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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.

Install / Use

npx skills add NVIDIA/skills --skill earth2studio-install

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

92/100

Category

Automation

Supported Platforms

Universal

Our assessment of earth2studio-install

earth2studio-install scores 92/100 on our quality scale, 714th of 2,125 Automation skills we index (top 34%).

Its SKILL.md is 6.4 KB long, well organised into 15 sections with 2 code examples: a thorough specification that gives an agent plenty to work with.

With 3,421 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
18/20
Description
15/15
Adoption
15/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 5 days ago, so earth2studio-install is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

earth2studio-install compared with similar skills

All 4 of these similar skills score higher than earth2studio-install; compare them before choosing.

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Frequently asked questions

How do I install earth2studio-install?
Run npx skills add NVIDIA/skills --skill earth2studio-install. The install tabs above show the steps for each supported agent.
Which AI agents does earth2studio-install work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is earth2studio-install safe to use?
It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is earth2studio-install still maintained?
The repository was last updated 5 days ago, so earth2studio-install is actively maintained.

name: earth2studio-install version: 0.16.0 license: Apache-2.0 metadata: author: NVIDIA Earth-2 Team tags: - earth2studio - earth2 - python - install - deployment - environment 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.

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.

Related Skills

View on GitHub
GitHub Stars3.4k
CategoryAutomation
Updated5d ago
Forks412

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions