i4h-workflow-dataset-convert

i4h-workflow-dataset-convert is a skill for Claude Code, Codex from NVIDIA/skills. It costs 43 tokens per session (1,340 once invoked), scanned A, original, Apache-2.0.

A dataset conversion guide for turning HDF5 recordings into LeRobot datasets. HDF5 is a file format for storing structured scientific and machine-learning data; LeRobot is a dataset format and toolset for robot learning.

In plain words
What is it for?
It helps convert HDF5 recordings into parquet data, metadata, and videos using the environment that created them.
Why use it?
It prepares recorded robot demonstrations in the files and videos needed for training or further inspection.

Skill for Claude CodeCodex ✓ vendor

Written for no agent in particular: nothing here depends on one.

Good fit It helps convert HDF5 recordings into parquet data, metadata, and videos using the environment that created them.

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Install with agentmods
npx agentmods add skills/nvidia/skills/i4h-workflow-dataset-convert
About the project

NVIDIA/skills is a catalogue of portable instruction sets that teach coding agents how to use NVIDIA software for robotics, simulation, CUDA, retrieval-augmented generation, and related workflows. Developers install these skills in agents such as Claude Code or Codex, while the catalogue mirrors skills maintained in separate NVIDIA product repositories.

NVIDIA/skills · 3,873 stars · on GitHub · docs.nvidia.com

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add NVIDIA/skills --skill i4h-workflow-dataset-convert
Clone the repo
git clone --depth 1 https://github.com/NVIDIA/skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for i4h-workflow-dataset-convert

README.md
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Your own site
<a href="https://agentmods.dev/skills/nvidia/skills/i4h-workflow-dataset-convert"><img src="https://agentmods.dev/badge/skills/nvidia/skills/i4h-workflow-dataset-convert/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/nvidia/skills/i4h-workflow-dataset-convert"><img src="https://agentmods.dev/badge/skills/nvidia/skills/i4h-workflow-dataset-convert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,340 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00043 $0.01340
Opus 5.5 $0.00017 $0.00536
Sonnet 5.5 $0.00009 $0.00268
Haiku 4.5 $0.00004 $0.00134

Measured 1mo ago against content hash 51cae38f064d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

i4h-workflow-dataset-convert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/i4h-workflow-dataset-convert/SKILL.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Convert Workflow HDF5 to LeRobot

Purpose

Preserve recorded actions, state, cameras, task text, and embodiment labels in a local LeRobot dataset.

Instructions

  1. Run the checkout resolver and select the source HDF5.
  2. Read the workflow, Scene, embodiment, and instruction.
  3. Run conversion for the selected successful episodes.
  4. Inspect metadata, parquet, videos, and feature widths.

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 "$ROOT"
HDF5_PATH=/absolute/path/to/recording.hdf5
uv run --project tools/dataset i4h-dataset inspect "$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. Resolve its workflow and Scene from recording metadata/context, then read the Scene manifest for the embodiment and instruction. Use the embodiment manifest for labels. Do not assume state width equals action width; the converter derives both from the recording.

Convert

RUN_DIR="$(pwd)/runs/<workflow>/$(date +%Y%m%d_%H%M%S)"
DATASET_DIR="$RUN_DIR/lerobot/local/<name>"
mkdir -p "$(dirname "$DATASET_DIR")"
[ ! -e "$DATASET_DIR" ] || { echo "Destination already exists: $DATASET_DIR" >&2; exit 2; }
uv run --project tools/dataset i4h-dataset convert \
  "$HDF5_PATH" "$DATASET_DIR" \
  --robot <embodiment> \
  --repo-id "local/<name>" \
  --successful-only \
  --task "<instruction>"

Read the full file on GitHub · 108 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago Changed · +1 lines 51cae38f064d
  2. 2mo ago Changed · -10 lines · -22 tokens per session 074308a60032
  3. 2mo ago First seen · 117 lines · 65 tokens per session scan A a72783b90ab4

Subscribe to this mod's changes

i4h-workflow-dataset-convert is a skill published in the GitHub repository NVIDIA/skills (3,873 stars, last pushed yesterday), licensed Apache-2.0. It adds 43 tokens to every session and 1,340 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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