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i4h-workflow

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.

Install / Use

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

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

89/100

Category

Automation

Supported Platforms

Universal

Tags

Our assessment of i4h-workflow

i4h-workflow scores 89/100 on our quality scale, 916th of 2,125 Automation skills we index (top 44%).

Its SKILL.md is 5.0 KB long, well organised into 12 sections with 2 code examples: a solid amount of guidance for an agent.

With 3,421 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
18/20
Description
15/15
Adoption
15/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 5 days ago, so i4h-workflow is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

i4h-workflow compared with similar skills

All 4 of these similar skills score higher than i4h-workflow; compare them before choosing.

SkillScoreStarsUpdatedFormat
i4h-workflow (this skill)by NVIDIA893.4k5d agoSKILL.md
Agent-Reachby Panniantong10086.0k13d agoCLAUDE.md
rufloby ruvnet10073.4ktodayCLAUDE.md
Scraplingby D4Vinci10084.4ktodayMCP Server
algorithmic-artby anthropics100177.9k6d agoSKILL.md

Frequently asked questions

How do I install i4h-workflow?
Run npx skills add NVIDIA/skills --skill i4h-workflow. The install tabs above show the steps for each supported agent.
Which AI agents does i4h-workflow work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is i4h-workflow safe to use?
It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is i4h-workflow still maintained?
The repository was last updated 5 days ago, so i4h-workflow is actively maintained.

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" tags: - isaac-for-healthcare - i4h - robotics - onboarding

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

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:

./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.

Related Skills

View on GitHub
GitHub Stars3.4k
CategoryAutomation
Updated5d ago
Forks412

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions