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/i4h-workflow-e2e

@79f1873
by NVIDIA Corporationnvidia/skills3.5k stars
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Run the maintained workflow data-to-policy pipeline from recording through checkpoint validation. Use for full end-to-end requests; do not use for one individual stage.

Use this Skill: https://skilld.dev/gh/nvidia/skills/i4h-workflow-e2e

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Description: <br>

Run the maintained workflow data-to-policy pipeline from recording through checkpoint 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 running the Isaac for Healthcare end-to-end data-to-policy workflow, from recording through training and checkpoint validation. <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, 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>

Evaluated against 2 evaluation tasks (2 positive) in isolated k8s-sandbox pods with 3 attempts per task. <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 final answer is correct against the reference answer. <br>
  • Discoverability: Whether the expected skill was selected and the workflow executed when needed. <br>
  • Effectiveness: Whether the skill helped complete the user's goal (50% goal accuracy + 50% expected workflow adherence). <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: Unsafe operations, secret leakage, and unauthorized access. <br>
  • accuracy: Final-answer correctness against the reference answer. <br>
  • skill_execution: Whether the expected skill was selected, decoys were avoided, and the workflow executed. <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 usage. <br>

Evaluation Results: <br>

Measure Claude Code (Baseline → Skill Uplift) Codex (Baseline → Skill Uplift)
Overall 62.8% — baseline ran, but no comparable score was available; uplift unavailable 57.3% — baseline ran, but no comparable score was available; uplift unavailable
Security 83.3% → 33.3% (-50.0 points) 75.0% → 0.0% (-75.0 points)
Correctness 6.7% → 100.0% (+93.3 points) 25.0% → 100.0% (+75.0 points)
Discoverability 85.0% — baseline ran, but no comparable score was available; uplift unavailable 75.0% — baseline ran, but no comparable score was available; uplift unavailable
Effectiveness 6.3% → 20.2% (+13.9 points) 22.1% → 52.9% (+30.8 points)
Efficiency 75.3% — baseline ran, but no comparable score was available; uplift unavailable 58.6% — baseline ran, but no comparable score was available; uplift unavailable

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>

Source: SKILL.md on GitHub

1 warning1d3 checks · Risk SAFE
  • Gen Agent Trust Hub1d

    This skill automates the setup and execution of a robotics data-to-policy pipeline by cloning official resources from a trusted NVIDIA-associated repository and running a maintained driver script with built-in verification steps.

  • Socket1d

    No alerts

  • Snyk1d

    Risk: MEDIUM · 1 issue

Signed by skilld at 79f1873. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated yesterday
Other metadata
metadata
{
  "author": "Isaac for Healthcare Team <isaac-for-healthcare-support@nvidia.com>",
  "version": "0.8.0",
  "verification-request": "2026-09-15",
  "tags": [
    "isaac-for-healthcare",
    "i4h",
    "robotics",
    "data-to-policy"
  ]
}

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