Get Available Resources
技能 已验证 活跃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.
To proactively identify available system resources and provide strategic recommendations that inform optimal computational approaches for intensive scientific tasks.
功能
- Detects CPU cores, frequency, and architecture
- Detects NVIDIA, AMD, and Apple Silicon GPUs with backend support
- Reports total, available, and used memory and swap space
- Reports total, available, and used disk space
- Generates JSON output with resource information and strategic recommendations
- Provides guidance on parallel processing, memory management, GPU acceleration, and data handling
使用场景
- Before running large-scale data analysis to determine appropriate processing strategies (e.g., Dask, Zarr)
- Before training machine learning models to identify optimal GPU backends and resource allocation
- Before parallel processing tasks to suggest the number of worker processes
- Before large file operations to verify sufficient disk space
非目标
- Monitoring system resources in real-time
- Providing benchmarks for specific software performance
- Automatically reconfiguring system settings
安装
npx skills add K-Dense-AI/claude-scientific-skills通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。
质量评分
已验证类似扩展
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