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get-available-resources

Detect CPU, GPU, memory, and disk resources and output a .claude_resources.json with usage guidance.

15|2|Updated Dec 17, 2025
Search Tags:#memory#gpu#cpu#parallel-processing#disk-space#resource-detection#system-resources
One-click install
npx skills add https://github.com/rubensliv/k-dense-ai --skill get-available-resources-rubensliv
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: get-available-resources
Source: https://github.com/rubensliv/k-dense-ai/tree/main/scientific-skills/get-available-resources
Command: npx skills add https://github.com/rubensliv/k-dense-ai --skill get-available-resources-rubensliv

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Detects and reports available system resources to inform computational decisions at task start.

Core Features & Use Cases

  • Resource detection: CPU, GPU, memory, and disk space.
  • Output: generates a .claude_resources.json with recommendations for parallel processing, memory strategies, and GPU usage.
  • Use Case: Before training models or processing large datasets, run this to tailor your compute plan.

Quick Start

Run this at the start of any computational task to detect system resources and generate a .claude_resources.json with practical guidance for parallelism, memory, and GPU usage.

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 like CPU, GPU, and memory before running data analysis?▼

You can detect system resources such as CPU, GPU, memory, and disk space by running a resource detection script. This process scans your hardware and generates a .claude_resources.json file containing specific hardware metrics and usage guidance.

What is the best way to check available disk space and GPU availability for parallel processing?▼

Checking available disk space and GPU availability for parallel processing involves querying system hardware metrics. The detection process outputs a JSON file with tailored recommendations for parallelism, memory strategy, and GPU usage.

Does psutil support detecting GPU resources for large-file processing tasks?▼

Psutil primarily detects CPU, memory, and disk space resources. The Skill extends system resource detection to include GPU metrics, generating a comprehensive JSON profile to guide large-file processing and model training.

How do I generate a compute plan for model training based on available memory and CPU?▼

Generating a compute plan for model training requires detecting available memory and CPU metrics first. The detection script outputs a JSON file with actionable recommendations for memory strategy and parallel processing tailored to your hardware.

Can I use system resource detection to guide memory strategy and GPU usage?▼

Yes, system resource detection guides memory strategy and GPU usage by profiling your hardware. It generates a .claude_resources.json file that provides specific recommendations for parallel processing and memory allocation based on detected capabilities.

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