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Earth2Studio Data Fetch Skill · nvidia | DecimalAI

scienceby nvidia

Earth2Studio Data Fetch Skill

nvidia/earth2studio-data-fetch

Source nvidia/skills ↗License Apache-2.0

Fetch weather/climate data via Earth2Studio data sources for specific variables and times.

SkillScore86Maintained

Automatic

Data Engineer pack

Last verified 8/12/2026

What it changes

Passed 17 of 20 test cases with the skill, and 13 of 20 without it.

Without skill64%

With skill86%

Checks it passed that the model alone missed

The response identifies `WB2ERA5_32x64` as a coarse-resolution alternative.
The script instantiates forecast sources using classes with the `_FX` suffix.
The response maps the variables to Earth2Studio standard names `t2m` and `z500`.

and 4 more in the full report

6 fixed13 passed either way2 still failing1 broke

Pass-rate lift: +23 pp
Tokens: +92%
Agent turns: 0%
Response time: -18%

Model gemini-3.6-flashMeasured 8/12/2026v119 of 22 cases passed with skill · 20 comparable

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/nvidia-earth2studio-data-fetch/SKILL.md https://app.decimal.ai/s/nvidia-earth2studio-data-fetch/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add nvidia-earth2studio-data-fetch, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/nvidia-earth2studio-data-fetch/ and pins it in .decimal/skills.lock

decimalai skills add nvidia-earth2studio-data-fetch

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/nvidia-earth2studio-data-fetch/SKILL.md https://app.decimal.ai/s/nvidia-earth2studio-data-fetch/SKILL.md

Raw file: /s/nvidia-earth2studio-data-fetch/SKILL.md ↗ · machine-readable summary at /s/nvidia-earth2studio-data-fetch.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 6

Prompt

Which Earth2Studio forecast source class provides ensemble forecasts from NCEP, and what suffix distinguishes forecast sources from analysis sources?

What was checked, without and with the skill
Checked	Without skill	With skill
The response identifies `GEFS_FX` as the NCEP ensemble forecast data source class.	Missed	Passed

case-16 · gemini-3.6-flash · 8/12/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md229 linessingle file

Earth2Studio Data Fetch Skill

Purpose

Guide a user through downloading weather/climate data via Earth2Studio data source APIs. Identifies compatible sources by checking the lexicon, verifies variable support, and produces a working fetch script outputting an xarray DataArray.

Prerequisites

Earth2Studio installed (uv pip install earth2studio or equivalent)
Network access to remote data stores (GCS, S3, CDS API, etc.)
For CDS-based sources: valid CDS API key configured (~/.cdsapirc)
Python 3.10+

Instructions

You are helping a user download specific weather/climate data using Earth2Studio's data source APIs. Your job is to identify which data source(s) can provide the requested variables, verify compatibility via the lexicon system, and produce a working fetch script.

Core principle: live docs and lexicon are the source of truth

Data source APIs, available variables, and the lexicon evolve between releases. Before recommending a data source or writing a fetch script:

Fetch the relevant data source doc page to confirm the API signature and constructor arguments.
Check the lexicon to verify the requested variable is supported by that data source.

Live doc references (fetch only what the user's request requires):

Analysis data sources: https://nvidia.github.io/earth2studio/modules/datasources_analysis.html
Forecast data sources: https://nvidia.github.io/earth2studio/modules/datasources_forecast.html
DataFrame data sources: https://nvidia.github.io/earth2studio/modules/datasources_dataframe.html

Track record

Benchmark

17 / 20

test cases passed, vs 13 / 20 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

nvidia / skills

skills/earth2studio-data-fetch/SKILL.md

View on GitHub ↗

License Apache-2.0Imported 8/3/2026Version v1

More skills from the same source and nearby in the registry, with their headline benchmark lift.

Ready to supercharge your AI agents?

See it in action

What's inside

Earth2Studio Data Fetch Skill

Purpose

Prerequisites

Instructions

Core principle: live docs and lexicon are the source of truth

Track record

Benchmark

Adoption

SkillSafety

Source

Related skills