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/earth2studio-create-prognostic

@4cb1092
by NVIDIA Corporationnvidia/skills3.5k stars
424

Create Earth2Studio prognostic (time-stepping forecast) model wrappers. Do NOT use for diagnostic models, data sources, or installation.

Ask your Agent

Use this Skill: https://skilld.dev/gh/nvidia/skills/earth2studio-create-prognostic

This session only. Nothing lands on disk.

BENCHMARK.md

≈1.1k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Evaluation Report

Evaluation of the earth2studio-create-prognostic skill before publication through NVSkills-Eval.

This benchmark summarizes 3-Tier Evaluation from NVSkills-Eval results for the skill. The goal is to document whether the skill is safe, discoverable, effective, and useful for agents before it is published for broader workflow use.

Evaluation Summary

  • Skill: earth2studio-create-prognostic
  • Evaluation date: 2026-06-03
  • NVSkills-Eval profile: external
  • Overall verdict: FAIL
  • Tier 3 live agent evaluation: not available in this report

Agents Used

  • Tier 3 agent details were not available in this report.

Metrics Used

Reported benchmark dimensions:

  • Security: checks whether skill-assisted execution avoids unsafe behavior such as secret leakage, destructive commands, or unauthorized access.
  • Correctness: checks whether the agent follows the expected workflow and produces the correct final output.
  • Discoverability: checks whether the agent loads the skill when relevant and avoids using it when irrelevant.
  • Effectiveness: checks whether the agent performs measurably better with the skill than without it.
  • Efficiency: checks whether the agent uses fewer tokens and avoids redundant work.

Underlying evaluation signals used in this run:

  • No Tier 3 evaluation signal details were available in this report.

Test Tasks

Tier 3 evaluation task details were not available in this report.

Results

Tier 3 dimension rollup was not available in this report.

Tier 1: Static Validation Summary

Tier 1 validation passed with observations. NVSkills-Eval ran 9 checks and found 6 total findings.

Top findings:

  • MEDIUM SCHEMA/body_recommended_section: Missing recommended section: '## Instructions' (skills/earth2studio-create-prognostic/SKILL.md)
  • LOW QUALITY/quality_reliability: No prerequisites/requirements documented (skills/earth2studio-create-prognostic/SKILL.md)
  • LOW QUALITY/quality_reliability: No limitations documented (skills/earth2studio-create-prognostic/SKILL.md)
  • LOW QUALITY/quality_efficiency: Non-doc file in references/: testing-guide.py (skills/earth2studio-create-prognostic/SKILL.md)
  • LOW UNICODE/isolated_invisible_char: Isolated invisible character(s) (1): VARIATION SELECTOR-16 (SKILL.md:25)

Tier 2: Deduplication Summary

Tier 2 validation reported findings. NVSkills-Eval ran 2 checks and found 5 total findings.

Top findings:

  • HIGH DUPLICATE/duplicate: Duplicate content found within references/validation-guide.md: "# ============================================================" in references/validation-guide.md (lines 93-97) vs "# Load model" in references/validation-guide.md (lines 353-356) (references/validation-guide.md:93)
  • HIGH DUPLICATE/duplicate: Duplicate content found across references/method-templates.py and references/skeleton-template.py: "default_generator_template()" in references/method-templates.py (lines 215-255) vs "create_iterator_template()" in references/method-templates.py (lines 258-277) vs "_default_generator()" in references/skeleton-template.py (lines 357-392) vs "create_iterator()" in references/skeleton-template.py (lines 397-416) (references/method-templates.py:215)
  • HIGH DUPLICATE/duplicate: Duplicate content found across references/method-templates.py and references/skeleton-template.py: "load_default_package_template()" in references/method-templates.py (lines 286-321) vs "load_default_package()" in references/skeleton-template.py (lines 202-226) (references/method-templates.py:286)
  • HIGH DUPLICATE/duplicate: Duplicate content found across references/method-templates.py and references/skeleton-template.py: "call_template()" in references/method-templates.py (lines 157-211) vs "call()" in references/skeleton-template.py (lines 303-351) (references/method-templates.py:157)
  • HIGH DUPLICATE/duplicate: Duplicate content found across references/method-templates.py and references/skeleton-template.py: "load_model_template()" in references/method-templates.py (lines 326-365) vs "load_model()" in references/skeleton-template.py (lines 233-262) (references/method-templates.py:326)

Publication Recommendation

The skill should be reviewed before NVSkills-Eval publication. Skill owners should address the findings above and rerun NVSkills-Eval to refresh this benchmark.

Source: SKILL.md on GitHub

Third-party checks

2 warnings3mo3 checks · Risk MEDIUM
  • Gen Agent Trust Hub3mo

    This skill facilitates the creation of wrappers for machine learning weather models. It involves fetching and executing third-party inference scripts and uses an unsafe deserialization pattern (torch.load with weights_only=False) which can lead to arbitrary code execution if used with malicious model checkpoints.

  • Socket3mo

    No alerts

  • Snyk3mo

    Risk: MEDIUM · 1 issue

Provenance

Signed by skilld at 4cb1092. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 3 months ago

Capability

version
0.16.0
argument-hint
URL or local path to reference inference script (optional)
Other metadata
metadata
{
  "author": "NVIDIA Earth-2 Team <agent-skills@nvidia.com>",
  "tags": [
    "earth2studio",
    "prognostic-model",
    "python"
  ]
}

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