nvidia-skill-finder
Use for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill. Trigger on NVIDIA products, hardware, software,…
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.
$ npx -y skills add NVIDIA/skills --skill earth2studio-install --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/earth2studio-installContext preview
The summary Claude sees to decide when to auto-load this skill.
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.
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.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.
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.
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.
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.
Use WebFetch on the install URL above. Extract:
manual pre-installs)
Keep this data in working memory for all subsequent steps.
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)
Provide commands from the live docs based on their answers:
After the user runs the install, verify:
import earth2studio earth2studio.__version__
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`)
Provide the exact commands from the live docs for their selections. Key warnings to surface:
(Atlas, StormScope), torch-harmonics CUDA extensions (FCN3, SFNO) — can take 10-30+ minutes
`--no-build-isolation` or pre-installing packages like earth2grid, torch-harmonics, or makani
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 |
If installation fails, point the user to:
Common issues:
PyTorch CUDA
`sudo apt-get install libeccodes-dev` (Debian/Ubuntu) or `conda install -c conda-forge eccodes`
headers; install via `sudo apt-get install python3-dev`
Official, NVIDIA-verified Agent Skills for Claude Code, Codex, and other coding agents.
Use for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill. Trigger on NVIDIA products, hardware, software,…
Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and…
Use when asked to install, deploy, run, validate, troubleshoot, or stop NVIDIA AI-Q Blueprint infrastructure.
Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.
Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras;…
Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample…