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HaykTarkhanyan
HaykTarkhanyanCOMMUNITY
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get-available-resources

Detect CPU, GPU, memory, and disk resources and generate a structured JSON report.

Updated Mar 31, 2026
Search Tags:#resources#memory#detection#gpu#cpu#system#disk
One-click install
npx skills add https://github.com/HaykTarkhanyan/dst_research --skill get-available-resources-hayktarkhanyan
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: get-available-resources
Source: https://github.com/HaykTarkhanyan/dst_research/tree/main/.claude/skills/get-available-resources
Command: npx skills add https://github.com/HaykTarkhanyan/dst_research --skill get-available-resources-hayktarkhanyan

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

The skill detects CPU, GPU, memory, and disk resources and generates a JSON report with recommendations to guide computational strategies for analytics, modeling, and large-data tasks.

Core Features & Use Cases

  • Resource discovery across CPU cores, GPUs (NVIDIA, AMD, Apple Silicon), memory, disk space, and OS details.
  • Output a .claude_resources.json file containing both resource metrics and structured recommendations for parallelism, memory strategies, and GPU usage.
  • Use at project initialization or before heavy analyses to calibrate processing strategies and tool choices.

Quick Start

Run the resource detector to produce a .claude_resources.json file summarizing your system and recommended strategies.

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 to guide compute decisions?▼

To detect system resources, this skill runs a Python script using psutil to discover CPU cores, GPUs, memory, and disk space, outputting a .claude_resources.json file with structured recommendations for parallelism and memory strategies.

When should I check available system resources before running heavy analyses or large-data tasks?▼

You should check available system resources at project initialization or before heavy analyses to calibrate processing strategies, determine parallelism, select memory strategies, and evaluate GPU usage for computational tasks.

Does the system resource detection script support NVIDIA, AMD, and Apple Silicon GPUs?▼

Yes, the system resource detection script supports GPU discovery across NVIDIA, AMD, and Apple Silicon, alongside CPU cores, memory, disk space, and OS details, generating a JSON report to guide computational strategies.

Can I customize the output file path and verbosity when detecting system resources?▼

Yes, you can customize the output when detecting system resources by using optional CLI arguments supported by the detect_resources.py script, allowing you to specify the output file path and control verbosity levels.

Do I need Python and psutil installed to generate a system resource report?▼

Yes, you need Python and the psutil dependency installed to run the resource detection script, which discovers hardware metrics and outputs a structured JSON file containing computational recommendations.

What is the best way to evaluate disk space and OS details for computational modeling?▼

The best way to evaluate disk space and OS details is running this resource detection script, which discovers system metrics and generates a JSON report with structured recommendations for disk considerations and computational modeling.

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