# Openfold2 Nim

Use this skill for OpenFold2, NVIDIA's BioNeMo NIM microservice for monomer protein...

- Repository: https://github.com/NVIDIA/skills (3812 stars)
- Category: DevOps
- License: Apache-2.0 AND CC-BY-4.0
- Last updated: 2026-10-30
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add NVIDIA/skills --skill openfold2-nim -g -a claude-code -y`
Codex: `npx skills add NVIDIA/skills --skill openfold2-nim -g -a codex -y`
Cursor: `npx skills add NVIDIA/skills --skill openfold2-nim -g -a cursor -y`
Gemini CLI: `npx skills add NVIDIA/skills --skill openfold2-nim -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add NVIDIA/skills`

## Description

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.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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
$NGC_API_KEY`; 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 `NGC_API_KEY` in the request header. Supported local Docker
startup uses `NGC_API_KEY`, or `NVIDIA_API_KEY` as a fallback, plus
`LOCAL_NIM_CACHE`. A repo-root `.env` file may be sourced as a local override.

## Local Docker

Use the official OpenFold2 NIM image and mount `LOCAL_NIM_CACHE` 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.

The rest: https://github.com/NVIDIA/skills/blob/HEAD/skills/bionemo-openfold2-nim/SKILL.md