Agent skill · NVIDIA

cupynumeric-install

Install and verify cuPyNumeric for Python — requirements, commands, verification. Source builds are out of scope.

What it needs

About 4k tokens when loaded.

What this skill does

cuPyNumeric Install (user) Purpose Use this skill to install cuPyNumeric for use from Python and to verify the install actually works (including GPU usage). Apply it whenever a user wants cuPyNumeric running via conda or pip. Do not use it to build from source (to modify or contribute) — that is out of scope. Mandatory rules Never run installs. Do not run pip install, conda install, or any installer. Print the command; let the user run it. Always isolate. No installs into base conda, system Python, or shared global envs. Detect before recommending. Read-only --version checks are fine. Prerequisites Confirm these system requirements before recommending any install: GPU: Compute Capability ≥ 7.0 (Volta+). CPU-only also supported. CUDA: 12.2+. OS: Linux (x8664 / aarch64), Windows via WSL. Python: 3.11 through 3.14 conda: ≥ 24.1 (conda path only). Package manager: conda (upstream-recommended) or pip. If neither is present, bootstrap one first (see Instructions). Instructions Follow these steps in order: confirm the prerequisites, ask the scoping questions, install via the chosen path, then verify. Ask before installing 1. Package manager? Check conda --version and pip --version. Prefer conda (upstream-recommended); fall back to pip. 1. Env target? GPU machine, CPU-only laptop, cloud, container, or remote/server. 1. CUDA version? Ask only when forcing the GPU variant on a host without a visible GPU. Check with nvidia-smi / nvcc --version. Bootstrap — install a package manager first If neither conda nor pip is available, install one. Provide the command and the docs link; do not run it. Recommended: Miniforge (full conda, conda-forge default) Docs: https://github.com/conda-forge/miniforge Alternative: Python + pip Install Python from your OS package manager (apt/dnf/brew) or https://www.python.org/downloads/. If pip is missing on an existing Python: python -m ensurepip --upgrade. After installing, open a new shell so the binary is on PATH. …

How to use it

Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:

@skills NVIDIA/cupynumeric-install

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