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Skillv1.0.0

i4h-workflow-validate

Run the root-level workflow runtime policy or rule-based rollouts and verify simulator success. Use for evaluation, checkpoints, or local controllers; do not use for replay or dataset annotation.

by nvidia(0) 0 installs
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About

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

Validate a Workflow

Purpose

Run the selected workflow run mode through the unified launcher, inspect the completed recording, and report simulator success.

Instructions

  1. Resolve the base checkout and a live workflow run mode.
  2. Run the unified launcher in the foreground.
  3. Require the final episode success summary.
  4. Inspect visible behavior and every rollout artifact.

Resolve live support

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"
./run.sh list

Treat the resolver above 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.

Treat ./run.sh list output as the complete authoritative workflow-by-mode table; it is dependency-light and faster than scanning workflow modules. Do not duplicate that mutable table in this skill. Map the user's natural name to a listed workflow id, then choose only a mode shown on that same line:

User intent Required live mode Launcher argument
Ordinary learned-policy evaluation policy --policy
Requested or only available local controller rule-based --rule-based
Explicit named alternative such as N1.7 matching listed mode such as policy_n17 --mode <name>

Inspect ./run.sh show <workflow> --mode <mode>, the workflow module, Scene manifest, and selected Task manifest when model, prompt, checkpoint, goal, or step-cap behavior matters.

Use precise readiness language:

  • Structurally valid: show, per-mode lint, and lint --all pass.
  • Launchable: the selected simulator mode starts and every required backend/checkpoint preloads.
  • Rollout-validated: the requested episodes complete and the recorded success evidence passes inspection.

Do not report “validated” without stating which level was actually reached.

Foreground execution rule

Keep run.sh as this agent's foreground tool call. Do not use a subagent, monitor task, shell backgrounding, nohup, tmux, or a detached process. Poll a yielded session until exit and inspect the final episode summary before responding. When the selected Task is remote, the policy backend subprocess internally owned by run.sh is expected; a simulator-compatible exported RSL-RL Task runs in-process.

Run visibly by default. If the user explicitly requests headless execution, or a documented environment constraint makes it necessary, say so before launch and include --headless; never switch to headless silently.

Policy:

./run.sh <workflow> --policy \
  --episodes <N> --attempts 3 \
  --record verify.hdf5

Rule-based:

./run.sh <workflow> --rule-based \
  --episodes <N> --attempts 3 \
  --record verify.hdf5

The launcher creates a unique canonical run directory and anchors the relative verify.hdf5 inside it. Resolve RUN_DIR from the ==> run dir ... line or machine-readable run.json; do not recreate the launcher's timestamp. Use --run-dir "$RUN_DIR" only when a caller-selected location must be shared with another stage; the launcher creates it. Absolute recording paths remain supported.

For another declared mode, use --mode <name>. For a supplied/new checkpoint, resolve its exact path, confirm it belongs to the selected policy Task, and pass --checkpoint /absolute/path; an exported RSL-RL Task expects its TorchScript policy.pt, while a remote Task expects the owning backend's loadable checkpoint format. For “300 timesteps,” pass --episode-steps 300.

Never raise the Scene manifest's cap. --episode-steps may only lower it. Remote inference waits do not consume simulation steps. Use a unique --namespace when another run of the same workflow is active.

Verify

Require exit status 0 and final N/N episodes succeeded. A failed attempt followed by a successful retry counts as a successful requested episode; report attempts and retries.

RUN_DIR="<absolute run_dir from run.json or launcher output>"
uv run --project tools/dataset i4h-dataset inspect "$RUN_DIR/verify.hdf5" --segments

Inspect episode metadata, action/state widths, camera frames, node segments, and success flags. For visible runs, observe Scene/camera behavior and final task outcome. On failure, use the first actionable backend, contract, graph, or simulator error; never switch modes or increase the cap silently. Run ./stop.sh all after crashes that leave processes.

For a success rule that excludes collision, inspect the owning contact-sensor configuration and require a forced-contact negative test at least once after authoring or changing that rule. A sensor that initializes but has never produced a non-zero filtered force does not establish collision rejection.

Troubleshooting

Use the first actionable backend, graph, contract, or simulator error. Retry within the same mode and cap only after correcting it.

Prerequisites

Require synced simulator assets and any backend/checkpoint declared by the selected run mode.

Limitations

Only modes from run.sh list are supported, and a runtime step override may lower but never raise the validated Scene cap.

Examples

  • Evaluate scissor pick and place for 2 episodes. → run policy mode for two successful episodes, record, inspect, and report attempts plus visible outcome.
  • Run surgical_reach_psm in rule-based mode for 1 episode. → use only the declared local-controller mode.

Completion gate

Report workflow, mode, model/checkpoint source, requested successes, attempts/retries, completion steps, visible outcome, HDF5 path and inspection, final exit status, and first unresolved failure if any.

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-validate/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-validate.ocm.jsonjson
{
  "ocm": "1",
  "id": "nvidia-skills-i4h-workflow-validate",
  "kind": "skill",
  "name": "i4h-workflow-validate",
  "description": "Run the root-level workflow runtime policy or rule-based rollouts and verify simulator success. Use for evaluation, checkpoints, or local controllers; do not use for replay or dataset annotation.",
  "publisher": "nvidia",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "data_analysis"
    ],
    "tags": [
      "skill-md",
      "isaac-for-healthcare",
      "i4h",
      "simulation",
      "evaluation",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Run the root-level workflow runtime policy or rule-based rollouts and verify simulator success. Use for evaluation, checkpoints, or local controllers; do not use for replay or dataset annotation."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/nvidia/skills",
      "path": "skills/i4h-workflow-validate/SKILL.md",
      "ref": "HEAD",
      "url": "https://github.com/nvidia/skills/blob/HEAD/skills/i4h-workflow-validate/SKILL.md",
      "key": "nvidia/skills/skills/i4h-workflow-validate/SKILL.md"
    },
    "license": "Apache-2.0"
  },
  "instructions": "# Validate a Workflow\n\n## Purpose\n\nRun the selected workflow run mode through the unified launcher, inspect the completed recording, and report simulator success.\n\n## Instructions\n\n1. Resolve the base checkout and a live workflow run mode.\n2. Run the unified launcher in the foreground.\n3. Require the final episode success summary.\n4. Inspect visible behavior and every rollout artifact.\n\n## Resolve live support\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_NAM",
  "cost": {
    "context_tokens": 1638
  }
}

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

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