Turn any agent into a life science expert with NVIDIA BioNeMo skills.
Protein folding, molecular docking, generative chemistry, genomics analysis, protein design, and biomarker discovery — a decade of NVIDIA life sciences libraries, tools, and models, packaged as ready-to-call agent skills.
Each skill gives a coding or scientific agent structured instructions, scripts, and references to select a tool, prepare inputs, run it, inspect outputs, and explain results — across both single tasks and multi-step scientific workflows.
Skills install with the skills CLI:
# interactive — pick a skill + install destination
npx skills add NVIDIA-BioNeMo/bionemo-agent-toolkit
# one skill, no prompts
npx skills add NVIDIA-BioNeMo/bionemo-agent-toolkit --skill boltz2-nim --yes
# target a specific agent (repeatable)
npx skills add NVIDIA-BioNeMo/bionemo-agent-toolkit --skill boltz2-nim --agent claude-code
npx skills add NVIDIA-BioNeMo/bionemo-agent-toolkit --skill boltz2-nim --agent codex
# browse the catalog without installing
npx skills add NVIDIA-BioNeMo/bionemo-agent-toolkit --listThe repo also ships self-hosted plugin marketplaces:
- Codex: .agents/plugins/marketplace.json
- Claude Code: .claude-plugin/marketplace.json
so the
bionemo-agent-toolkitplugin installs through each agent's native plugin flow as well. Skills are also discoverable by partner harnesses directly from the repo.
| Product | Description | Skills |
|---|---|---|
| Protein Binder Design | End-to-end de novo binder design workflows — a NIM route and a Proteina-Complexa route. | protein-binder-design, complexa-binder-design |
| Generative Virtual Screening workflow | Generate candidate molecules, dock them to a target, and score binding affinity (GenMol → DiffDock → Boltz-2). | drug-discovery-pipeline |
| MSA-enabled protein structure prediction workflow | Build a multiple sequence alignment, then predict structure (MSA-Search → OpenFold3). | msa-structure-prediction-pipeline |
| Boltz-2 | Biomolecular structure prediction + binding affinity (NIM). | boltz2-nim |
| DiffDock | Small-molecule docking and binding-pose prediction (NIM). | diffdock-nim |
| Evo 2 | DNA sequence generation and variant scoring (NIM). | evo2-nim |
| GenMol | De novo molecule generation, scaffold decoration, lead optimization (NIM). | genmol-nim |
| MolMIM | Latent-space small-molecule generation and optimization (NIM). | molmim-nim |
| MSA-Search | Multiple sequence alignments via ColabFold (NIM). | msa-search-nim |
| OpenFold2 | Monomer protein structure prediction (NIM). | openfold2-nim |
| OpenFold3 | Biomolecular complex structure prediction (NIM). | openfold3-nim |
| ProteinMPNN | Inverse folding / sequence design for a target backbone (NIM). | proteinmpnn-nim |
| RFdiffusion | De novo protein backbone and binder design (NIM). | rfdiffusion-nim |
| Proteina-Complexa | Protein binder design for protein and small molecule targets. Combines a pretrained flow-based generative model (built on La-Proteina) with inference-time optimization for high-quality binder generation. | complexa-setup, complexa-target, complexa-design, complexa-sweep, complexa-evaluate-pdbs, complexa-slurm |
| KERMT | Pretrained graph neural network for molecular property prediction (ADMET). Multi-task extension of GROVER with accelerated data loading via cuik-molmaker. SOTA on real-world ADMET data. | kermt-setup, kermt-infer, kermt-embed, kermt-finetune, kermt-continue-pretrain, kermt-pretrain-scratch, kermt-add-cmim-pretrain, kermt-monitor |
| Parabricks | Agent-ready skills built on Parabricks for accelerated genomic analysis and workflows. | parabricks, genomics-workflow-acceleration |
| nvMolKit | GPU-accelerated cheminformatics library for molecular fingerprinting, Tanimoto/cosine similarity, Butina clustering, conformer generation (ETKDGv3), MMFF geometry optimization, and substructure search. | nvmolkit-usage |
| cuEquivariance | Build equivariant neural-network primitives (segmented tensor products, CG coefficients). | cuequivariance |
Every skill is a directory with a SKILL.md (YAML frontmatter + instructions),
optional references/, and optional scripts/. The generated, installable plugin
lives in plugins/bionemo-agent-toolkit/.
This project is dual-licensed:
- Source code (scripts, tests, build tooling): Apache-2.0
- Skills and documentation (SKILL.md, workflows, READMEs): CC-BY-4.0
See LICENSE for the full dual-license statement. Individual skills may reference third-party data sources with their own terms; consult each skill's references and the NOTICE file.