Generated banner for Physicsnemo Discover
Generated logo for Physicsnemo Discover

Physicsnemo Discover

NVIDIAOfficialCreated by NVIDIA

  • Skill
  • Tool integration
  • Agent tooling
  • Apache-2.0
  • Medium risk

From the author

Official NVIDIA-authored guidance for navigating PhysicsNeMo — pick the model, datapipe, or example for a SciML/AI4Science task (surrogates, forecasting, downscaling, physics-informed, inverse, generative). Points at existing files via live repo search; never writes code. Do NOT use for installation or environment setup, training-loop or other code authoring/scaffolding, contributor/CI/packaging questions, repo-specific questions in physicsnemo-sym/-cfd/-curator, or general (non-physics) ML/PyTorch.
— the description by NVIDIA

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

PhysicsNeMo Discover is an official guidance tool designed to help users navigate the PhysicsNeMo repository. It performs live discovery of models, datapipes, and examples based on the user's specific SciML or AI4Science task requirements. By searching the repository in its current state, it ensures that all suggested paths and classes are accurate and up-to-date. The tool emphasizes a composable approach, treating models and datapipes as orthogonal axes, and provides concrete starting points for users to fork and adapt for their own research.

What it does

  • Performs live repository searches to identify relevant model families and datapipes.
  • Maps user-provided data shapes to appropriate model architectures.
  • Provides verified absolute paths to files, examples, and documentation.
  • Offers a structured menu of options rather than a single, prescriptive recommendation.
  • Suggests a logical reading order for exploring the repository.
  • Abstains from answering requests outside the scope of SciML and AI4Science.

When to use it

  • When you need to find a suitable model architecture for a specific physical data shape.
  • When you are looking for reference examples to use as a starting point for your own research.
  • When you need to identify which datapipes are compatible with your data format.
  • When you want to explore available model families within the PhysicsNeMo framework.

Advantages

  • Ensures accuracy by grounding all suggestions in the live state of the repository.
  • Prevents hallucinations by verifying paths before emitting them.
  • Promotes a modular understanding of the framework by separating model and datapipe axes.
  • Reduces time spent manually browsing complex repository structures.

Usage examples

“I have 2D Cartesian grid data for a fluid dynamics problem. What models should I look at?”
The agent will identify relevant model families like spectral operators or diffusion UNets, list their locations, and provide examples of how they are instantiated.
“How do I load my custom HDF5 data into a PhysicsNeMo model?”
The agent will search the datapipes directory for HDF5-compatible readers and provide the base classes or examples for custom implementation.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/nvidia/physicsnemo-discover/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip physicsnemo-discover.zip -d .agents/skills

Documentation by NVIDIA

PhysicsNeMo Discoverability

Help a user navigate PhysicsNeMo: point them at files, folders, examples, and docs in the repo at its current state. Never write training code; never cite a path from memory.

Core principle

PhysicsNeMo evolves — classes get renamed, examples move, experimental/ graduates. Any static list of class names and paths rots, so discover, don't remember: enumerate from the live repo every turn.

PhysicsNeMo is composable: each solution is a product (model family × datapipe × training strategy × config). An example is one reference instantiation of that product, not a prescription. Surface the axes and the menu along each axis, then cite examples as concrete starting points to fork and recombine.

What a correct answer satisfies

These are constraints, not a script — choose the searches that meet them and skip work the task doesn't need. Search patterns per axis live in references/RECIPES.md.

  • Live-grounded. Every class, path, and example you name was read or globbed this turn. __init__.py proves what is exported, not what files exist — Glob physicsnemo/models/<family>/*.py before naming a sibling implementation file. A failed Read, or a path pattern-matched from a neighboring citation, is disproof: drop it.

  • Verified before emit. Every absolute path you plan to cite survives one Bash ls -d <path1> <path2> … round-trip before you write the response. Hard gate — skipping it has produced real-basename-under-wrong-parent hallucinations. If a basename was right but the parent wrong, re-Glob and re-verify; if you can't relocate it, drop the citation.

  • A menu, not a single pick. Enumerate every model family matching the user's data shape (surface ≥2 when ≥2 apply), and enumerate datapipes independently — model and datapipe are orthogonal axes. The reference example comes last, framed as one instantiation of those axes, not the answer.

