I4h workflow e2e

Skill NVIDIA/skills/skills/i4h-workflow-e2e

Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end.

Install

npx -y skills add NVIDIA/skills --skill i4h-workflow-e2e

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What its author says it does

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Run the full end-to-end agentic pipeline (record → mimic → annotate → replay → convert → visualize → finetune → validate). Use when asked to run the whole pipeline or do an e2e, smoke, or demo run.

The file declares its own license as Apache-2.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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i4h Workflow — End-to-End

Purpose

Run the full end-to-end agentic pipeline (record, mimic, annotate/filter, replay, convert, visualize, finetune, validate). Use when the user asks to run the full pipeline, smoke the whole workflow, demo the workflow, or do an e2e run.

Base Code

These steps drive the i4h-workflows base code (the workflows/agentic/ tree). To reuse an existing checkout, set I4H_WORKFLOWS to its path (no clone happens). Otherwise this resolves the current repo, or clones to ~/i4h-workflows — pick that default without prompting. Run every command below from the resolved root:

# Resolve the i4h-workflows base code (provides workflows/agentic/).
ROOT="${I4H_WORKFLOWS:-$(git rev-parse --show-toplevel 2>/dev/null)}"
if [ ! -d "$ROOT/workflows/agentic" ]; then
  ROOT="${I4H_WORKFLOWS:-$HOME/i4h-workflows}"
  [ -d "$ROOT/workflows/agentic" ] || git clone https://github.com/isaac-for-healthcare/i4h-workflows "$ROOT"
fi
export I4H_WORKFLOWS="$ROOT"; cd "$ROOT"

Basics

Env config (source of truth): workflows/agentic/config/environments/<env>.yaml — drives every stage for <env> (robot, task, policy, cameras, arena.max_timesteps, dataset.* mappings).
Use the e2e script for full pipeline runs.
For per-stage work, use the corresponding dataset/finetune/validate skills.
assemble_trocar is inference-only; the e2e script skips finetune and checkpoint validation for it.

Dry Run

REPO_ROOT="${I4H_WORKFLOWS:-$(git rev-parse --show-toplevel 2>/dev/null)}"; [ -d "$REPO_ROOT/workflows/agentic" ] || REPO_ROOT="$HOME/i4h-workflows"
"${REPO_ROOT}/workflows/agentic/scripts/e2e/run.sh" --dry-run --env <env>

Run

Run the steps below in order. Each step is a separate bash call; variables persist in the local agent's tmux session.

For Claude Code --print or any other noninteractive runner, keep Step 2 in the foreground. This is a validation requirement: do not use Claude background tasks, async task mode, Bash background mode, &, nohup, tmux, disown, or any detached process/task id, and do not answer that the pipeline is still running. Do not return until run.sh exits and you have inspected logs/SUMMARY.txt on success, or the failing stage log on failure. Report the run dir, skipped stages, per-stage status, key artifacts, and cleanup/stop status before finishing.

Step 1 — setup

REPO_ROOT="${I4H_WORKFLOWS:-$(git rev-parse --show-toplevel 2>/dev/null)}"; [ -d "$REPO_ROOT/workflows/agentic" ] || REPO_ROOT="$HOME/i4h-workflows"

Step 2 — e2e pipeline

"${REPO_ROOT}/workflows/agentic/scripts/e2e/run.sh" --env <env>

Flags

--skip-mimic, --skip-annotate, --skip-replay, --skip-viz
--from-stage <stage> --run-dir <existing-run> resumes from a prior run.
Policy record/verify stages open the sim window by default. Set ARENA_HEADLESS=1 before run.sh only when the user explicitly asks for headless/no-window execution.

Stages: setup record mimic annotate replay convert viz finetune validate summary.

Outputs

The script prints RUN_DIR and symlinks it to runs/.latest. Subdirs:

logs/ — per-stage logs, workflow.log (full teed output), and logs/SUMMARY.txt (the final summary report)
data/
lerobot/
checkpoint/ (trainable envs only)

Monitor

run.sh runs every stage in the foreground and returns only when the whole pipeline ends, so track a long run from a separate shell (do not expect to query it from the shell that launched it):

tail -f "${REPO_ROOT}/workflows/agentic/runs/.latest/logs/workflow.log"   # live per-stage progress
cat    "${REPO_ROOT}/workflows/agentic/runs/.latest/logs/SUMMARY.txt"     # final report (once DONE)

Stop

Step 3 — stop (if needed)

"${REPO_ROOT}/workflows/agentic/stop.sh" all --env <env>

Prerequisites

Workflow set up via [[i4h-workflow-setup]] (the .venv must exist); setup is also the first pipeline stage.
A valid --env name to drive the run.
For per-stage work, use the corresponding dataset/finetune/validate skills instead.

Limitations

assemble_trocar is inference-only; the e2e script skips finetune and checkpoint validation for it.
checkpoint/ outputs are produced for trainable envs only.
Resuming requires both --from-stage <stage> and --run-dir <existing-run>.

Troubleshooting

Error: .venv not found / module import fails - Cause: workflow not set up. Fix: run [[i4h-workflow-setup]] first.
Error: env not recognized - Cause: wrong --env name. Fix: pass a valid env name; dry-run first with --dry-run --env <env>.
Error: resume fails to find prior outputs - Cause: --from-stage used without a matching --run-dir. Fix: pass --from-stage <stage> --run-dir <existing-run>.
Error: stale processes block a rerun - Cause: a previous pipeline session is still running. Fix: run stop.sh all --env <env> before retrying.

Final Response

Report env, run dir, skipped stages, per-stage success/failure, key artifact paths.