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I4h Workflow Setup

NVIDIAOfficialCreated by Isaac for Healthcare TeamDistributed by NVIDIA

  • Skill
  • Workflow
  • Cloud and DevOps
  • Apache-2.0
  • Medium risk
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From the author

Preflight and set up the root-level workflow runtime. Use for installation, missing component environments, or third-party failures; do not use for rollout validation.
— the description by Isaac for Healthcare Team

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The i4h-workflow-setup skill provides a standardized procedure for initializing the Isaac for Healthcare (i4h) workflow environment. It manages repository checkout, performs host-level preflight checks for system dependencies, executes the full setup process, and verifies workflow discovery and linting. This skill is designed to ensure the runtime is correctly configured before attempting to run specific healthcare-related simulation workflows.

What it does

  • Resolves and clones the i4h workflows repository to a specified or default directory.
  • Performs host preflight checks including OS, hardware, and dependency verification.
  • Executes the full setup script to synchronize environments and third-party components.
  • Verifies successful workflow discovery and runs linting across all components.
  • Provides a structured approach to troubleshooting environment-related installation failures.

When to use it

  • When initializing a new development or runtime environment for Isaac for Healthcare workflows.
  • When encountering missing component environments or third-party dependency failures.
  • To verify that the host system meets all hardware and software requirements before deployment.
  • To perform a clean synchronization of the workflow runtime.

Advantages

  • Ensures a consistent and reproducible environment setup across different machines.
  • Automates complex dependency checks and repository management.
  • Provides immediate feedback on system compatibility through preflight checks.
  • Validates the integrity of the installation via automated discovery and linting.

Usage examples

“Set up the i4h workflow on this machine and tell me if any host requirements are missing.”
The agent will perform host preflight checks, execute the full setup script, run discovery, and report linting results.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/nvidia/i4h-workflow-setup/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip i4h-workflow-setup.zip -d .agents/skills

Documentation by Isaac for Healthcare Team

i4h Workflow Setup

Purpose

Prepare the complete runtime, then prove dependency-light workflow discovery works.

Instructions

  1. Resolve the base checkout.

  2. Run every host preflight check.

  3. Run default full setup.

  4. Verify discovery and lint --all.

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.

Preflight

uname -srm
command -v uv
command -v git
nvidia-smi
df -h .
./setup.sh --help

Require supported Linux on x86_64 or aarch64, uv, Git, network access for missing packages/assets, sufficient disk and model-cache space, and an NVIDIA driver compatible with the repository's Isaac Sim version. Read the exact current requirements from ./README.md; do not rely on remembered version numbers. Require Docker only when the requested local VLM or Cosmos service needs it.

Sync

Run the default full setup:

./setup.sh

The explicit equivalent is:

./setup.sh all

Use ./setup.sh clean only when the user explicitly requests a full rebuild or cleanup because it deletes generated caches, component environments, and third-party checkouts. Setup is idempotent; do not clean as a generic repair. The setup script restores pinned third-party sources and the upstream Isaac Sim skill catalog; do not copy that catalog into skills/.

Verify

./run.sh list
./run.sh lint --all
test -f ./third_party/IsaacSim-045ca8b/skills/SKILLS.md

Use run.sh show <workflow> --mode <mode> when the user named a workflow. These checks prove discovery and contracts without importing Isaac Sim. Use i4h-workflow-validate for an actual rollout.

Troubleshooting

On failure, report the first host, network, checkout, or uv-sync error and rerun full setup only after correcting that cause.

Prerequisites

Require supported Linux, network access, uv, Git, disk space, and a compatible NVIDIA GPU/driver for simulator use.

Limitations

Setup does not download every optional checkpoint or prove any rollout succeeds. clean is destructive to generated environments and third-party checkouts.

Examples

  • Set up the i4h workflow on this machine and tell me if any host requirements are missing. → preflight, run default full setup, then run discovery and lint --all.

Completion gate

Report every host check, synced target, first failing component if any, discovery/lint results, and the smallest next smoke command. Do not claim simulator or policy success from setup alone.

