NVIDIA BioNeMo Agent Toolkit
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.
Install
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 --list
The 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.
Skill Catalog
| 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 |
Evaluating NIM Skill Lift
NIM skill evaluation has two levels:
- Hosted skill lift with ACES/SkillEvaluator. Each NIM skill ships a
single, bounded
evals/evals.jsoncase plusevals/config.yml.astra-skill-evalconverts the case into Harbor tasks and runs the same prompt both with and without the skill. The task requires a call to the real hosted NVIDIA NIM endpoint; whether each agent successfully discovers and executes that call is part of the measurement. The ACES default grader combines deterministic trajectory checks with LLM judgments to report skill lift. - Native Harbor tasks (TODO). Deterministic RLVR-style graders are planned
for workflows requiring local GPU deployment, custom scientific scoring, or
additional infrastructure. They are not yet shipped as supported evaluation
coverage. These tasks will live under
evals/harbor/and provide their own verifier.
The hosted lift evaluations require NGC_API_KEY in the invoking shell; each
skill's evals/config.yml passes it into the Harbor tasks. No local NIM
deployment is required. The commands below disable the optional Astra viewer
upload, allow up to twice the default agent runtime, and write reports under
.nv-aces-verify/.
OpenFold3 and the MSA-Search to OpenFold3 workflow are pending validation. Their current hosted runs timed out and should not yet be used for pass/fail or model comparison.
-
Evo 2
ASTRA_HARBOR_VIEWER_UPLOAD=0 astra-skill-eval evaluate nim-skills/evo2-nim --agent-eval -a claude-code --n-attempts 1 --n-concurrent 1 --timeout-multiplier 2.0 --results-dir "$PWD/.nv-aces-verify" -
OpenFold2
ASTRA_HARBOR_VIEWER_UPLOAD=0 astra-skill-eval evaluate nim-skills/openfold2-nim --agent-eval -a claude-code --n-attempts 1 --n-concurrent 1 --timeout-multiplier 2.0 --results-dir "$PWD/.nv-aces-verify" -
OpenFold3 (pending validation)
ASTRA_HARBOR_VIEWER_UPLOAD=0 astra-skill-eval evaluate nim-skills/openfold3-nim --agent-eval -a claude-code --n-attempts 1 --n-concurrent 1 --timeout-multiplier 2.0 --results-dir "$PWD/.nv-aces-verify" -
Boltz-2
ASTRA_HARBOR_VIEWER_UPLOAD=0 astra-skill-eval evaluate nim-skills/boltz2-nim --agent-eval -a claude-code --n-attempts 1 --n-concurrent 1 --timeout-multiplier 2.0 --results-dir "$PWD/.nv-aces-verify" -
DiffDock
ASTRA_HARBOR_VIEWER_UPLOAD=0 astra-skill-eval evaluate nim-skills/diffdock-nim --agent-eval -a claude-code --n-attempts 1 --n-concurrent 1 --timeout-multiplier 2.0 --results-dir "$PWD/.nv-aces-verify" -
GenMol
ASTRA_HARBOR_VIEWER_UPLOAD=0 astra-skill-eval evaluate nim-skills/genmol-nim --agent-eval -a claude-code --n-attempts 1 --n-concurrent 1 --timeout-multiplier 2.0 --results-dir "$PWD/.nv-aces-verify" -
MolMIM
ASTRA_HARBOR_VIEWER_UPLOAD=0 astra-skill-eval evaluate nim-skills/molmim-nim --agent-eval -a claude-code --n-attempts 1 --n-concurrent 1 --timeout-multiplier 2.0 --results-dir "$PWD/.nv-aces-verify" -
RFdiffusion
ASTRA_HARBOR_VIEWER_UPLOAD=0 astra-skill-eval evaluate nim-skills/rfdiffusion-nim --agent-eval -a claude-code --n-attempts 1 --n-concurrent 1 --timeout-multiplier 2.0 --results-dir "$PWD/.nv-aces-verify" -
MSA-Search
ASTRA_HARBOR_VIEWER_UPLOAD=0 astra-skill-eval evaluate nim-skills/msa-search-nim --agent-eval -a claude-code --n-attempts 1 --n-concurrent 1 --timeout-multiplier 2.0 --results-dir "$PWD/.nv-aces-verify" -
ProteinMPNN
ASTRA_HARBOR_VIEWER_UPLOAD=0 astra-skill-eval evaluate nim-skills/proteinmpnn-nim --agent-eval -a claude-code --n-attempts 1 --n-concurrent 1 --timeout-multiplier 2.0 --results-dir "$PWD/.nv-aces-verify" -
MSA-Search to OpenFold3 workflow (pending validation)
ASTRA_HARBOR_VIEWER_UPLOAD=0 astra-skill-eval evaluate nim-skills/meta-skills/msa-structure-prediction-pipeline --agent-eval -a claude-code --n-attempts 1 --n-concurrent 1 --timeout-multiplier 2.0 --results-dir "$PWD/.nv-aces-verify" -
Generative virtual screening workflow
ASTRA_HARBOR_VIEWER_UPLOAD=0 astra-skill-eval evaluate nim-skills/meta-skills/drug-discovery-pipeline --agent-eval -a claude-code --n-attempts 1 --n-concurrent 1 --timeout-multiplier 2.0 --results-dir "$PWD/.nv-aces-verify"
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/.
License
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.