Official agent skill

Genmol Nim

by NVIDIA in NVIDIA/skills

Generate novel drug-like molecules using the GenMol NIM microservice.

OfficialApache-2.0Auto-check: notesDevOps & Cloud

Install Genmol Nim

skills CLI
$ npx skills add NVIDIA/skills --skill genmol-nim -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install NVIDIA/skills genmol-nim --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/bionemo-genmol-nim .claude/skills/genmol-nim && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
genmol-nim
GitHub stars
3.5k
Used in
1 other repo
Token cost
~1.4k tokens
SKILL.md length
504 words
Files
13 (incl. references)
Skills in repo
380
Repo updated
First seen
Licence
Apache-2.0

At a glance

Generate novel drug-like molecules using the GenMol NIM microservice.

  • De novo generation
  • SKILL.md covers Choose Mode, Local Docker, SAFE Input and Request Pattern, plus 2 more sections
  • Calls docker; reaches health.api.nvidia.com; needs NGC_API_KEY and NVIDIA_API_KEY
  • Scaffold decoration

What it does

Genmol Nim is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Generate novel drug-like molecules using the GenMol NIM microservice. Use for de novo generation, scaffold decoration, motif extension, lead optimization, SAFE notation, QED or LogP ranking, hosted NVIDIA API calls, or local Docker deployment. GenMol takes SAFE notation in the smiles field, not ordinary SMILES.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 15 other files, including reference files (for example `BENCHMARK.md`, `config/skillspector-baseline.yml` and `evals/config.yml`). Compatibility notes: safe-mol=0.1.14; requests=2.28

It sits in DevOps & Cloud, covering Drug discovery and cheminformatics, Containers and Microservices. It works with NVIDIA AI Platform and Docker. The repository describes itself as: Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end. The licence is Apache-2.0.

When your agent uses it

  • De novo generation
  • Scaffold decoration
  • Motif extension
  • Lead optimization

Example prompts

  • “/genmol-nim”

Requirements

  • Python 3
  • Docker
  • A credential in NGC_API_KEY
  • A credential in NVIDIA_API_KEY
  • Compatibility (from SKILL.md): safe-mol>=0.1.14; 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 0e0d506. 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

    safe-mol>=0.1.14; requests>=2.28

    From compatibility in the SKILL.md frontmatter.

Context cost

Genmol Nim loads about 1.4k tokens when it runs, and up to ~4.5k if it reads all its reference files. Until then it costs about 81 tokens; SKILL.md has 504 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~81
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.5k

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

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • 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 0e0d506, republished under its Apache-2.0 licence (© NVIDIA). 504 words, ~1,358 tokens.

Download SKILL.mdSave it as .claude/skills/genmol-nim/SKILL.md (or your agent's skills folder). This skill also uses 12 other files; get the full folder from GitHub.
name
genmol-nim
description
Generate novel drug-like molecules using the GenMol NIM microservice. Use for de novo generation, scaffold decoration, motif extension, lead optimization, SAFE notation, QED or LogP ranking, hosted NVIDIA API calls, or local Docker deployment. GenMol takes SAFE notation in the smiles field, not ordinary SMILES.
allowed-tools
Bash, Read, Write, AskUserQuestion
compatibility
safe-mol>=0.1.14; requests>=2.28
license
Apache-2.0 AND CC-BY-4.0

GenMol NIM

Generate drug-like molecules with GenMol. Use this guide for first-pass hosted and local usage; load supplemental files only when needed:

  • references/api.md: endpoints, schema, Docker flags, response fields.
  • references/science.md: use cases, strengths, limits, and handoffs.
  • references/parameters.md: SAFE patterns and tuning effects.
  • references/validation.md: chemical and artifact checks.
  • references/examples.md: compact request patterns.

Choose Mode

Ask only when context is unclear:

Hosted NVIDIA API or local Docker NIM?

  • Hosted: https://health.api.nvidia.com/v1/biology/nvidia/genmol/generate
  • Local: http://localhost:8000/generate

Hosted requests use Authorization: Bearer $NGC_API_KEY. For local Docker, authenticate image pulls with docker login nvcr.io using NGC_API_KEY (or NVIDIA_API_KEY via the preflight). Pass -e NGC_API_KEY into the container for entitlement checks and first-run model downloads. Local inference requests use no auth header after readiness, so bind the published port to loopback with -p 127.0.0.1:8000:8000. Warm-cache key-free startup varies by image version and should not be assumed.

Local Docker

Use credentials already supplied in the shell environment or injected by a secret manager. Do not load credential files, print keys, or enable shell tracing. For local setup answers, include this sequence: env preflight, docker login with --password-stdin, docker run, readiness loop, then a no-auth localhost request. Do not invent a cache default or drop the NVIDIA_API_KEY fallback.

Before executing local setup, explain that registry authentication sends the key to the NVIDIA registry at https://nvcr.io and first-run model downloads use about 20 GB in LOCAL_NIM_CACHE. Execute deployment only when the user requests it; for a setup guide, provide the commands without running them.

For the exact startup preflight (environment checks, NVIDIA_API_KEY fallback, --shm-size=2G, both --ulimit flags, docker login, and the docker run for nvcr.io/nim/nvidia/genmol:1.0.1), copy the command block in references/api.md under Local container startup verbatim.

