create-prognostic-wrapper

Automate Earth2Studio px wrapper creation from a reference inference script.

1.1k|240|Updated Apr 5, 2024
One-click install
npx skills add https://github.com/NVIDIA/earth2studio --skill create-prognostic-wrapper
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: create-prognostic-wrapper
Source: https://github.com/NVIDIA/earth2studio/tree/main/.claude/skills/create-prognostic-wrapper
Command: npx skills add https://github.com/NVIDIA/earth2studio --skill create-prognostic-wrapper

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Enables rapid creation of Earth2Studio prognostic model wrappers (px) from an existing reference inference script or repository, reducing manual wiring and setup time.

Core Features & Use Cases

  • Guided workflow to analyze dependencies, generate a skeleton wrapper, implement coordinate mappings, and set up testing scaffolds.
  • Supports deterministic single-step and multi-step forward passes for px models, with configurable input/output coords.
  • Use case: convert a reference inference script into a reusable Earth2Studio wrapper to accelerate experimentation and deployment in production pipelines.

Quick Start

Provide a reference inference script or repository and follow the steps to generate a working px wrapper.

Frequently Asked Questions about create-prognostic-wrapper

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create an Earth2Studio prognostic wrapper from an existing inference script?

To create an Earth2Studio prognostic wrapper, provide a reference inference script and follow the guided workflow to analyze dependencies, generate a skeleton wrapper, implement coordinate mappings, and set up testing scaffolds.

What is a px model wrapper used for in Earth2Studio?

A px model wrapper in Earth2Studio coordinates deterministic single-step and multi-step forward passes for prognostic models, enabling reusable experimentation and production pipeline deployment with configurable input and output coordinates.

Does Earth2Studio wrapper generation include unit test scaffolding and pyproject.toml configuration?

Earth2Studio wrapper generation includes unit test scaffolding and satisfies requirements for pyproject.toml extras, ensuring the newly generated prognostic wrapper class skeleton is ready for validation and deployment.

What's the best way to map coordinate systems when building a prognostic model wrapper?

The best way to map coordinate systems is using the guided workflow that automates coordinate mapping implementation during skeleton generation, ensuring input and output coordinates are correctly configured for deterministic forward passes.

Why does my model loading fail when converting a reference script to an Earth2Studio px wrapper?

Model loading during px wrapper creation can fail if dependency resolution is incomplete; the guided workflow automates dependency analysis to ensure the reference repository requirements are properly resolved before skeleton generation.