Agent skill · nvidia
openfold2-nim
Use this skill for OpenFold2, NVIDIA's BioNeMo NIM microservice for monomer protein structure prediction. Invoke whenever the user mentions OpenFold2, AlphaFold2-like monomer folding, protein sequence-to-structure prediction, A3M MSAs, mmCIF templates, hosted NVIDIA API calls, or local Docker deployment.
What it needs
About 3k tokens when loaded.
What this skill does
OpenFold2 NIM Predict a single protein-chain structure from an amino-acid sequence, with optional A3M multiple sequence alignments and mmCIF templates. Use this guide for basic hosted/local NIM use; load supplemental files only when the task needs deeper context: references/api.md: exact endpoints, schemas, Docker flags, response fields. references/science.md: model scope, strengths, limitations, and handoffs. references/parameters.md: MSA, template, model-selection, and relax effects. references/validation.md: artifact and scientific sanity checks. references/examples.md: compact hosted/local payload patterns. Choose Mode Ask only when context is unclear: Hosted NVIDIA API or local Docker NIM? Hosted URL: https://health.api.nvidia.com/v1/biology/openfold/openfold2/predict-structure-from-msa-and-template Local URL: http://localhost:8000/biology/openfold/openfold2/predict-structure-from-msa-and-template Local readiness: http://localhost:8000/v1/health/ready Mode difference: hosted and local use the same prediction path except local does not include /v1/. Hosted requests use Authorization: Bearer $NGCAPIKEY; local inference requests use no auth header after readiness. Auth And Environment Do not print API keys. Confirm they exist with shell tests, not echoes. Hosted needs NGCAPIKEY in the request header. Supported local Docker startup uses NGCAPIKEY, or NVIDIAAPIKEY as a fallback, plus LOCALNIMCACHE. A repo-root .env file may be sourced as a local override. Local Docker Use the official OpenFold2 NIM image and mount LOCALNIMCACHE at /opt/nim/.cache. Current docs recommend at least 80 GB disk, 64 GB system RAM, 8 CPU cores, and one supported GPU; the container is roughly 55 GB and first startup downloads about 10 GB of model parameters. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/bionemo-openfold2-nim