Agent skill · NVIDIA
physicsnemo-discover
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.
What it needs
About 4k tokens when loaded.
What this skill does
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. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills NVIDIA/physicsnemo-discover