get-available-resources
This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.
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Excerpt from the author’s documentation
Extracted from a fixed version of SKILL.md in its original language. This is the author’s documentation; installation, compatibility and runtime results have not been verified by this site.
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Topics in the source
- Get Available Resources
- Overview
- When to Use This Skill
- How This Skill Works
- Resource Detection
- Output Format
- Strategic Recommendations
- Usage Instructions
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. 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 "Process 10,000 files in parallel" → Use this skill to determine optimal worker count "Run a computationa
This is an excerpt. Refer to the complete source and its current requirements.
- Source repository
- davila7/claude-code-templates
- Source file
- cli-tool/components/skills/scientific/get-available-resources/SKILL.md
- Fixed revision
- 21be197f100a12b8d0dd9a211cc244c8179f84d3
Sources and evidence
This record was collected automatically. Its documentation, suitability and runtime behavior have not been manually verified.
Author: davila7/claude-code-templates · original repository metadata. Documentation review: Not reviewed. Last source check: 2026-11-09T15:01:40.088Z.
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License and attribution
MIT. Third-party content and copyright remain with their authors. Refer to the original license and terms.
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