get-available-resources
Get Available Resources
Overview
Detect available computational resources and generate strategic recommendations for scientific computing tasks. This skill automatically identifies CPU capabilities, GPU availability (NVIDIA CUDA, AMD ROCm, Apple Silicon Metal), memory constraints, and disk space to help make informed decisions about computational approaches.
When to Use This Skill
Use this skill proactively before any computationally intensive task:
- Before data analysis: Determine if datasets can be loaded into memory or require out-of-core processing
- Before model training: Check if GPU acceleration is available and which backend to use
- Before parallel processing: Identify optimal number of workers for joblib, multiprocessing, or Dask
- Before large file operations: Verify sufficient disk space and appropriate storage strategies
- At project initialization: Understand baseline capabilities for making architectural decisions
Example scenarios:
- "Help me analyze this 50GB genomics dataset" → Use this skill first to determine if Dask/Zarr are needed
- "Train a neural network on this data" → Use this skill to detect available GPUs and backends
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