Agent skill · Data & Analytics

physical-ai-video-data-augmentation

Use when running video data augmentation and auto-labeling workflows on OSMO: flow selection, preflight, submit-time interpolation, monitoring, and output retrieval. Trigger keywords: video data augmentation, data enrichment, auto labeling, VDA demo, OSMO workflow, pseudo labeling.

NVIDIAgithub.com/NVIDIAGitHub ↗
claude-codecodexships scriptsApache-2.0
Install
npx skills add NVIDIA/skills --skill physical-ai-video-data-augmentation --agent claude-code

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

Facts
Files in the skill folder: 75
SKILL.md size: 19 KB
Bundled scripts: yes
Version: 1.0.0
Declared author: NVIDIA
Path: skills/physical-ai-video-data-augmentation/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

# Physical AI Video Data Augmentation Workflow Orchestrator Default workflow skill for VDA execution on OSMO. It owns flow selection, preflight, cache readiness, inference-path decisions, submit-time interpolation, monitoring, and output retrieval. Component skills are consult-only. ## Purpose Run the end-to-end VDA workflow safely and reproducibly from preflight to output download. Do NOT use thi

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About this skill
What does the physical-ai-video-data-augmentation skill do?

Use when running video data augmentation and auto-labeling workflows on OSMO: flow selection, preflight, submit-time interpolation, monitoring, and output retrieval. Trigger keywords: video data augmentation, data enrichment, auto labeling, VDA demo, OSMO workflow, pseudo labeling.

How do I install it?

Run `npx skills add NVIDIA/skills --skill physical-ai-video-data-augmentation --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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