Agent skill · software engineering · nvidia
holoscan-setup
Assess a host and choose a Holoscan SDK 5.x installation method using release availability, CUDA 13 compatibility, and component needs.
Why this skill is useful
Adds executable scripts for checking Conda and NGC image availability that automate the installation process for the Holoscan SDK.
What it needs
Requires docker, nvidia-container-toolkit, python installed locally. About 2k tokens when loaded. Last updated 2026-08-07. 2,816 stars on the source repository.
What this skill does
Holoscan 5.x Setup Establish the target Determine the requested 5.x release or source branch and whether the user needs C++, Python, specific modules, or SDK development. Read the release notes and SDK installation guide with the matching 5.x version selected. An unversioned page may describe 4.x; for a development checkout use its docs/sdkinstallation.mdx and DEVELOP.md. Treat Early Access binary methods as tentative until the exact artifacts are confirmed published. Package-name registration alone is not availability. Inspect and assess Use read-only checks on the intended Linux host: Report unavailable tools separately from incompatible hardware. Inspect an existing venv or SDK checkout only at user-selected or relevant known paths. Use python -m pip list in the intended environment and dpkg-query -W 'holoscan' on Debian systems to distinguish 4.x installations from usable 5.x ones. A GPU passthrough check that runs/pulls an image is a separate execution step; a Docker version check alone does not establish passthrough. The 5.0 baseline is CUDA 13 with dGPU support, Ubuntu 24.04 native packages, and x8664/SBSA arm64. Wheels require glibc 2.39 and regular CPython 3.12–3.14. The nvidia-smi CUDA value describes driver capability, not toolkit presence. Check driver/runtime compatibility for the selected artifact; a CUDA 12-only host cannot be routed to a nonexistent 5.x CUDA 12 package. ARM64 does not establish Tegra/iGPU support. Confirm hardware-specific support before offering installation on Jetson, IGX, DGX Spark, or Grace systems. To check an already-pulled image, run the bundled helper from this skill's installation directory with the full confirmed 5.x tag, for example: It inspects the local image only, makes no registry request, and does not prove publication, GPU passthrough, or runtime success. Report its result accordingly. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/holoscan-setup