Borrowing it
Nothing to install: this file belongs to AMDResearch/ai4science-studio. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/AMDResearch/ai4science-studio/main/.cursor/skills/ai4science-earth-science/SKILL.mdgit clone --depth 1 https://github.com/AMDResearch/ai4science-studioWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/amdresearch/ai4science-studio/ai4science-earth-science)<a href="https://agentmods.dev/skills/amdresearch/ai4science-studio/ai4science-earth-science"><img src="https://agentmods.dev/badge/skills/amdresearch/ai4science-studio/ai4science-earth-science/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/amdresearch/ai4science-studio/ai4science-earth-science"><img src="https://agentmods.dev/badge/skills/amdresearch/ai4science-studio/ai4science-earth-science.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00049 | $0.00577 |
| Opus 5.5 | $0.00020 | $0.00231 |
| Sonnet 5.5 | $0.00010 | $0.00115 |
| Haiku 4.5 | $0.00005 | $0.00058 |
Grade A, and why
ai4science-earth-science scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 30 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Earth science domain
Scope
The earth_science/ domain covers climate, weather, and broader Earth-system machine learning: gridded fields, forecasting, downscaling, remote sensing, geospatial tensors, reanalysis-style inputs, etc. Do not create separate top-level climate or weather trees.
Layout
- Models:
earth_science/models/<model-slug>/ - Template:
_template/(repo root) - Conventions:
earth_science/models/README.md
Agent guidance
- Place new Earth-related HF models under
earth_science/models/unless the model clearly fits another domain better (e.g. pure protein LM →protein_folding/). - Recipes should state spatial/temporal resolution, coordinate conventions if relevant, and data sources (ERA5, satellite products, etc.) without bundling large raw archives in git.
- When suggesting AMD-specific notes, keep them optional and tied to tested stack versions (e.g. PyTorch + ROCm).
- Institutional AMD clusters and data staging (Globus, Constellation DOI pages, Hugging Face Hub CLI) onto shared filesystems are in-scope for recipe text; align guidance with gridded / reanalysis-style datasets and citation requirements.
- For models whose authoritative code lives on GitHub (e.g. ORBIT-2 under
earth_science/models/ORBIT-2/), the Studio may addexamples/with thin Python or SLURM scripts that delegate to upstream entry points (samecwd/PYTHONPATH/ scheduler layout upstream expects). Do not copy large upstream training or distributed inference files into Studio—wrappers plus recipe links stay maintainable. - Distributed inference on cluster jobs must match upstream assumptions (e.g. SLURM task count vs YAML parallelism product). Site-specific partition and account names (e.g. HPCFund-style queues) belong in comments or placeholders, not hard-coded secrets.
Model-specific HPC notes
Per-model overlay sizes, --no-deps lists, ORBIT-2 training landmines, and weather-stack data blockers: reference/models.md. Shared Apptainer/Docker patterns: ai4science-studio/reference/rocm.md.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed · -82 lines · -1 tokens per session scan C → A 2ca4eeb49e57
- 2mo ago First seen · 112 lines · 50 tokens per session scan C 817291c3a4aa
ai4science-earth-science is a skill published in the GitHub repository AMDResearch/ai4science-studio (4 stars, last pushed yesterday), licensed MIT. It adds 49 tokens to every session and 577 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
ai4science-earth-science compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ai4science-earth-scienceAMDResearch/ai4science-studio | Skill | 4 | yesterday | MIT | A | 49 | Cursor |
| batch-processing-clinical-textmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 161 | Claude Code |
| exporting-to-fhirmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 163 | Claude Code |
| choosing-openmed-modelsmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 134 | Claude Code |
| extracting-clinical-entitiesmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 118 | Claude Code |
| loading-openmed-modelsmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 118 | Claude Code |
| normalizing-rxnormmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 187 | Claude Code |