nvidia-skill-finder
Use for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill. Trigger on NVIDIA products, hardware, software,…
Serve and visually inspect a converted LeRobot dataset in the browser. Use for videos and state/action timelines; do not use for raw workflow HDF5 or incomplete conversion output.
$ npx -y skills add NVIDIA/skills --skill i4h-lerobot-viz --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/i4h-lerobot-vizContext preview
The summary Claude sees to decide when to auto-load this skill.
Serve and visually inspect a converted LeRobot dataset in the browser. Use for videos and state/action timelines; do not use for raw workflow HDF5 or incomplete conversion output.
name: i4h-lerobot-viz
description: Serve and visually inspect a converted LeRobot dataset in the browser. Use for videos and state/action timelines; do not use for raw workflow HDF5 or incomplete conversion output.
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
- lerobot
- visualizationServe one completed local dataset and verify its episode videos and timelines in a browser.
1. Resolve the base checkout and one completed LeRobot dataset. 2. Launch its managed local server. 3. Open the printed URL. 4. Inspect videos, timelines, episode count, and cleanup state.
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 "$ROOT"
find runs "${HF_LEROBOT_HOME:-$HOME/.cache/huggingface/lerobot}" \
-name info.json -path '*/meta/*' -printf '%T@ %h\n' 2>/dev/null \
| sort -nr | headTreat the resolver above as part of the skill contract: a hosted copy may run outside the base repository, so never assume the current checkout contains `workflows/i4h_workflows`. `I4H_WORKFLOWS_REPO_URL` selects the clone source. When `I4H_WORKFLOWS` is unset, derive the fallback directory from that URL; set `I4H_WORKFLOWS` only to reuse or choose a specific destination. Never replace an existing checkout.
Use the explicit/current-chain converted directory. Otherwise select the newest candidate and state the choice. Require `<dataset>/meta/info.json`; route raw HDF5 to `i4h-workflow-dataset-convert`.
Pass an absolute local path:
DATASET_DIR=/absolute/path/to/lerobot/dataset STATE_DIR=/absolute/path/to/run/viz-state tools/dataset/scripts/viz.sh "$DATASET_DIR" --state-dir "$STATE_DIR"
The script selects a free local port, waits for HTTP readiness, and prints the URL, PID, state files, log, and exact stop command. Keep it running only while the user wants access.
Open the printed URL. Confirm:
Reuse a live server only when its target dataset matches. Otherwise stop it using its printed state directory and port, then start the requested dataset.
If startup or the page fails, inspect `meta/info.json`, videos, the printed server log, and port ownership before restarting.
Require the dataset tool environment and a completed LeRobot dataset with `meta/info.json`.
The visualizer does not accept raw workflow HDF5 or repair incomplete metadata/videos.
Report dataset path, repo id, local URL, episode/camera/timeline observations, PID/state directory, and exact cleanup command.
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