From earth2studio
Create Earth2Studio prognostic (time-stepping forecast) model wrappers. Do NOT use for diagnostic models, data sources, or installation.
How this skill is triggered — by the user, by Claude, or both
Slash command
/earth2studio:earth2studio-create-prognostic URL or local path to reference inference script (optional)URL or local path to reference inference script (optional)The summary Claude sees in its skill listing — used to decide when to auto-load this skill
**Do these steps IN ORDER. Do not skip any step.**
BENCHMARK.mdevals/config.ymlevals/environment/Dockerfileevals/environment/setup/bootstrap.shevals/evals.jsonevals/targets/eval_1_target.pyevals/targets/eval_2_target.pyevals/targets/test/eval_1_test_target.pyevals/targets/test/eval_2_test_target.pyreferences/method-templates.pyreferences/pr-body-template.mdreferences/pr-comment-template.mdreferences/skeleton-template.pyreferences/testing-guide.pyreferences/validation-guide.mdskill-card.mdskill.oms.sigDo these steps IN ORDER. Do not skip any step.
earth2studio/models/px/<name>.py with triple inheritancetest/models/px/test_<name>.py with mock testsuv run pytest test/models/px/test_<name>.py -vmake format && make lint⚠️ CRITICAL: Always use
uv runfor Python commands:
- ✅
uv run pytest .../uv run python ...- ❌
pytest .../python ...(missing dependencies)Stuck or wrong output: Do not keep retrying the same fix. Follow Self-Improvement to patch this skill before continuing.
Implement a prognostic model wrapper connecting third-party ML weather models to Earth2Studio. Prognostic models time-integrate forward—given initial state, they predict future states by stepping through time (e.g., 6-hour increments).
| Context | Location |
|---|---|
| Harbor eval | Write to /workspace/output/earth2studio/models/px/... |
Harbor + --copy-repo | Full checkout at /workspace/repo |
| Local clone | Directory with pyproject.toml |
Never read evals/targets/ — grader references only.
Load on demand during the matching step:
| File | Content | Load at |
|---|---|---|
references/skeleton-template.py | Full model skeleton with FILL comments | Steps 3–6 |
references/method-templates.py | Canonical method implementations | Steps 4–6 |
references/testing-guide.py | Test skeleton and mock patterns | Step 7 |
references/validation-guide.md | Comparison scripts, PR, code review | Steps 10–11 |
If $ARGUMENTS provided, use it. Otherwise ask:
Please provide a reference inference script URL/path.
Analyze: packages, architecture, I/O shapes, time step, resolution, checkpoint.
Propose pyproject.toml group (alphabetical, add to all). Every
prognostic model must have an optional dependency extra, even when no packages
are required:
model-name = ["package1>=version", "package2"]
# or, when no additional packages are required:
model-name = []
[CONFIRM] Present dependencies and ask user to approve.
Edit pyproject.toml: add the model extra alphabetically, even if it is
empty, and update the all aggregate.
File: earth2studio/models/px/<lowercase>.py
Required inheritance (all three):
class ModelName(torch.nn.Module, AutoModelMixin, PrognosticMixin):
Required imports:
import numpy as np
import torch
from earth2studio.models.auto import AutoModelMixin, Package
from earth2studio.models.batch import batch_coords, batch_func
from earth2studio.models.px.base import PrognosticMixin
from earth2studio.models.utils import create_coords_from_lat_lon, handshake_dim
from earth2studio.lexicon import E2STUDIO_VOCAB
from earth2studio.utils import check_optional_dependencies
from loguru import logger
SPDX header (required at top of every .py file):
# SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES.
# SPDX-License-Identifier: Apache-2.0
Canonical method order:
__init__ 2. input_coords 3. output_coords (@batch_coords)load_default_package 5. load_model 6. to (optional)__call__ (@batch_func) 9. _default_generatorcreate_iteratorinput_coords rules:
batch: np.empty(0)time: np.empty(0) (dynamic)lead_time: starts at np.timedelta64(0, "h")lat: 90 to -90 (north to south); this is the public Earth2Studio convention even if the source model uses the opposite orderlon: 0 to 360input_coords or output_coordsE2STUDIO_VOCAB (282 entries in earth2studio/lexicon/base.py)output_coords: Use handshake_dim/handshake_coords for input validation, then increment lead_time. Prefer a shared coordinate-check helper and call it from output_coords, __call__, and iterator setup before model execution.
__call__: @batch_func decorated, shape (batch, time, lead_time, var, lat, lon).
Reshape to model format → call model → reshape back.
create_iterator: MUST yield initial condition first (step 0).