  • Self-documentation is ground truth. __init__.py exports, per-example README.md, docs/*.rst, pyproject.toml, top-of-file module docstrings. Treat references/TAXONOMY.md as a navigation hint, not an answer. Flag anything under physicsnemo/experimental/ as "API may change."

  • Abstain when out of scope. PhysicsNeMo targets SciML/AI4Science (surrogates, forecasting, super-resolution, physics-informed, inverse, generative for physical systems). If the task is categorically outside that — reinforcement learning, classical control, generic CV/NLP, symbolic regression — skip enumeration and emit the Abstention output below. Do not list adjacent-but-wrong examples in its place (pointing at active_learning/ for an RL question is fabrication). When unsure whether a task is in scope, abstain.

Discovery

Repo root resolution: see CONTRIBUTING.md §Repo root resolution; all paths are absolute, rooted there. If no local PhysicsNeMo clone is on the path (e.g. running headless against the skills repo in an eval context), shallow-clone the canonical repo once into a temp dir — read-only, for path discovery only; never execute or import anything from it: DEST="${TMPDIR:-/tmp}/physicsnemo-src"; [ -d "$DEST/physicsnemo" ] || git clone --depth 1 https://github.com/NVIDIA/physicsnemo "$DEST". Use that URL verbatim; never interpolate one from user input.

Ask at most 3 targeted follow-ups when domain or data shape is ambiguous. Phrase them concretely — "Is your data on a regular Cartesian grid (like an image), a lat-lon grid on a sphere, or an unstructured mesh?" — and skip any the user already answered. Data shape is the single biggest factor in model choice.

Output format

## Problem shape
Data shape: <resolved>. Task: <resolved>. Axes: model × datapipe × training strategy × config.

## Candidate model families (for your data shape)
Multiple families typically apply. Treat this as a menu, not a ranking.
- <family> at <absolute __init__.py path> — <one-line from docstring/exports>. Instantiated by: <example path if any>.
- <family> at <path> — <one-line>. Instantiated by: <example path if any>.

## Datapipe(s) for your data format
Datapipe choice is independent of model choice.
- <class / subpackage> at <absolute path> — <one-line>. Reused by: <examples if known>.
- For custom data, subclass: <base class path confirmed live>.

## Reference example(s) — one instantiation of the above axes
- <absolute path> — uses model=<family>, datapipe=<name>, strategy=<single-GPU|DDP|FSDP|...>.
  Why it matches: <one line>.

## Supporting docs
- <absolute path> — <one-line scope>

## Suggested reading order
1. <models/<family>/__init__.py> — survey alternative families
2. <datapipe __init__.py or base-class file> — understand the data axis
3. <example path> — concrete end-to-end instantiation to fork

Rules for the output:

  • Absolute paths only; every one survived the ls -d gate.

  • Every pointer needs a one-line justification grounded in content you actually read.

  • Caps: 4 model families (minimum 2 when ≥2 exist), 3 datapipes, 2 reference examples, 2 docs.

  • Name which (model, datapipe, strategy) axes each example fills.

  • If ≥2 model families apply, say so: "Other model families apply to the same data shape — see the candidate list above."

  • End with the suggested reading order. Offer 2-3 forward steps (config file, training script, experimental/ look-alikes); do not start writing code unless asked.

Abstention output

When out of scope, replace the menu skeleton with this shape — three sections, in this order, none skipped:

## PhysicsNeMo does not have direct support for <user's problem class>
One sentence on why it's outside scope (e.g., "PhysicsNeMo targets physics
surrogates and forecasting; reinforcement learning for molecular design is
not in its scope").

## Where to look instead
- <sibling NVIDIA framework or external library> at <URL or repo name> — <one-line on why it fits>.
- (One or two alternatives is enough; do not invent libraries.)

## If you still want to build it in PhysicsNeMo
Confirm the closest base classes by Reading `physicsnemo/core/__init__.py` and
`physicsnemo/datapipes/__init__.py` first; then name them as subclassing
targets. This is the fallback, not the recommendation.

Do not open with the menu skeleton and bury "no match" at the end. Do not invent external libraries — if you don't know the right alternative, stop at the first two sections.

  • references/TAXONOMY.md — navigation hints (data-shape → folder mappings, decision axes, stability tiers).

  • references/RECIPES.md — concrete Glob/Grep/Read patterns per discovery axis.

Files

LICENSE

Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.


