AGENT SKILL

earth2studio-install

Guide installing Earth2Studio via uv or pip, selecting model extras, and configuring the environment. Do NOT use for writing inference code, choosing models, or PhysicsNeMo questions.

License 许可
Apache-2.0
最近更新
2026-08-12
Stars
★ 0
Forks
0

01 前言 Front Matter

name
earth2studio-install
license
Apache-2.0
version
0.16.0
metadata
{ "tags": [ "earth2studio", "earth2", "python", "install", "deployment", "environment" ], "author": "NVIDIA Earth-2 Team" }
description
Guide installing Earth2Studio via uv or pip, selecting model extras, and configuring the environment. Do NOT use for writing inference code, choosing models, or PhysicsNeMo questions.

02 资源文件 4

03 SKILL.md 正文

Earth2Studio Installation Skill

Never install packages automatically

You MUST NOT install, upgrade, or modify packages on the user's behalf. Provide the exact command; the user runs it. No exceptions.

Forbidden: running pip install, uv pip install, uv add, uv sync, conda install, apt install, or any package manager.

Instead: give the exact command and ask the user to run it. Explain why the package is needed.

When a package is needed:

  1. Identify it
  2. Provide the exact command
  3. Explain why it is needed
  4. Wait for the user to confirm they ran it

Even if the user says "just install it", give the command and require them to execute it themselves.

Purpose

Help users install Earth2Studio and its optional model dependencies correctly for their use case. This skill handles package installation, optional-extra selection, environment variable configuration, and install verification.

Prerequisites

  • Python 3.10+ (3.13 recommended)
  • CUDA-capable GPU with compatible drivers for GPU extras
  • uv (recommended) or pip package manager
  • Internet access (packages installed from PyPI and GitHub)

You are helping a user install Earth2Studio and its optional model dependencies. Your only job is to get the package installed correctly for their use case — do not write inference code, do not compose workflows.

Core principle: docs are the source of truth

Earth2Studio installation commands, version tags, and extra names change between releases. Before executing or recommending any install command, fetch the live installation docs:

https://nvidia.github.io/earth2studio/userguide/about/install.html

Parse the page for the current version tag, available extras, and any special build notes. The workflow below is structural guidance — the specific commands come from the live page.

Instructions

Step 1. Fetch live docs

Use WebFetch on the install URL above. Extract:

  • Current release version tag (e.g. @0.14.0)
  • Available optional extras by category
  • Known build quirks (e.g. --no-build-isolation for pip, manual pre-installs)

Keep this data in working memory for all subsequent steps.

Step 2. Understand the user's environment

Ask (cap at 3 questions, skip what the user already answered):

  1. Package manager — uv (recommended) or pip? If unsure, recommend uv and link https://docs.astral.sh/uv/getting-started/installation/
  2. Project context — new project or adding to existing?
  3. Python version — recommend the version from the docs (currently 3.13)

Step 3. Base install

Provide commands from the live docs based on their answers:

  • uv uses a git source (not PyPI) to handle URL-based transitive dependencies
  • pip installs from PyPI but some extras require manual pre-install steps

After the user runs the install, verify:

import earth2studio
earth2studio.__version__

Step 4. Select models and extras

Present the available extras organized by use case. Ask what the user plans to do — don't dump all options unprompted. Categories from the docs:

Category Example extras
Prognostic (forecasting) aifs, aurora, graphcast, pangu, sfno, stormcast, ...
Diagnostic (post-processing) corrdiff, climatenet, precip-afno, ...
Data assimilation (beta) da-healda, da-interp, da-stormcast
Submodules data, perturbation, statistics

The exact list comes from the live docs — cite those, not this table.

