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I4h Workflow Dataset Mimic

NVIDIAOfficialCreated by Isaac for Healthcare TeamDistributed by NVIDIA

  • Skill
  • Workflow
  • Data and AI
  • Apache-2.0
  • Medium risk
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From the author

Expand workflow HDF5 demonstrations with action jitter, optionally scoped to node segments. Use for synthetic variants; do not use to collect data, alter state directly, or generate new images.
— the description by Isaac for Healthcare Team

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured workflow for augmenting existing HDF5 demonstration datasets used in healthcare robotics workflows. It enables users to create synthetic variants of successful episodes by applying controlled action jitter, which can be scoped to specific node segments. The process involves inspecting source data, generating new episodes with configurable noise levels, and verifying the integrity of the resulting dataset.

What it does

  • Inspects HDF5 demonstration files to identify successful episodes and segments.
  • Generates synthetic dataset variants by applying action jitter to source demonstrations.
  • Supports node-scoped jitter application for targeted data augmentation.
  • Verifies generated datasets for consistency in dimensions and success flags.
  • Integrates with visualization tools for post-generation review.

When to use it

  • When you need to increase the volume of demonstration data for training models.
  • When you want to introduce controlled variability into existing successful robot episodes.
  • When you need to test model robustness by adding noise to specific action nodes.
  • When preparing datasets for further visualization or analysis workflows.

Advantages

  • Automates the creation of synthetic training data from existing successful runs.
  • Allows for precise control over noise levels and random seeds.
  • Supports targeted augmentation via node-specific segment scoping.
  • Includes built-in verification steps to ensure data integrity.

Usage examples

“Mimic 3 more episodes and visualize my dataset.”
The agent generates three synthetic variants of the source HDF5 file with action jitter, verifies the output, converts the data, and launches the LeRobot visualizer.
“Create 10 new episodes from my source file with 0.05 noise.”
The agent creates 10 additional episodes in a new directory using the specified noise level and reports the final dataset counts.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/nvidia/i4h-workflow-dataset-mimic/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip i4h-workflow-dataset-mimic.zip -d .agents/skills

Documentation by Isaac for Healthcare Team

Mimic Workflow Demonstrations

Purpose

Clone successful source episodes and perturb recorded actions.

Instructions

  1. Run the checkout resolver and select the source HDF5.

  2. Inspect successful episodes and segments.

  3. Run mimic to generate the requested additional action-jitter variants.

  4. Compare exact counts and preserved contracts.

Resolve and inspect

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 "$ROOT"
HDF5_PATH=/absolute/path/to/source.hdf5
uv run --project tools/dataset i4h-dataset inspect "$HDF5_PATH" --segments

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.

Use the explicit/current-chain recording. Require at least one successful source episode. If the user asks for node-scoped jitter, require that node in segment metadata.

Expand

RUN_DIR="$(pwd)/runs/<workflow>/$(date +%Y%m%d_%H%M%S)"
mkdir -p "$RUN_DIR"
uv run --project tools/mimic i4h-mimic \
  "$HDF5_PATH" "$RUN_DIR/expanded.hdf5" \
  --episodes <additional-count> \
  --noise 0.01 \
  --seed <seed> \
  --include-source \
  --successful-only

--episodes is the number of generated variants, not the final total. Add --node <node-id> only when requested. Preserve the default deterministic seed unless the user supplies another.

Verify and compose

uv run --project tools/dataset i4h-dataset inspect "$RUN_DIR/expanded.hdf5" --segments

Confirm source count, generated count, dimensions, success flags, and segment preservation. Reject zero generated episodes.

If the same prompt requests visualization, continue with i4h-workflow-dataset-convert, then i4h-lerobot-viz; raw HDF5 is not a LeRobot visualizer input.

Troubleshooting

On failure, inspect the first episode shape or segment error. If a requested node is absent, report available node ids.

Prerequisites

Require a readable HDF5 file with at least one successful episode and valid segments for node-scoped jitter.

Limitations

The current tool does not independently add state noise, rerun physics, or synthesize camera frames.

Examples

  • Mimic 3 more episodes and visualize my dataset. → generate three variants, convert the expanded HDF5, then launch LeRobot visualization.

Completion gate

Report input/output paths, source and generated counts, final total, action-noise value, seed, optional node, limitations, and conversion/visualizer result when requested.

Files

skill.oms.sig

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python, Needs Node.js

Security

What our scanner noticed· Medium risk

  • Large base64-encoded blobs

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Isaac for Healthcare Team
Publisher
NVIDIA (Official)
Distributed by
NVIDIA
Source
NVIDIA/skills · skills/i4h-workflow-dataset-mimic · commit fce3cca
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE-APACHE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download i4h-workflow-dataset-mimic.zip