GenMol is single-GPU; NIM_TEST_GPU defaults to 0. Wait for readiness:

bash
until curl -sf http://localhost:8000/v1/health/ready; do sleep 5; done
Show full SKILL.md (220 more words)Show less

SAFE Input

The API field is named smiles, but GenMol expects SAFE notation. Masked positions use [*{min-max}].

  • De novo: safe_input = "[*{20-30}]"
  • Scaffold decoration: safe_input = scaffold_to_safe("C1CC(=O)NC1", 10, 15)
  • Motif extension: safe_input = f"[*{{5-10}}].{motif_safe}.[*{{5-10}}]"
  • Lead optimization: encode the hit, then replace a fragment with .[*{5-12}]

Use safe-mol for conditioned generation. Simple ring scaffolds may raise SAFEFragmentationError; fall back to the original SMILES plus a SAFE mask.

See the scaffold_to_safe helper in references/examples.md under Scaffold Decoration.

Wider masks increase diversity; tight masks keep analog size more predictable.

Request Pattern

python
import os
import requests

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

payload = {
    "smiles": "[*{20-30}]",  # SAFE notation
    "num_molecules": 30,
    "temperature": "1",      # string, not float
    "noise": "1",            # string, not float
    "step_size": 1,
    "scoring": "QED",        # or "LogP"
    "unique": False,
}

response = requests.post(url, headers=headers, json=payload, timeout=180)
response.raise_for_status()
result = response.json()

Gotchas:

  • temperature and noise are strings.
  • num_molecules is 1-1000; invalid/duplicate molecules may be filtered, so request extra when the user needs a minimum count.
  • scoring is "QED" for drug-likeness or "LogP" for lipophilicity.
  • Set unique=True for deduplicated analog lists.

Save And Report Output

Sort molecules by score, print the top ranks, and write a .smi file as shown in references/examples.md under Save Ranked Results. For chemical validity, uniqueness, PAINS/alerts, and visualization with RDKit, read references/validation.md.

Limits And Troubleshooting

  • Fewer molecules than requested is expected after filtering.
  • Invalid SAFE strings cause status: "failed" or validation errors.
  • Install safe-mol only for scaffold, motif, or lead-optimization workflows; de novo masks work without conversion.
  • Local startup downloads about 20 GB into LOCAL_NIM_CACHE.
  • Container issues: confirm nvidia-smi, NVIDIA Container Toolkit, and --runtime=nvidia; use NIM_TEST_GPU to choose the single visible GPU.

© 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 12 other files (references) in skills/bionemo-genmol-nim of NVIDIA/skills.

  • SKILL.md
  • BENCHMARK.md
  • config/skillspector-baseline.yml
  • evals/config.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 0e0d506

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.

Compare with similar skills

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Setup Workshopbrevdev/workshop-build-an-agent143—~2.3kAutomated safety check: NotesApache-2.0

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Questions about Genmol Nim

What does Genmol Nim do?

Generate novel drug-like molecules using the GenMol NIM microservice. Genmol Nim is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Generate novel drug-like molecules using the GenMol NIM microservice.

When should I use Genmol Nim?

Genmol Nim fits situations like: de novo generation; scaffold decoration; motif extension; lead optimization.

How do I install Genmol Nim in Claude Code?

Run `npx skills add NVIDIA/skills --skill genmol-nim -a claude-code`. Or copy the skill folder (skills/bionemo-genmol-nim in NVIDIA/skills) into .claude/skills/genmol-nim in your project. Claude Code loads it when a task matches its description.

How do I install Genmol Nim in Codex?

Run `npx skills add NVIDIA/skills --skill genmol-nim -a codex`. Or copy the skill folder (skills/bionemo-genmol-nim in NVIDIA/skills) into .agents/skills/genmol-nim in your project. Codex loads it when a task matches its description.

Can I use Genmol Nim in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/skills --skill genmol-nim -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/genmol-nim, .gemini/skills/genmol-nim, .github/skills/genmol-nim and .opencode/skills/genmol-nim in your project.

What does Genmol Nim need to run?

Going by SKILL.md and its folder, Genmol Nim needs the command-line tools its instructions call (docker) and credentials named NGC_API_KEY and NVIDIA_API_KEY. Our summary lists: Python 3; Docker; A credential in NGC_API_KEY; A credential in NVIDIA_API_KEY. Its frontmatter pre-approves these tools: Bash, Read, Write, AskUserQuestion. Compatibility (from SKILL.md): safe-mol>=0.1.14; requests>=2.28.

Does Genmol Nim access the network?

SKILL.md names 2 domains. In commands or code: health.api.nvidia.com; the agent is likely to contact it when it follows the instructions. As links in the text: nvcr.io. This is read from the text; nothing was executed.

Is Genmol Nim safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Genmol Nim use?

Genmol Nim is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Genmol Nim use?

About 1.4k tokens (SKILL.md is roughly 5.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.1k tokens, read only when the agent opens those files.

What are the alternatives to Genmol Nim?

Skills that share tags, products or a category with Genmol Nim: Frontmcp Deployment (agentfront/frontmcp, 146 stars), Model Download Dev (open-edge-platform/edge-ai-libraries, 168 stars), Time Series Analytics Dev (open-edge-platform/edge-ai-libraries, 168 stars) and Supabase (magnus919/agent-skills, 111 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Genmol Nim?

NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/skills, which has 3,534 GitHub stars. The repository holds 380 skills in this directory. The repository was last updated on October 7, 2026.

Source: NVIDIA/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.