Agent skill · NVIDIA
i4h-workflow-dataset-annotate
Grade or filter workflow HDF5 episodes with an OpenAI-compatible vision model. Use for visual success labels; do not use for replay, policy evaluation, or recordings without frames.
What it needs
About 3k tokens when loaded.
What this skill does
Annotate Workflow Recordings Purpose Grade sampled camera frames against a natural-language success criterion while keeping VLM labels separate from simulator success. Instructions 1. Run the checkout resolver and select one HDF5 and one criterion. 2. Test camera sampling and the vision endpoint. 3. Run grading and optional filtering on every selected episode. 4. Compare verdict and output counts. Resolve input and criterion 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/i4hworkflows. I4HWORKFLOWSREPOURL selects the clone source. When I4HWORKFLOWS is unset, derive the fallback directory from that URL; set I4HWORKFLOWS only to reuse or choose a specific destination. Never replace an existing checkout. Use the explicit/current-chain HDF5. “All recorded episodes” means every episode in that selected file, not every historical run. Inspect it and use the user's explicit success criterion when supplied; otherwise combine the source Scene manifest instruction with the workflow's visible terminal goal semantics. Phrase placement success as the object reaching and remaining at its target, not as the robot continuing to hold it. Resolve the endpoint Use a caller-provided OpenAI-compatible vision endpoint/model first. Local Agent exposes that configuration as I4HAGENTVLBASEURL, I4HAGENTVLMODEL, and either I4HAGENTVLAPIKEY or I4HAGENTAPIKEY. Map those generic agent variables to the annotator without printing the credential: If no caller-provided endpoint/model is available, start the repository's local service: Record whether this invocation started it. Do not hard-code a model name in the skill; use the CLI/service defaults unless the user supplies one. Dry-run sampling when needed Use this to verify cameras and sampled frames without transmitting images. Grade and filter Add global --base-url, --model, --camera, or --frames only when selected. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills NVIDIA/i4h-workflow-dataset-annotate