About

Imported from nvidia/skills (skills/i4h-workflow/SKILL.md). Install upstream with npx skills add nvidia/skills --skill i4h-workflow. Copyright stays with the author (Apache-2.0).

i4h Workflows

Name: i4h-workflow
Author: nvidia

Purpose

Orient the user from live repository facts, then hand execution to the narrowest stage skill.

Instructions

Run the base-checkout resolver.
Read live support and DESIGN.md.
Use only current architecture facts in the answer.
Use the narrowest stage skill for execution.

Resolve the checkout

export I4H_WORKFLOWS_REPO_URL="${I4H_WORKFLOWS_REPO_URL:-https://github.com/isaac-for-healthcare/i4h-workflows}"
I4H_REPO_DIR_NAME="${I4H_WORKFLOWS_REPO_URL%/}"
I4H_REPO_DIR_NAME="${I4H_REPO_DIR_NAME##*/}"
I4H_REPO_DIR_NAME="${I4H_REPO_DIR_NAME##*:}"
I4H_REPO_DIR_NAME="${I4H_REPO_DIR_NAME%.git}"
[ -n "$I4H_REPO_DIR_NAME" ] || { echo "Cannot derive a checkout name from I4H_WORKFLOWS_REPO_URL" >&2; exit 2; }
ROOT="${I4H_WORKFLOWS:-$(git rev-parse --show-toplevel 2>/dev/null)}"
if [ ! -d "$ROOT/workflows/i4h_workflows" ]; then
  ROOT="${I4H_WORKFLOWS:-$HOME/$I4H_REPO_DIR_NAME}"
  [ -d "$ROOT/workflows/i4h_workflows" ] || git clone "$I4H_WORKFLOWS_REPO_URL" "$ROOT"
fi
export I4H_WORKFLOWS="$ROOT"
cd "$ROOT"

Treat this resolver as part of the skill contract: a hosted copy may run outside the base repository, so never assume the current checkout contains workflows/i4h_workflows. I4H_WORKFLOWS_REPO_URL selects the clone source. When I4H_WORKFLOWS is unset, derive the fallback directory from that URL; set I4H_WORKFLOWS only to reuse or choose a specific destination. Never replace an existing checkout.

Inspect before answering

Read ./DESIGN.md for architecture and skills/i4h-workflow/references/repo-map.md for ownership. Discover current support instead of copying a static table:

./run.sh list

If discovery fails because setup is incomplete, report that limitation and route to i4h-workflow-setup.

Explain the design

Keep the summary precise:

A Scene owns the simulated world, assets, embodiment, cameras, randomization, adapters, and reset hooks.
A Task owns one reusable capability. It reads ctx.scene, writes ctx.act, and never advances the simulator.
A Workflow selects one Scene, exposes run-mode-specific TaskGraph builders, and owns goal semantics. A run mode answers how that workflow should run; code and CLI use the shorter term mode.
The Engine schedules graph nodes; the shared SimulationRunner alone resets, steps, renders, records, retries whole episodes, and prints run summaries.
Online RL is a separate training lifecycle: its trainer owns vectorized stepping and returns a checkpoint to the normal policy Task and SimulationRunner validation path.
Simulator-compatible exported RSL-RL actors may run as in-process Tasks; incompatible foundation-model policy stacks remain remote.
Remote policy stacks run out of process and communicate over Zenoh; offline dataset tools remain independent of the simulator.
Python owns behavior. Manifests carry facts across dependency boundaries.

Do not describe retired environment YAMLs, per-mode runners, or separate policy/Arena launchers.

Route the next action

Goal	Skill
Install, sync, or repair dependencies	`i4h-workflow-setup`
Create a new workflow/environment	`i4h-workflow-create`
Edit an existing scene, camera, task, or success rule	`i4h-workflow-scene-edit`
Record demonstrations	`i4h-workflow-dataset-teleop`
Replay HDF5	`i4h-workflow-dataset-replay`
Augment HDF5	`i4h-workflow-dataset-mimic`
Grade/filter HDF5 with a VLM	`i4h-workflow-dataset-annotate`
Convert HDF5 to LeRobot	`i4h-workflow-dataset-convert`
Inspect LeRobot in a browser	`i4h-lerobot-viz`
Fine-tune a manifest-backed policy task	`i4h-workflow-finetune`
RL post-train a supported policy in simulation	`i4h-workflow-train-rl`
Run policy or rule-based rollouts	`i4h-workflow-validate`
Run the maintained complete pipeline	`i4h-workflow-e2e`

For Stop all, do not load a stage skill. Run ./stop.sh all from the repository root and report the stopped process count.

Troubleshooting

If discovery fails, verify the resolved checkout and run setup. If a mode is absent, report it as unsupported.

Prerequisites

Require a readable base checkout or network access to clone it.

Limitations

This router does not install, author, simulate, process data, train, or evaluate.

Examples

What does the i4h workflow include, and where should I start? → inspect live support, summarize DESIGN.md, and recommend one stage skill.

Completion gate

Answer with the live workflow/mode list, a short architecture summary, and one concrete next skill. If the requested workflow or mode is absent from run.sh list, say it is unsupported instead of inventing a command.

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml

targets:
  - https://api.opensmartroute.ai/api/v1/registry/nvidia-skills-i4h-workflow/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

nvidia-skills-i4h-workflow.ocm.jsonjson

{
  "ocm": "1",
  "id": "nvidia-skills-i4h-workflow",
  "kind": "skill",
  "name": "i4h-workflow",
  "description": "Orient users to the i4h workflow runtime and route them to the correct stage skill. Use for architecture, support, or where-to-start questions; do not execute a known stage.",
  "publisher": "nvidia",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "general"
    ],
    "tags": [
      "skill-md",
      "isaac-for-healthcare",
      "i4h",
      "robotics",
      "onboarding",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Orient users to the i4h workflow runtime and route them to the correct stage skill. Use for architecture, support, or where-to-start questions; do not execute a known stage."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/nvidia/skills",
      "path": "skills/i4h-workflow/SKILL.md",
      "ref": "HEAD",
      "url": "https://github.com/nvidia/skills/blob/HEAD/skills/i4h-workflow/SKILL.md",
      "key": "nvidia/skills/skills/i4h-workflow/SKILL.md"
    },
    "license": "Apache-2.0"
  },
  "instructions": "# i4h Workflows\n\n## Purpose\n\nOrient the user from live repository facts, then hand execution to the narrowest stage skill.\n\n## Instructions\n\n1. Run the base-checkout resolver.\n2. Read live support and `DESIGN.md`.\n3. Use only current architecture facts in the answer.\n4. Use the narrowest stage skill for execution.\n\n## Resolve the checkout\n\n```bash\nexport I4H_WORKFLOWS_REPO_URL=\"${I4H_WORKFLOWS_REPO_URL:-https://github.com/isaac-for-healthcare/i4h-workflows}\"\nI4H_REPO_DIR_NAME=\"${I4H_WORKFLOWS_REPO_URL%/}\"\nI4H_REPO_DIR_NAME=\"${I4H_REPO_DIR_NAME##*/}\"\nI4H_REPO_DIR_NAME=\"${I4H_REPO_DIR_NAME##*:}\"",
  "cost": {
    "context_tokens": 1185
  }
}

Fetch it by URL: GET /api/v1/registry/nvidia-skills-i4h-workflow/manifest?version=1.0.0

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