Use front_hook/rear_hook for perturbation injection.
load_default_package: Lock HuggingFace URLs: hf://org/repo@commit
load_model: Use package.resolve(), map_location="cpu", eval() mode,
decorate with @check_optional_dependencies().
File: test/models/px/test_<name>.py
Required tests:
| Function | Purpose |
|---|---|
test_<model>_call | Single forward pass (parametrize device/time) |
test_<model>_iter | Iterator produces sequence |
test_<model>_exceptions | Invalid coords raise errors |
test_<model>_package | Real weights (@pytest.mark.package) |
Create PhooModelName dummy matching interface for mock tests.
Run tests:
uv run pytest test/models/px/test_<name>.py -m "not package" -v
uv run pytest test/models/px/test_<name>.py::test_<model>_package --package -v
Do not omit the package test. If arbitrary random inputs are not physically valid for the real checkpoint, use a stable model-appropriate synthetic input while still loading real weights and running a forward pass.
earth2studio/models/px/__init__.py (alphabetical)docs/modules/models_px.rst (alphabetical). This is required for
every new prognostic model so the API docs include the generated page.docs/userguide/about/install.md (alphabetical tab) for the
model extra, even when the extra is empty. Include model-specific notes plus
both pip install earth2studio[model-name] and
uv add earth2studio --extra model-name instructions.CHANGELOG.md under ### Added. This is required for every new
prognostic model.Format and lint:
make format && make lint && make license
Follow references/validation-guide.md. Create uncommitted vanilla, E2S,
comparison, and sanity-check scripts; do not commit generated outputs or images.
Use PR-safe placeholders for plots so the user can upload images manually.
[CONFIRM] User must visually inspect plots before proceeding.
Follow references/validation-guide.md and use:
references/pr-body-template.mdreferences/pr-comment-template.mdBefore creating the PR, verify pyproject.toml has the model extra, the
all extra includes it, install docs include both pip and uv commands, and
docs/modules/models_px.rst plus CHANGELOG.md are updated.
Do not include machine names, absolute paths, device inventory, or uploaded image links in PR text. Use plot placeholders instead.
User: Create IdentityModel - returns input unchanged, 6h step, 181x360, vars: t2m, u10m, v10m, msl
Agent: [reads SKILL.md, creates identity.py with triple inheritance,
creates test_identity.py, runs pytest, runs make format && lint]
User: Add Pangu-Weather wrapper
GitHub: https://github.com/198808xc/Pangu-Weather
Agent: [reads SKILL.md, fetches inference.py, creates pangu.py,
creates test_pangu.py, runs pytest]
@property
def input_coords(self) -> CoordSystem:
return CoordSystem({
"batch": np.empty(0),
"time": np.empty(0),
"lead_time": np.array([np.timedelta64(0, "h")]),
"variable": np.array(["t2m", "u10m", ...]),
# Public Earth2Studio convention is north-to-south latitude.
"lat": np.linspace(90, -90, 181),
"lon": np.linspace(0, 359, 360),
})
@batch_coords()
def output_coords(self, input_coords: CoordSystem) -> CoordSystem:
output = input_coords.copy()
output["lead_time"] = input_coords["lead_time"] + np.timedelta64(6, "h")
return output
def create_iterator(self, x, coords):
yield x, coords # Initial condition (step 0)
while True:
x, coords = self.front_hook(x, coords)
x, coords = self(x, coords)
x, coords = self.rear_hook(x, coords)
yield x, coords
| Error | Solution |
|---|---|
OptionalDependencyFailure | uv add --optional <group> <pkg> |
| Coordinate handshake fails | Check handshake_dim indices match dim position |
| Iterator wrong shapes | Debug reshape logic with random input |
ModuleNotFoundError: pytest | Use uv run pytest not pytest |
DO:
uv run python for ALL Python commandsloguru.logger, never print()torch.nn.Module + AutoModelMixin + PrognosticMixincreate_iteratorfront_hook()/rear_hook() in _default_generatorDON'T:
evals/targets/npx claudepluginhub nvidia/earth2studio --plugin earth2studioBuild deterministic forecast scripts with Earth2Studio (model, data source, IO, inference). Do NOT use for ensemble, diagnostics, data-only fetch, or install.
Packages and builds custom AI models with Cog for deployment on Replicate. Covers cog.yaml, predict.py, GPU/CUDA setup, and Docker image creation.
Build and validate Bayesian models using PyMC 6.x: hierarchical models, MCMC sampling, variational inference, posterior checks, and model comparison (LOO/WAIC).