Agent skill · software engineering · nvidia
holoscan-install-container
Install and verify the Holoscan SDK 5.x CUDA 13 development container after checking release availability and host compatibility.
Why this skill is useful
Provides specific commands and configurations for installing and validating the Holoscan SDK via Docker, which the AI wouldn't reliably generate on its own.
What it needs
Requires docker, nvidia-container-toolkit installed locally. About 3k tokens when loaded. Last updated 2026-08-07. 2,816 stars on the source repository.
What this skill does
Holoscan 5.x Development Container 1. Check the release and platform This skill targets Holoscan SDK 5.x. Select the requested 5.x release before choosing artifacts. Read its release notes and the matching SDK installation guide. Select the 5.x documentation version; an unversioned page may describe 4.x. For an unreleased checkout, use its docs/sdkinstallation.mdx and DEVELOP.md. Early Access binary commands describe planned artifacts, so confirm publication for the exact release before installing. If unavailable, explain that status and offer holoscan-install-source; keep the requested 5.x version. The 5.0 artifact set targets CUDA 13 and dGPU systems on x8664 or arm64. Native packages use Ubuntu 24.04; wheels use glibc 2.39 and regular CPython 3.12–3.14. Check the selected release for changes to that matrix. There is no CUDA 12 variant or separate Tegra/iGPU artifact in this set. A driver reporting CUDA 12 support needs a compatibility assessment or driver upgrade before a CUDA 13 installation; the nvidia-smi CUDA field is a driver capability, not the installed toolkit version. Never infer compatibility from that field alone. 2. Select and pull the image Inspect Linux architecture, GPU model, driver, Docker, and NVIDIA Container Toolkit. The planned image is one multi-architecture amd64/arm64 dGPU image: nvcr.io/nvidia/clara-holoscan/holoscan:v<SDKVERSION>-cuda13. Check the NGC catalog and release notes for the exact published tag and supported host. There are no cuda12-dgpu or cuda12-igpu tags for this 5.x workflow. GPU passthrough tests may pull an image; explain the download before running one if needed. Use the exact published tag within the installation scope the user authorized. When the method and release are already selected, proceed with that choice. Ask only when a missing release or host fact prevents safe selection. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/holoscan-install-container