Files

skill-card.md

Description: <br>

Preflight and set up the root-level workflow runtime. Use for installation, missing component environments, or third-party failures; do not use for rollout validation. <br>

This skill is ready for commercial/non-commercial use. <br>

Owner

NVIDIA <br>

License/Terms of Use: <br>

Apache-2.0 <br>

Use Case: <br>

Developers and engineers who need to prepare the Isaac for Healthcare workflow runtime, verify host prerequisites, and confirm dependency-light workflow discovery. <br>

Deployment Geography for Use: <br>

Global <br>

Requirements / Dependencies: <br>

Requires API Key or External Credential: [Not Specified] <br> Credential Type(s): [None identified] <br>

Do not include secrets in prompts/logs/output; use least-privilege credentials; rotate keys as appropriate. <br>

Known Risks and Mitigations: <br>

Risk: Review before execution as proposals could introduce incorrect or misleading guidance into skills. <br> Mitigation: Review and scan skill before deployment. <br>

Reference(s): <br>

Skill Output: <br>

Output Type(s): [Shell commands, Configuration instructions, Analysis] <br> Output Format: [Markdown with inline bash code blocks] <br> Output Parameters: [1D] <br> Other Properties Related to Output: [None] <br>

Evaluation Agents Used: <br>

  • Claude Code (aws/anthropic/bedrock-claude-opus-4-8) <br>

  • Codex (openai/openai/gpt-5.5) <br>

Evaluation Tasks: <br>

1 evaluation task (1 positive), 3 attempts per task in isolated k8s-sandbox pods. <br>

Evaluation Metrics Used: <br>

Reported benchmark dimensions: <br>

  • Security: Whether the skill is safe to use, checking for unsafe operations, secret leakage, and unauthorized access. <br>

  • Correctness: Whether the answer produced is correct against the reference answer. <br>

  • Discoverability: Whether the right skill was selected, decoys were avoided, and the workflow executed. <br>

  • Effectiveness: Whether the skill helped complete the user's goal (50% goal accuracy + 50% behavior check). <br>

  • Efficiency: Whether the skill avoided wasted tool calls and token usage (50% tool productivity + 50% token efficiency). <br>

Underlying evaluation signals used in this run: <br>

  • security: Checks for unsafe operations, secret leakage, and unauthorized access. <br>

  • skill_execution: Whether the expected skill was selected, decoys were avoided, and the workflow executed. <br>

  • accuracy: Final-answer correctness against the reference answer. <br>

  • goal_accuracy: Whether the user's goal was achieved. <br>

  • behavior_check: Whether the expected workflow behavior was followed. <br>

  • skill_efficiency: Tool-call productivity; routing is scored under Discoverability. <br>

  • token_efficiency: Actual uncached prompt plus completion token usage. <br>

Evaluation Results: <br>

MeasureClaude Code (Baseline → Skill Uplift)Codex (Baseline → Skill Uplift)
Overall88.8%65.7%
Security100.0% → 100.0% (±0.0 points)0.0% → 0.0% (±0.0 points)
Correctness80.0% → 100.0% (+20.0 points)100.0% → 100.0% (±0.0 points)
Discoverability95.0%75.0%
Effectiveness39.3% → 71.1% (+31.8 points)85.7% → 95.0% (+9.3 points)
Efficiency77.9%58.7%

Skill Version(s): <br>

0.8.0 (source: frontmatter) <br>

Ethical Considerations: <br>

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal team to ensure this skill meets requirements for the relevant industry and use case and addresses unforeseen product misuse. <br>

(For Release on NVIDIA Platforms Only) <br> Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns here. <br>

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

What our scanner noticed· Medium risk

  • Large base64-encoded blobs

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Isaac for Healthcare Team
Publisher
NVIDIA (Official)
Distributed by
NVIDIA
Source
NVIDIA/skills · skills/i4h-workflow-setup · commit fce3cca
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE-APACHE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Isaac for Healthcare Team or NVIDIA.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download i4h-workflow-setup.zip