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i4h-workflow-dataset-teleop

Record demonstrations through a workflow's teleop Task into workflow HDF5. Use for keyboard, leader, VR, or bus input; do not use for policy evaluation or autonomous rule-based Tasks.

Install / Use

npx skills add NVIDIA/skills --skill i4h-workflow-dataset-teleop

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

89/100

Category

Automation

Supported Platforms

Universal

Tags

Our assessment of i4h-workflow-dataset-teleop

i4h-workflow-dataset-teleop scores 89/100 on our quality scale, 914th of 2,125 Automation skills we index (top 44%).

Its SKILL.md is 4.6 KB long, well organised into 12 sections with 3 code examples: a solid amount of guidance for an agent.

With 3,421 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
18/20
Description
15/15
Adoption
15/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 5 days ago, so i4h-workflow-dataset-teleop is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

i4h-workflow-dataset-teleop compared with similar skills

All 4 of these similar skills score higher than i4h-workflow-dataset-teleop; compare them before choosing.

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i4h-workflow-dataset-teleop (this skill)by NVIDIA893.4k5d agoSKILL.md
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Frequently asked questions

How do I install i4h-workflow-dataset-teleop?
Run npx skills add NVIDIA/skills --skill i4h-workflow-dataset-teleop. The install tabs above show the steps for each supported agent.
Which AI agents does i4h-workflow-dataset-teleop work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is i4h-workflow-dataset-teleop safe to use?
It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is i4h-workflow-dataset-teleop still maintained?
The repository was last updated 5 days ago, so i4h-workflow-dataset-teleop is actively maintained.

name: i4h-workflow-dataset-teleop description: Record demonstrations through a workflow's teleop Task into workflow HDF5. Use for keyboard, leader, VR, or bus input; do not use for policy evaluation or autonomous rule-based Tasks. license: Apache-2.0 metadata: author: "Isaac for Healthcare Team isaac-for-healthcare-support@nvidia.com" version: "0.8.0" tags: - isaac-for-healthcare - i4h - dataset - teleoperation - hdf5

Record Teleop Demonstrations

Purpose

Run the workflow's declared teleop graph through the shared SimulationRunner so actions, state, cameras, segments, attempts, and outcomes use the normal HDF5 contract.

Instructions

  1. Resolve the base checkout and live teleop device contract.
  2. Choose a supported human-input device.
  3. Record in the foreground through run.sh.
  4. Inspect visible motion and HDF5 content.

Resolve 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
./run.sh show <workflow> --mode teleop

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.

Require teleop in the live mode list. Read the workflow builder, its scene manifest teleop override, and the embodiment manifest's teleop_devices. Do not maintain a static support table in the skill.

Choose input

  • Use the named device when supported.
  • Otherwise use the workflow builder's default device.
  • Keep interactive keyboard/leader/VR/bus sessions visible and in the foreground. Surface the device controls and require the human operator to complete the task.
  • Never pretend to provide human input in an unattended shell.

Record

./run.sh <workflow> --teleop <device> \
  --episodes <N> --attempts 3 \
  --record

Omit <device> to use the workflow default. Bare --record writes demos.hdf5 inside the launcher's automatic run directory. Read the absolute directory from the ==> run dir ... line or run.json; do not recreate its timestamp in the shell. When a larger pipeline requires a caller-selected shared directory, pass --run-dir "$RUN_DIR" --record demos.hdf5; the launcher creates the directory and anchors the relative recording name inside it. An absolute --record path remains supported.

Verify

Require the final N/N episodes succeeded summary. Then inspect content:

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

Visually confirm that the operator completes the requested task, robot motion matches the input device, and all expected cameras record the same behavior. Treat zero saved episodes, missing observations, absent action motion, or an unsuccessful task outcome as failure. Stop leftovers with ./stop.sh all.

Troubleshooting

On device or width errors, compare the workflow teleop builder, Scene mode override, and embodiment devices.

Prerequisites

Require a workflow with teleop, a supported device, a working simulator, and a present operator for interactive input.

Limitations

Teleop records human input and requires an operator for interactive devices. Record autonomous rule-based Tasks with i4h-workflow-validate instead.

Examples

  • Record 5 keyboard teleop demonstrations for locomanip tray pick and place. → use G1's supported keyboard device, require a human operator, and verify the recorded action motion.

Completion gate

Report workflow, mode/device, controls, requested/saved episodes, attempts, visual result, HDF5 path, dimensions/segments, and whether a human operator completed the task.

Related Skills

View on GitHub
GitHub Stars3.4k
CategoryAutomation
Updated5d ago
Forks412

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions