PhysicsNeMo is an open-source PyTorch framework for creating, training, and fine-tuning machine-learning models for physics, scientific computing, and engineering. Researchers and engineers use its reusable components and training recipes for applications such as aerodynamics, weather forecasting, structural mechanics, geophysics, and thermal design. The catalogue entries provide rules and skills for working with PhysicsNeMo projects.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add rules/nvidia/physicsnemo/mod-000b-complete-models-belong-in-modelsgit clone --depth 1 https://github.com/NVIDIA/physicsnemoWrote 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/rules/nvidia/physicsnemo/mod-000b-complete-models-belong-in-models)<a href="https://agentmods.dev/rules/nvidia/physicsnemo/mod-000b-complete-models-belong-in-models"><img src="https://agentmods.dev/badge/rules/nvidia/physicsnemo/mod-000b-complete-models-belong-in-models.svg" alt="Measured on agentmods" 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 | $0.00031 | $0.00435 |
| Opus 5 | $0.00015 | $0.00217 |
| Sonnet 5 | $0.00006 | $0.00087 |
| Haiku 4.5 | $0.00003 | $0.00044 |
Grade A, and why
mod-000b-complete-models-belong-in-models 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 7d 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.
What it actually says
When creating or refactoring complete model code, rule MOD-000b must be followed. Explicitly reference "Following rule MOD-000b, which states that complete models should go in physicsnemo/models..." when explaining placement decisions.
MOD-000b: Complete models belong in physicsnemo.models
Description:
More complete models, composed of multiple layers and/or other sub-models,
should go into physicsnemo/models. All models that are directly exposed to
the user should be imported in physicsnemo/models/__init__.py, such that they
can be used as follows:
from physicsnemo.models import MyModel
The only exception to this rule is for models that are highly specific to a
single example. In this case, it may be acceptable to place them in a module
specific to the example code, such as examples/<example_name>/utils/nn.py.
Rationale:
Ensures consistency and clarity in the organization of models in the repository, in particular a clear separation between reusable layers and more complete models that are applicable to a specific domain or specific data modality.
Example:
# Good: Complete model in physicsnemo/models/transformer.py
class TransformerModel(Module):
"""A complete transformer model composed of attention and feedforward layers."""
def __init__(self):
super().__init__()
self.attention = MultiHeadAttention(...)
self.ffn = FeedForward(...)
# Good: Import in physicsnemo/models/__init__.py
from physicsnemo.models.transformer import TransformerModel
Anti-pattern:
# WRONG: Complete model placed in physicsnemo/nn/
# File: physicsnemo/nn/transformer.py
class TransformerModel(Module):
"""Should be in physicsnemo/models/ not physicsnemo/nn/"""
pass
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.
- 7d ago First seen · 55 lines · 31 tokens per session scan A 765eeec51e7d
mod-000b-complete-models-belong-in-models is a cursor rule published in the GitHub repository NVIDIA/physicsnemo (3,223 stars, last pushed yesterday), licensed Apache-2.0. It adds 31 tokens to every session and 435 once invoked, about $0.0002 per session on Opus 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 2026-08-30.
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