Openfold3 Nim

What it does

When your agent uses it

• NVIDIAs BioNeMo NIM microservice for biomolecular structure prediction
• Mentions OpenFold3
• Protein-DNA/RNA
• Multi-chain complex prediction with the hosted NVIDIA API

Example prompts

• “/openfold3-nim”

Requirements

• Python 3
• Docker
• A credential in NGC_API_KEY
• A credential in NVIDIA_API_KEY
• Compatibility (from SKILL.md): requests>=2.28
• Pre-approved tools (allowed-tools): Bash, Read, Write, AskUserQuestion

What it can do on your machine

Read from SKILL.md and the folder at commit 67a13c0. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Bash
  • Read
  • Write
  • AskUserQuestion

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • docker

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Hosts in commands or code, which the agent is likely to contact:

  • health.api.nvidia.com

  Also links to:

  • nvcr.io

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names these keys or tokens, usually read from environment variables:

  • NGC_API_KEY
  • NVIDIA_API_KEY

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  requests>=2.28

  From compatibility in the SKILL.md frontmatter.

Context cost

Openfold3 Nim loads about 1.9k tokens when it runs, and up to ~5.9k if it reads all its reference files. Until then it costs about 101 tokens; SKILL.md has 611 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~101

When it runs · the whole SKILL.md, loaded when a task matches

~1.9k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~5.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

• NotePre-approves every shell command (allowed-tools: Bash)SKILL.md

  allowed-tools: Bash, Read, Write, AskUserQuestion

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from NVIDIA/skills at commit 67a13c0, republished under its Apache-2.0 licence (© NVIDIA). 611 words, ~1,896 tokens.

name

openfold3-nim

description

Use this skill for OpenFold3, NVIDIA's BioNeMo NIM microservice for biomolecular structure prediction. Invoke whenever the user mentions OpenFold3 or needs protein, protein-ligand, protein-DNA/RNA, or multi-chain complex prediction with the hosted NVIDIA API or local Docker NIM. Covers endpoint choice, auth, request payloads, output artifacts, confidence scores, and local container setup.

allowed-tools

Bash, Read, Write, AskUserQuestion

compatibility

requests>=2.28

license

Apache-2.0 AND CC-BY-4.0

set +x

if [ -z "${NGC_API_KEY:-}" ] && [ -n "${NVIDIA_API_KEY:-}" ]; then
  NGC_API_KEY="$NVIDIA_API_KEY"
fi
: "${NGC_API_KEY:?Set NGC_API_KEY or NVIDIA_API_KEY}"
export NGC_API_KEY
: "${LOCAL_NIM_CACHE:?Set LOCAL_NIM_CACHE}"

mkdir -p "${LOCAL_NIM_CACHE}"
chmod 755 "${LOCAL_NIM_CACHE}"

printf '%s\n' "$NGC_API_KEY" | \
  docker login nvcr.io --username '$oauthtoken' --password-stdin && \
docker run --rm --name openfold3 \
  --runtime=nvidia \
  --gpus "device=0" \
  --shm-size=16g \
  -e NGC_API_KEY \
  -v "${LOCAL_NIM_CACHE}:/opt/nim/.cache" \
  -p 127.0.0.1:8000:8000 \
  nvcr.io/nim/openfold/openfold3:latest

until curl -sf http://localhost:8000/v1/health/ready; do sleep 5; done

import os
import requests

hosted = True
url = (
    "https://health.api.nvidia.com/v1/biology/openfold/openfold3/predict"
    if hosted
    else "http://localhost:8000/biology/openfold/openfold3/predict"
)
headers = {"Content-Type": "application/json"}
if hosted:
    headers["Authorization"] = f"Bearer {os.getenv('NGC_API_KEY')}"

seq = "MKTVRQERLKSIVR"
payload = {
    "inputs": [{
        "input_id": "prediction_1",
        "output_format": "pdb",
        "molecules": [{
            "type": "protein",
            "id": "A",
            "sequence": seq,
            "diffusion_samples": 1,
            "msa": {
                "main": {
                    "a3m": {
                        "alignment": f">query\n{seq}",
                        "format": "a3m"
                    }
                }
            }
        }]
    }]
}

response = requests.post(url, headers=headers, json=payload, timeout=300)
response.raise_for_status()
result = response.json()

output = result["outputs"][0]
for i, sample in enumerate(output["structures_with_scores"], start=1):
    fmt = sample["format"]
    with open(f"openfold3_structure_{i}.{fmt}", "w", encoding="utf-8") as fh:
        fh.write(sample["structure"])
    print("confidence_score", sample.get("confidence_score"))
    print("complex_plddt_score", sample.get("complex_plddt_score"))
    print("ptm_score", sample.get("ptm_score"))
    print("iptm_score", sample.get("iptm_score"))
    print("complex_pde_score", sample.get("complex_pde_score"))

© NVIDIA, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 11 other files (references) in skills/bionemo-openfold3-nim of NVIDIA/skills.

• SKILL.md
• BENCHMARK.md
• config/skillspector-baseline.yml
• evals/evals.json
• evals/trigger_evals.json
• references/api.md
• references/examples.md
• references/parameters.md
• references/science.md
• references/validation.md
• skill-card.md
• skill.oms.sig

Open the folder on GitHubat commit 67a13c0

Used in 1 other repository

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in NVIDIA/skills, which our catalogue first saw on October 7, 2026.

• NVIDIA-BioNeMo/bionemo-agent-toolkitnim-skills/openfold3-nimskills/bionemo-agent-toolkit/skills/openfold3-nim