i4h-workflow
Orient users to the i4h workflow runtime and route them to the correct stage skill.
Skill by Isaac for Healthcare Team <isaac-for-healthcare-support@nvidia.com>
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: productivity, agent-orchestration, documentation
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/i4h-workflow
What's inside
- Skill name
i4h-workflow- Description
- Orient users to the i4h workflow runtime and route them to the correct stage skill. Use for architecture, support, or where-to-start questions; do not execute a known stage.
- License
- Apache-2.0
- Metadata
- author: Isaac for Healthcare Team <isaac-for-healthcare-support@nvidia.com> · version: 0.8.0 · verification-request: 2026-09-15
- Instructions
- 99 lines in SKILL.md · view on GitHub
Files (6)
- BENCHMARK.md
- SKILL.md
- evals.json · evals/
- repo-map.md · references/
- skill-card.md
- skill.oms.sig
SKILL.md (first lines)
# i4h Workflows
## Purpose
Orient the user from live repository facts, then hand execution to the narrowest stage skill.
## Instructions
1. Run the base-checkout resolver.
2. Read live support and `DESIGN.md`.
3. Use only current architecture facts in the answer.
4. Use the narrowest stage skill for execution.
## Resolve the checkout
```bash
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"
```
Treat this resolver 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.
## Inspect before answering
Read `./DESIGN.md` for architecture and `skills/i4h-workflow/references/repo-map.md` for ownership. Discover current support instead of copying a static table:
```bash
./run.sh list
```
If discovery fails because setup is incomplete, report that limitation and route to `i4h-workflow-setup`.
## Explain the design
Keep the summary precise:
- A Scene owns the simulated world, assets, embodiment, cameras, randomization, adapters, and reset hooks.
- A Task owns one reusable capability. It reads `ctx.scene`, writes `ctx.act`, and never advances the simulator.
- A Workflow selects one Scene, exposes run-mode-specific `TaskGraph` builders, and owns goal semantics. A run mode answers how that workflow should run; code and CLI use the shorter term `mode`.
- The Engine schedules graph nodes; the shared `SimulationRunner` alone resets, steps, renders, records, retries whole episodes, and prints run summaries.
- Online RL is a separate training lifecycle: its trainer owns vectorized stepping and returns a checkpoint to the normal policy Task and `SimulationRunner` validation path.
- Simulator-compatible exported RSL-RL actors may run as in-process Tasks; incompatible foundation-model policy stacks remain remote.
- Remote policy stacks run out of process and communicate over Zenoh; offline dataset tools remain independent of the simulator.
- Python owns behavior. Manifests carry facts across dependency boundaries.
Do not describe retired environment YAMLs, per-mode runners, or separate policy/Arena launchers.
## Route the next action
| Goal | Skill |
|---|---|
| Install, sync, or repair dependencies | `i4h-workflow-setup` |
| Create a new workflow/environment | `i4h-workflow-create` |
| Edit an existing scene, camera, task, or success rule | `i4h-workflow-scene-edit` |
| Record demonstrations | `i4h-workflow-dataset-teleop` |
| Replay HDF5 | `i4h-workflow-dataset-replay` |
| Augment HDF5 | `i4h-workflow-dataset-mimic` |
| Grade/filter HDF5 with a VLM | `i4h-workflow-dataset-annotate` |
| Convert HDF5 to LeRobot | `i4h-workflow-dataset-convert` |
| Inspect LeRobot in a browser | `i4h-lerobot-viz` |
| Fine-tune a manifest-backed policy task | `i4h-workflow-finetune` |
| RL post-train a supported policy in simulation | `i4h-workflow-train-rl` |
| Run policy or rule-based rollouts | `i4h-workflow-validate` |
| Run the maintained complete pipeline | `i4h-workflow-e2e` |
For `Stop all`, do not load a stage skill. Run `./stop.sh all` from the repository root and report the stopped process count.
## Troubleshooting
If discovery fails, verify the resolved checkout and run setup. If a mode is absent, report it as unsupported.
## Prerequisites
Require a readable base checkout or network access to clone it.
## Limitations
This router does not install, author, simulate, process data, train, or evaluate.
## Examples
- `What does the i4h workflow include, and where should I start?` → inspect live support, summarize `DESIGN.md`, and recommend one stage skill.
## Completion gate
Answer with the live workflow/mode list, a short architecture summary, and one concrete next skill. If the requested workflow or mode is absent from `run.sh list`, say it is unsupported instead of inventing a command.From NVIDIA/skills, Apache-2.0.
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Signals
- Stars
- 3,718
- Forks
- 457
- Open issues
- 8
- Last commit (this folder)
- Sep 30, 2026 (27 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 0.8.0
- License
- Apache-2.0
- Repository
- github.com/NVIDIA/skills
- Website
- docs.nvidia.com/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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i4h-workflow-train-rl
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Run the root-level workflow runtime policy or rule-based rollouts and verify simulator success.
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Preflight and set up the root-level workflow runtime.
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Fine-tune a manifest-backed GR00T or openpi remote Task on compatible LeRobot data.
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Cite this page
i4h-workflow skill. Agent Mart. https://agentmart.dev/skills/nvidia-i4h-workflow (last updated 2026-10-24)