recommendations to guide computational choices (parallelism, out-of-core processing, GPU usage, and memory strategies).

Core Features & Use Cases

  • Resource discovery: detect CPU cores, GPU availability, RAM, and disk space.
  • Output and guidance: writes .claude_resources.json and provides recommendations for parallel processing, memory strategies, GPU acceleration, and large-data handling.
  • Use Case: Use before data analyses, model training, or large simulations to inform architecture and tooling choices.

Quick Start

Run the resource detection script to generate the resource report for your machine.

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 before running heavy computations or model training?▼

System resource detection involves scanning CPU cores, GPU availability, RAM, and disk space to generate a decision-ready report. This skill provides recommendations for parallelism, out-of-core processing, and memory strategies before heavy computation.

When do I need to check CPU and GPU availability for data analysis workflows?▼

Checking CPU and GPU availability is necessary when planning data analysis, model training, or large-scale simulations. It informs architecture choices regarding GPU acceleration, parallel processing, and out-of-core data handling.

Can I use this resource detection tool on macOS, Linux, and Windows?▼

Yes, resource detection works across macOS, Linux, and Windows. It requires the psutil Python dependency to probe system hardware and generate a resource report for your specific operating system environment.

What is the best way to determine if out-of-core processing is needed for large datasets?▼

The best way to determine if out-of-core processing is needed is to compare available RAM against dataset size. This skill detects memory and generates recommendations on whether to adopt out-of-core data handling strategies.

Does this resource detection script require any specific Python dependencies?▼

Yes, the resource detection script requires the psutil Python dependency. It uses psutil to accurately query system hardware metrics and write the results into a .claude_resources.json file.

What format does the system resource report use to provide computation recommendations?▼

The system resource report uses a .claude_resources.json file format. This file contains detected hardware specifications alongside strategic recommendations for parallelism, GPU usage, and memory strategies to guide compute tasks.

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