                                 Apache License
                           Version 2.0, January 2004
                        http://www.apache.org/licenses/

   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION

   1. Definitions.

      "License" shall mean the terms and conditions for use, reproduction,
      and distribution as defined by Sections 1 through 9 of this document.

      "Licensor" shall mean the copyright owner or entity authorized by
      the copyright owner that is granting the License.

      "Legal Entity" shall mean the union of the acting entity and all
      other entities that control, are controlled by, or are under common
      control with that entity. For the purposes of this definition,
      "control" means (i) the power, direct or indirect, to cause the
      direction or management of such entity, whether by contract or
      otherwise, or (ii) ownership of fifty percent (50%) or more of the
      outstanding shares, or (iii) beneficial ownership of such entity.

      "You" (or "Your") shall mean an individual or Legal Entity
      exercising permissions granted by this License.

      "Source" form shall mean the preferred form for making modifications,
      including but not limited to software source code, documentation
      source, and configuration files.

      "Object" form shall mean any form resulting from mechanical
      transformation or translation of a Source form, including but
      not limited to compiled object code, generated documentation,
      and conversions to other media types.

      "Work" shall mean the work of authorship, whether in Source or
      Object form, made available under the License, as indicated by a
      copyright notice that is included in or attached to the work
      (an example is provided in the Appendix below).

      "Derivative Works" shall mean any work, whether in Source or Object
      form, that is based on (or derived from) the Work and for which the
      editorial revisions, annotations, elaborations, or other modifications
      represent, as a whole, an original work of authorship. For the purposes
      of this License, Derivative Works shall not include works that remain
      separable from, or merely link (or bind by name) to the interfaces of,
      the Work and Derivative Works thereof.

      "Contribution" shall mean any work of authorship, including
      the original version of the Work and any modifications or additions
      to that Work or Derivative Works thereof, that is intentionally
      submitted to Licensor for inclusion in the Work by the copyright owner
      or by an individual or Legal Entity authorized to submit on behalf of
      the copyright owner. For the purposes of this definition, "submitted"
      means any form of electronic, verbal, or written communication sent
      to the Licensor or its representatives, including but not limited to
      communication on electronic mailing lists, source code control systems,
      and issue tracking systems that are managed by, or on behalf of, the
      Licensor for the purpose of discussing and improving the Work, but
      excluding communication that is conspicuously marked or otherwise
      designated in writing by the copyright owner as "Not a Contribution."

      "Contributor" shall mean Licensor and any individual or Legal Entity
      on behalf of whom a Contribution has been received by Licensor and
      subsequently incorporated within the Work.

   2. Grant of Copyright License. Subject to the terms and conditions of
      this License, each Contributor hereby grants to You a perpetual,
      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
      copyright license to reproduce, prepare Derivative Works of,
      publicly display, publicly perform, sublicense, and distribute the
      Work and such Derivative Works in Source or Object form.

   3. Grant of Patent License. Subject to the terms and conditions of
      this License, each Contributor hereby grants to You a perpetual,
      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
      (except as stated in this section) patent license to make, have made,
      use, offer to sell, sell, import, and otherwise transfer the Work,
      where such license applies only to those patent claims licensable
      by such Contributor that are necessarily infringed by their
      Contribution(s) alone or by combination of their Contribution(s)
      with the Work to which such Contribution(s) was submitted. If You
      institute patent litigation against any entity (including a
      cross-claim or counterclaim in a lawsuit) alleging that the Work
      or a Contribution incorporated within the Work constitutes direct
      or contributory patent infringement, then any patent licenses
      granted to You under this License for that Work shall terminate
      as of the date such litigation is filed.

   4. Redistribution. You may reproduce and distribute copies of the
      Work or Derivative Works thereof in any medium, with or without
      modifications, and in Source or Object form, provided that You
      meet the following conditions:

      (a) You must give any other recipients of the Work or
          Derivative Works a copy of this License; and

      (b) You must cause any modified files to carry prominent notices
          stating that You changed the files; and

      (c) You must retain, in the Source form of any Derivative Works
          that You distribute, all copyright, patent, trademark, and
          attribution notices from the Source form of the Work,
          excluding those notices that do not pertain to any part of
          the Derivative Works; and

