Agent skill · Data & Analytics

i4h-workflow-dataset-mimic

Expand an HDF5 recording by cloning trajectories with action/state noise. Use when asked to mimic, expand, or augment a dataset; not for recording new demos (use [[i4h-workflow-dataset-teleop]]).

NVIDIAgithub.com/NVIDIAGitHub ↗
claude-codecodexApache-2.0
Install
npx skills add NVIDIA/skills --skill i4h-workflow-dataset-mimic --agent claude-code

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

Facts
Files in the skill folder: 5
SKILL.md size: 6 KB
Bundled scripts: none
Version: 0.6.0
Declared author: Isaac for Healthcare Team <isaac-for-healthcare-support@nvidia.com>
Path: skills/i4h-workflow-dataset-mimic/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

# i4h Workflow — Mimic Dataset ## Purpose Expand an HDF5 recording by replicating trajectories with small action and state noise. Use when the user asks to mimic, expand, or augment a dataset without recording new episodes. If the same prompt also asks to visualize the dataset, finish mimic first, then compose [[i4h-workflow-dataset-convert]] and [[i4h-lerobot-viz]] on the mimic output. ## Base Co

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About this skill
What does the i4h-workflow-dataset-mimic skill do?

Expand an HDF5 recording by cloning trajectories with action/state noise. Use when asked to mimic, expand, or augment a dataset; not for recording new demos (use [[i4h-workflow-dataset-teleop]]).

How do I install it?

Run `npx skills add NVIDIA/skills --skill i4h-workflow-dataset-mimic --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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