A tool for designing proteins at the level of individual atoms, including side chains and small molecules. It uses a diffusion model, which generates candidate structures by gradually refining random starting arrangements.

Designing proteins around small molecules, creating binders, and producing protein, peptide, nanobody, or antibody designs with specified protocols.

It supports designs where the exact placement of atoms matters, such as binding a ligand or achieving a specific binding geometry. YAML configuration files describe the design request.

boltzgen — Skill for Claude Code and Codex by adaptyvbio

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo

git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills

agentmods

npx agentmods add skills/adaptyvbio/protein-design-skills/boltzgen

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/adaptyvbio/protein-design-skills/boltzgen/github.svg)](https://agentmods.dev/skills/adaptyvbio/protein-design-skills/boltzgen)

Your own site

<a href="https://agentmods.dev/skills/adaptyvbio/protein-design-skills/boltzgen"><img src="https://agentmods.dev/badge/skills/adaptyvbio/protein-design-skills/boltzgen/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/adaptyvbio/protein-design-skills/boltzgen"><img src="https://agentmods.dev/badge/skills/adaptyvbio/protein-design-skills/boltzgen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 103 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,244 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00103	$0.02244
Opus 5	$0.00051	$0.01122
Sonnet 5	$0.00021	$0.00449
Haiku 4.5	$0.00010	$0.00224

Measured 12d ago against content hash 6c504d0a2a98, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

boltzgen scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/boltzgen/SKILL.md · 287 lines

How it starts

The opening of the file, as written. The whole thing — 287 lines — stays where its author put it; the contents beside it link to each section on GitHub.

BoltzGen All-Atom Design

Prerequisites

Requirement	Minimum	Recommended
Python	3.11+	3.12
CUDA	12.0+	12.1+
GPU VRAM	24GB	48GB (L40S)
RAM	32GB	64GB

How to run

First time? See Getting started to set up Modal and biomodals.

Option 1: Modal (recommended)

# Clone biomodals
git clone https://github.com/hgbrian/biomodals && cd biomodals

# Run BoltzGen (requires YAML config file)
modal run modal_boltzgen.py \
  --input-yaml binder_config.yaml \
  --protocol protein-anything \
  --num-designs 50

# With custom GPU
GPU=L40S modal run modal_boltzgen.py \
  --input-yaml binder_config.yaml \
  --protocol protein-anything \
  --num-designs 100

GPU: L40S (48GB) recommended | Timeout: 120min default

Available protocols: protein-anything, peptide-anything, protein-small_molecule, nanobody-anything, antibody-anything

Option 2: Local installation

git clone https://github.com/HannesStark/boltzgen.git
cd boltzgen
pip install boltzgen   # or: pip install -e .

# Driven by the boltzgen CLI with a YAML design spec
boltzgen run binder_config.yaml \
  --output out/ \
  --protocol protein-anything \
  --num_designs 50

The first run downloads model weights (~6GB) to ~/.cache. Verify a spec with boltzgen check binder_config.yaml before a full run.

GPU: L40S (48GB) | Time: ~30-60s per design

Key parameters (CLI)

Parameter	Default	Description
`--input-yaml`	required	Path to YAML design specification
`--protocol`	`protein-anything`	Design protocol
`--num-designs`	10	Number of designs to generate
`--steps`	all	Pipeline steps to run (e.g., `design inverse_folding`)

YAML configuration

BoltzGen uses an entity-based YAML format where you specify designed proteins and target structures as entities.

Important notes:

Residue indices use label_seq_id (1-indexed), not author residue numbers
File paths are relative to the YAML file location
Target files should be in CIF format (PDB also works but CIF preferred)
Run boltzgen check config.yaml to verify your specification before running

Read the full file on GitHub · 287 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

references/yaml-spec.md 6.0 KB

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

12d ago First seen · 287 lines · 103 tokens per session scan A 6c504d0a2a98

Subscribe to this mod's changes

boltzgen is a skill published in the GitHub repository adaptyvbio/protein-design-skills (159 stars, last pushed 3mo ago), licensed MIT. It adds 103 tokens to every session and 2,244 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Claude Code Scientific agent-skills all-atom binder design-tools diffusion protein-design protein-engineering sequence-design structure-design

protein-structure-design-boltzgen

All-atom protein design using BoltzGen diffusion model. Use this skill when: (1) Need side-chain aware design from the start, (2) Designing around small molecules or ligands, (3) Want all-atom diffusion (not just backbone), (4) Require precise binding geometries, (5) Using YAML-based configuration. For structure…

PharMolix/OpenBioMed · 89 tokens

bindcraft

End-to-end binder design using BindCraft hallucination. Use this skill when: (1) Designing protein binders with built-in AF2 validation, (2) Running production-quality binder campaigns, (3) Using different design protocols (fast, default, slow), (4) Need joint backbone and sequence optimization, (5) Want high…

FreedomIntelligence/OpenClaw-Medical-Skills · 104 tokens

rfdiffusion

Generate protein backbones using RFdiffusion, a diffusion-based generative model for de novo protein structure generation. Use this skill when: (1) Designing binder scaffolds for a target protein, (2) Generating novel protein backbones from scratch, (3) Scaffolding functional motifs into new proteins, (4) Specifying…

zongtingwei/Bioclaw_Skills_Hub · 130 tokens

boltzgen

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

BoltzGen All-Atom Design

Prerequisites

How to run

Option 1: Modal (recommended)

Option 2: Local installation

Key parameters (CLI)

YAML configuration

What ships with it

What this file has done since we first saw it

Other skills, from other repositories

protein-structure-design-boltzgen

boltzgen

boltzgen

boltzgen

bindcraft

rfdiffusion