setup — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited setup (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Help users get their environment ready to run protein design tools.
Run through this checklist when a user encounters setup issues:
| Step | Check | Fix |
|---|---|---|
| 1. Modal CLI | modal --version | pip install modal |
| 2. Modal auth | modal token show | modal setup |
| 3. biomodals | ls biomodals/modal_*.py | git clone https://github.com/hgbrian/biomodals |
| 4. Test | cd biomodals && modal run modal_boltzgen.py --help | See troubleshooting |
Cause: Modal CLI not installed.
Fix:
pip install modalThen restart the terminal or run hash -r.
Cause: Modal not authenticated.
Fix:
modal setupThis opens a browser. Click "Authorize" to complete authentication.
Cause: biomodals repository not cloned or not in correct directory.
Fix:
git clone https://github.com/hgbrian/biomodals
cd biomodalsCause: uvx is an optional wrapper from the uv package. It's not required.
Fix: Run modal directly (recommended):
modal run modal_boltzgen.py --helpOr install uv if you prefer using uvx:
pip install uvpip install modalVerify: modal --version
modal setupThis opens a browser. Click "Authorize".
Verify: modal token show
git clone https://github.com/hgbrian/biomodals
cd biomodalsVerify: ls modal_*.py should show files like modal_boltzgen.py
cd biomodals
modal run modal_boltzgen.py --helpExpected: Usage instructions appear showing --input-yaml, --protocol, --num-designs options.
Once setup is complete, users can:
cd biomodals
# Design binders with BoltzGen (requires YAML config)
modal run modal_boltzgen.py --input-yaml binder.yaml --protocol protein-anything --num-designs 50
# Generate backbones with RFdiffusion (official repo, not biomodals)
python run_inference.py inference.input_pdb=target.pdb contigmap.contigs=[A1-150/0 70-100] inference.num_designs=100
# Validate with Chai
modal run modal_chai1.py --input-faa designs.fastaSet GPU with environment variable:
GPU=L40S modal run modal_boltzgen.py --input-yaml config.yaml --num-designs 50
GPU=A100 modal run modal_chai1.py --input-faa complex.fasta| GPU | VRAM | Best For |
|---|---|---|
| T4 | 16GB | ProteinMPNN, ESM |
| A10G | 24GB | RFdiffusion, Chai |
| L40S | 48GB | BoltzGen, BindCraft |
| A100 | 40-80GB | Large complexes |
Modal offers $30/month in free credits - enough for:
Full documentation: See Getting started
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.