Agent skill · Workflow & Productivity

i4h-workflow-validate

Validate, evaluate, or run i4h envs. Use for policy/checkpoint rollouts and scripted state-machine smoke runs.

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

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

Facts
Files in the skill folder: 5
SKILL.md size: 11 KB
Bundled scripts: none
Version: 0.6.1
Declared author: Isaac for Healthcare Team <isaac-for-healthcare-support@nvidia.com>
Path: skills/i4h-workflow-validate/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 — Validate ## Purpose Roll out a policy or scripted state-machine controller against an env and record verification episodes to an HDF5. Use when the user asks to validate, evaluate, run, or rollout a policy/checkpoint, or asks for surgical state-machine smoke runs. ## Base Code These steps drive the i4h-workflows base code (the `workflows/agentic/` tree). To reuse an existing check

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About this skill
What does the i4h-workflow-validate skill do?

Validate, evaluate, or run i4h envs. Use for policy/checkpoint rollouts and scripted state-machine smoke runs.

How do I install it?

Run `npx skills add NVIDIA/skills --skill i4h-workflow-validate --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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