Agent skill · nvidia
nvmolkit-usage
Use when writing or debugging nvMolKit Python code for GPU-accelerated RDKit fingerprints, similarity, conformers, clustering, and molecular searches.
What it needs
About 9k tokens when loaded.
What this skill does
nvMolKit usage Purpose GPU-accelerated, batched implementations of common RDKit operations. APIs mirror RDKit where possible but are batch-oriented: they take lists of rdkit.Chem.Mol (or lists of fingerprints) and process them in parallel on one or more GPUs. nvMolKit links against RDKit at build time; inputs and outputs are real RDKit Mol objects. This skill covers the installed Python API. Building nvMolKit from source is out of scope. Where nvMolKit does well Reach for nvMolKit when: The workload is a large batch of molecules processed together (typically thousands or more). The metric is throughput / total wall time across the batch, not per-molecule latency. The same operation is repeated identically across the batch (fingerprinting a library, embedding/minimizing many conformers, bulk pairwise similarity), so the GPU stays saturated. Requirements An NVIDIA GPU with compute capability 7.0 (V100) or higher A CUDA driver compatible with CUDA 12.6+. A working torch install with CUDA support (nvMolKit returns GPU tensors via torch's CUDA array interface). When helping with installation, make the user choose a PyTorch CUDA backend that the host driver supports before installing nvMolKit. nvMolKit's PyPI wheels are built with CUDA Toolkit 12.9 and depend on CUDA 12 runtime packages, but pip/uv can still select a CUDA 13 PyTorch wheel unless the install command says otherwise. Conda: prefer conda-forge pytorch-gpu; pin cuda-version=12.6 or another CUDA version supported by the driver. pip: send the user to the PyTorch install selector or previous-versions page to install torch for a CUDA 12.x backend before installing nvMolKit. uv: install nvMolKit with an explicit backend, e.g. uv pip install --torch-backend=cu128 nvmolkit. Inputs Required: choose an operation and supply molecules or fingerprints from the user's code or molecular dataset. Parse SMILES with RDKit and reject failed parses (None). Molecular operations use RDKit Mol objects. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/bionemo-nvmolkit-usage