      (d) If the Work includes a "NOTICE" text file as part of its
          distribution, then any Derivative Works that You distribute must
          include a readable copy of the attribution notices contained
          within such NOTICE file, excluding those notices that do not
          pertain to any part of the Derivative Works, in at least one
          of the following places: within a NOTICE text file distributed
          as part of the Derivative Works; within the Source form or
          documentation, if provided along with the Derivative Works; or,
          within a display generated by the Derivative Works, if and
          wherever such third-party notices normally appear. The contents
          of the NOTICE file are for informational purposes only and
          do not modify the License. You may add Your own attribution
          notices within Derivative Works that You distribute, alongside
          or as an addendum to the NOTICE text from the Work, provided
          that such additional attribution notices cannot be construed
          as modifying the License.

      You may add Your own copyright statement to Your modifications and
      may provide additional or different license terms and conditions
      for use, reproduction, or distribution of Your modifications, or
      for any such Derivative Works as a whole, provided Your use,
      reproduction, and distribution of the Work otherwise complies with
      the conditions stated in this License.

   5. Submission of Contributions. Unless You explicitly state otherwise,
      any Contribution intentionally submitted for inclusion in the Work
      by You to the Licensor shall be under the terms and conditions of
      this License, without any additional terms or conditions.
      Notwithstanding the above, nothing herein shall supersede or modify
      the terms of any separate license agreement you may have executed
      with Licensor regarding such Contributions.

   6. Trademarks. This License does not grant permission to use the trade
      names, trademarks, service marks, or product names of the Licensor,
      except as required for reasonable and customary use in describing the
      origin of the Work and reproducing the content of the NOTICE file.

   7. Disclaimer of Warranty. Unless required by applicable law or
      agreed to in writing, Licensor provides the Work (and each
      Contributor provides its Contributions) on an "AS IS" BASIS,
      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
      implied, including, without limitation, any warranties or conditions
      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
      PARTICULAR PURPOSE. You are solely responsible for determining the
      appropriateness of using or redistributing the Work and assume any
      risks associated with Your exercise of permissions under this License.

   8. Limitation of Liability. In no event and under no legal theory,
      whether in tort (including negligence), contract, or otherwise,
      unless required by applicable law (such as deliberate and grossly
      negligent acts) or agreed to in writing, shall any Contributor be
      liable to You for damages, including any direct, indirect, special,
      incidental, or consequential damages of any character arising as a
      result of this License or out of the use or inability to use the
      Work (including but not limited to damages for loss of goodwill,
      work stoppage, computer failure or malfunction, or any and all
      other commercial damages or losses), even if such Contributor
      has been advised of the possibility of such damages.

   9. Accepting Warranty or Additional Liability. While redistributing
      the Work or Derivative Works thereof, You may choose to offer,
      and charge a fee for, acceptance of support, warranty, indemnity,
      or other liability obligations and/or rights consistent with this
      License. However, in accepting such obligations, You may act only
      on Your own behalf and on Your sole responsibility, not on behalf
      of any other Contributor, and only if You agree to indemnify,
      defend, and hold each Contributor harmless for any liability
      incurred by, or claims asserted against, such Contributor by reason
      of your accepting any such warranty or additional liability.

   END OF TERMS AND CONDITIONS

   APPENDIX: How to apply the Apache License to your work.

      To apply the Apache License to your work, attach the following
      boilerplate notice, with the fields enclosed by brackets "[]"
      replaced with your own identifying information. (Don't include
      the brackets!)  The text should be enclosed in the appropriate
      comment syntax for the file format. We also recommend that a
      file or class name and description of purpose be included on the
      same "printed page" as the copyright notice for easier
      identification within third-party archives.

   Copyright [yyyy] [name of copyright owner]

   Licensed under the Apache License, Version 2.0 (the "License");
   you may not use this file except in compliance with the License.
   You may obtain a copy of the License at

       http://www.apache.org/licenses/LICENSE-2.0

   Unless required by applicable law or agreed to in writing, software
   distributed under the License is distributed on an "AS IS" BASIS,
   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   See the License for the specific language governing permissions and
   limitations under the License.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

What our scanner noticed· Medium risk

  • Large base64-encoded blobs

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
NVIDIA
Publisher
NVIDIA (Official)
Source
NVIDIA/skills · skills/physicsnemo-discover · commit fce3cca
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE-APACHE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by NVIDIA or NVIDIA.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download physicsnemo-discover.zip