Ask:

  1. Which models do you plan to use?
  2. Do you need submodule extras (data sources, perturbation methods, statistics)?
  3. Or install everything? (uv only: --extra all)

Step 5. Install selected extras

Provide the exact commands from the live docs for their selections. Key warnings to surface:

  • Slow builds: flash-attention (AIFS variants), natten (Atlas, StormScope), torch-harmonics CUDA extensions (FCN3, SFNO) — can take 10-30+ minutes
  • pip-specific manual steps: some models require --no-build-isolation or pre-installing packages like earth2grid, torch-harmonics, or makani
  • Data assimilation models: require CuPy + cuDF (CUDA 12)

Step 6. Configuration (offer, don't force)

Mention environment variables the user might want to set — only if relevant (e.g. limited disk, shared filesystem, CI environment):

Variable Purpose
EARTH2STUDIO_CACHE General cache directory
EARTH2STUDIO_DATA_CACHE Data source cache (overrides general)
EARTH2STUDIO_MODEL_CACHE Model checkpoint cache (overrides general)
EARTH2STUDIO_PACKAGE_TIMEOUT Max seconds for model downloads

Troubleshooting

If installation fails, point the user to:

Common issues:

  • PyTorch/CUDA mismatch: verify torch.cuda.is_available() first
  • flash-attention build failure: CUDA toolkit version must match PyTorch CUDA
  • ONNX Runtime GPU: may need version-specific install for their CUDA
  • ecCodes missing: required for GRIB data handling; install via sudo apt-get install libeccodes-dev (Debian/Ubuntu) or conda install -c conda-forge eccodes
  • Python.h: No such file or directory: missing Python development headers; install via sudo apt-get install python3-dev

Limitations

  • Cannot help with runtime errors unrelated to missing dependencies
  • Does not cover model checkpoint downloads (those happen at first inference)
  • Data source setup beyond the data extra is out of scope
  • Cannot write inference or training code, or compose Earth2Studio workflows

Ownership and out-of-scope

Owns: package installation, optional-extra selection, environment variable configuration, install verification.

Does not own: writing inference or training code, composing Earth2Studio workflows, data source setup beyond the data extra, model checkpoint downloads (those happen at runtime), troubleshooting runtime errors unrelated to missing dependencies.

04 同仓库更多 Skills

headmktlucca-ui
headmktlucca-ui/neuroads-lp

xunit-skill

Generates xUnit.net tests in C#. Covers Fact/Theory, constructor injection, IClassFixture, and FluentAssertions. Use when user mentions "xUnit", "[Fact]", "[Theory]", "Assert.Equal", "C# xUnit". Triggers on: "xUnit", "[Fact]", "[Theory]", "Assert.Equal C#", "xUnit.net".

测试与质量Skill与智能体开发
★ 0
headmktlucca-ui
headmktlucca-ui/neuroads-lp

xcuitest-skill

Generates XCUITest UI tests for iOS/iPadOS apps in Swift. Apple's native testing framework for reliable, fast UI automation. Supports local simulators and TestMu AI cloud real devices. Use when user mentions "XCUITest", "XCTest", "iOS UI test", "Swift test", "XCUIApplication". Triggers on: "XCUITest", "XCTest UI", "iOS UI test", "Swift UI test", "XCUIApplication", "TestMu".

测试与质量Skill与智能体开发
★ 0
headmktlucca-ui
headmktlucca-ui/neuroads-lp

world-builder

Create and manage generative game zones for Dorothy's Pokemon-style world. Use this skill when creating, updating, or designing game worlds via MCP tools.

视觉设计Skill与智能体开发
★ 0
headmktlucca-ui
headmktlucca-ui/neuroads-lp

webdriverio-skill

Generates WebdriverIO (WDIO) automation tests in JavaScript or TypeScript. Supports local and TestMu AI cloud. Use when user mentions "WebdriverIO", "WDIO", "wdio.conf", "browser.url", "$", "$$". Triggers on: "WebdriverIO", "WDIO", "wdio", "browser.$".

测试与质量Skill与智能体开发
★ 0
headmktlucca-ui
headmktlucca-ui/neuroads-lp

web-design-guidelines

Web platform design and accessibility guidelines. Use when building web interfaces, auditing accessibility, implementing responsive layouts, or reviewing web UI code. Triggers on tasks involving HTML, CSS, web components, WCAG compliance, responsive design, or web performance.

设计师前端开发视觉设计
★ 0
headmktlucca-ui
headmktlucca-ui/neuroads-lp

watchos-design-guidelines

Apple Human Interface Guidelines for Apple Watch. Use when building watchOS apps, complications, or workout features. Triggers on tasks involving Watch UI, Digital Crown, glanceable interfaces, or wrist-based interactions.

设计师视觉设计
★ 0