Call NVIDIA BioNeMo NIM agents via API or local Docker to automate life science workflows: predict protein structures, dock small molecules, run generative chemistry, design proteins, and analyze genomics—with support for cluster job management, custom pretraining, and fine-tuning.
Use Boltz2 NIM for biomolecular structure prediction and binding affinity. Invoke for Boltz2, protein structures, protein-ligand/DNA/RNA complexes, SMILES or CCD ligands, pIC50/IC50 affinity scoring, mmCIF output, hosted NVIDIA API calls, or local Docker deployment.
End-to-end Proteina-Complexa design pipeline driver. Reach for this skill whenever the user wants to "design a binder", "design binders for X", "run complexa design", "de novo binder", "PDL1 binder", "TrkA binder", "design proteins for target", "protein binder design", "ligand binder", "design a small-molecule binder", "ATP-binding protein", "AME motif scaffolding", "scaffold a motif near a ligand", "motif + ligand design", "enzyme scaffolding", "flow matching protein design", "beam-search binder", "FK steering", "MCTS protein design", "refold with AF2", "refold with RF3", "refold with ESMFold", or wants success rates, interface pAE, scRMSD, or FoldSeek diversity from a single command. This is the scientific anchor of the skill set: it drives `complexa design <pipeline>` from target picking to manifest emission and tells the user how many designs passed.
Standalone evaluation of an existing PDB directory with Proteina-Complexa. Use this skill whenever the user wants to "evaluate PDB files", "re-fold these designs", "compute interface pAE", "compute i_pLDDT for a folder", "run AF2 / RF3 / ESMFold on my designs", "score binder candidates", "designability of this folder", "scRMSD for designs", "motif RMSD for these PDBs", "complexa analysis", "complexa evaluate from a PDB directory", "evaluate from pdb dir", or score third-party outputs (BindCraft, AlphaProteo, RFdiffusion, hand-curated decoys). It picks the correct `evaluate_*.yaml` config, wires `++dataset.pdb_dir` and the folding backend, runs `complexa analysis` (the evaluate → analyze chain), parses the result CSV, reports pass-rates against the right `result_type` thresholds, and emits a replayable `eval_manifest.json`. Reach for this skill before hand-rolling refolding scripts.
First-time setup, environment configuration, and model-weight installation for Proteina-Complexa. Reach for this skill whenever the user says "set up complexa", "install complexa", "configure my .env", "first-time setup", "what models do I have installed", "what's in my .env", "download model weights", "download Complexa / AF2 / RF3 / ProteinMPNN / LigandMPNN / ESM2 / ESMFold checkpoints", "preflight my GPU", "verify environment", "complexa init", "complexa download", "complexa download --status", "complexa validate env", or any time a fresh checkout needs to be made runnable. This is the first skill to run on a new clone — it drives `complexa init`, `complexa download`, and `complexa validate env` end-to-end, edits the required `.env` keys, picks the right runtime (UV vs Docker), and emits a replayable setup artifact.
Generate and analyze DNA sequences using NVIDIA's Evo 2 BioNeMo NIM microservice. Use for Evo2/Evo 2, DNA generation, genomic sequence generation, hosted generation, local Docker deployment, local forward passes, layer outputs, logits, sampled probabilities, and BioNeMo NIM workflows.
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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 --list
The repo also ships self-hosted plugin marketplaces:
bionemo-agent-toolkit plugin installs through each agent's native plugin
flow as well. Skills are also discoverable by partner harnesses directly from the repo.workflows/ Multi-step meta-skills that compose the skills below
generative_protein_binder_design/ RFdiffusion -> ProteinMPNN -> OpenFold3
nim-skills/ BioNeMo NIM skills (OpenFold, Boltz-2, DiffDock, GenMol,
RFdiffusion, ProteinMPNN, Evo2, MSA-Search, MolMIM, ...)
open-models-skills/ Open-model skills (Proteina-Complexa, KERMT, ...)
library-skills/ CUDA-X library skills (nvMolKit, cuEquivariance, parabricks, ...)
plugins/bionemo-agent-toolkit/ Generated installable plugin (claude + codex
manifests + a copy of every catalog skill)
.claude-plugin/marketplace.json Claude Code marketplace
.agents/plugins/marketplace.json Codex marketplace
skills.sh.json `npx skills add` catalog grouping
Every skill is a directory with a SKILL.md (YAML frontmatter + instructions),
optional references/, and optional scripts/.
This project is dual-licensed:
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.
npx claudepluginhub nvidia-bionemo/bionemo-agent-toolkit --plugin bionemo-agent-toolkitLife sciences computational skills for scientific AI agents — 197 skills covering genomics, proteomics, drug discovery, biostatistics, scientific computing, and scientific writing
1000+ scientific tools (PubMed, UniProt, PubChem, TCGA, FAERS, ClinicalTrials.gov, etc.) + 115 research skills + MCP server + research slash commands.
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces, choose a path, validate your setup, and build practical NVIDIA-powered workflows.
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