Agent skill

jetson-package

Pick Jetson-compatible containers, vLLM runtime images, and Jetson AI Lab PyPI indexes; maps Orin SM 8.7 vs Thor SM 11.0 and JetPack-specific package choices.

NVIDIAgithub.com/NVIDIAGitHub ↗
claude-codecodexships scriptsApache-2.0
Install
npx skills add NVIDIA/skills --skill jetson-package --agent claude-code

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

Facts
Files in the skill folder: 8
SKILL.md size: 7 KB
Bundled scripts: yes
Version: 0.0.1
Declared author: Jetson Team
Path: skills/jetson-package/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

# Jetson Package & Environment Agents often suggest `docker pull` images or `pip install` wheels that claim **aarch64** support but were never built for Jetson’s GPU **streaming multiprocessor (SM)** targets. On Jetson, **default to NVIDIA-curated artifacts** unless the user explicitly opts out. ## Purpose Choose Jetson-compatible containers and Python package indexes before installing GPU-native

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About this skill
What does the jetson-package skill do?

Pick Jetson-compatible containers, vLLM runtime images, and Jetson AI Lab PyPI indexes; maps Orin SM 8.7 vs Thor SM 11.0 and JetPack-specific package choices.

How do I install it?

Run `npx skills add NVIDIA/skills --skill jetson-package --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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