Agent skill · nvidia
i4h-workflow-train-rl
Use when training, evaluating, or exporting Workflow policies with online RSL-RL or RLinf, including RL checkpoint and Workflow handoff.
What it needs
About 8k tokens when loaded.
What this skill does
Train a Workflow Policy with RL Purpose Resolve a maintained online-RL profile, verify its Scene/objective/model contracts, run the selected vectorized trainer, evaluate and export its artifact, and hand that artifact to normal Workflow policy validation. Requirements Run the Workflow setup skill first so its uv environments and pinned third-party checkouts are available. Use a CUDA-capable Isaac Lab/Arena runtime for the RSL-RL workflow. For Trocar, provide a local GR00T N1.5 3B base or SFT checkpoint and two visible local GPUs for the isolated controller and simulator runtimes. A compatible checkpoint is a complete local Hugging Face directory that the pinned GR00T N1.5/RLinf loader accepts without conversion; it must retain the N1.5 3B architecture and support the maintained three-camera plus 28-joint observation mapping and 28-D policy action head. Reject another model family, an exported inference-only Task artifact, or a checkpoint whose config changes those interfaces. Instructions 1. Resolve the checkout, confirm Workflow setup is complete, and select training, evaluation, or export from the request. Evaluation/export with an existing checkpoint skips training; never start a new training run to satisfy those requests. 2. For a maintained profile, proceed directly to profile and contract checks. Only a request to author a new RL-backed Workflow takes the authoring branch below; return to these checks after adding its profile. 3. Confirm the Workflow, Scene, observations, actions, rewards, resets, termination, trainer, and runtime Task contracts, then dry-run training or evaluation with its exact checkpoint and options. Export uses profile/contract checks and has no dry-run mode. 4. For training, preflight the selected trainer runtime and train in the foreground. For evaluation/export, go directly to the matching commands below using the supplied checkpoint or run bundle. 5. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/i4h-workflow-train-rl