Agent skill · DevOps & Cloud

holoscan-install-container

Install Holoscan SDK via the NGC Docker container. Use for container-based installs; not for native apt/pip/Conda installs.

NVIDIAgithub.com/NVIDIAGitHub ↗
claude-codecodexApache-2.0
Install
npx skills add NVIDIA/skills --skill holoscan-install-container --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 5
SKILL.md size: 7 KB
Bundled scripts: none
Version: 1.0.0
Declared author: Holoscan Team <holoscan-team@nvidia.com>
Path: skills/holoscan-install-container/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,789
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Holoscan NGC Container Installation ## Purpose Pull and verify the official Holoscan SDK container from NGC (`nvcr.io/nvidia/clara-holoscan/holoscan`), selecting the right CUDA/arch tag for the host GPU and validating with the bundled Python and C++ examples. ## Prerequisites - Linux host with an NVIDIA GPU and a working driver (`nvidia-smi`). - Docker installed and the user in the `docker` grou

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About this skill
What does the holoscan-install-container skill do?

Install Holoscan SDK via the NGC Docker container. Use for container-based installs; not for native apt/pip/Conda installs.

How do I install it?

Run `npx skills add NVIDIA/skills --skill holoscan-install-container --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From NVIDIA/skills, a repository with 2,789 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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