Agent skill

Boltz

A skill your agent uses when predicting biomolecular structures (proteins, RNA, DNA, ligands) with the open-source Boltz diffusion model as an alternative to AlphaFold3.

Apache-2.0Auto-check passedAI & LLM Engineering

Install Boltz

skills CLI

$ npx skills add lamm-mit/scienceclaw --skill boltz -a claude-code

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

GitHub CLI

$ gh skill install lamm-mit/scienceclaw boltz --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/lamm-mit/scienceclaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/boltz .claude/skills/boltz && 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/

Paste into Claude Code

Install the "boltz" agent skill from https://github.com/lamm-mit/scienceclaw/tree/main/skills/boltz into .claude/skills/boltz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "boltz", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/lamm-mit/scienceclaw/tree/main/skills/boltz

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add lamm-mit/scienceclaw --skill boltz -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install lamm-mit/scienceclaw boltz --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/lamm-mit/scienceclaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/boltz .agents/skills/boltz && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "boltz" agent skill from https://github.com/lamm-mit/scienceclaw/tree/main/skills/boltz into .agents/skills/boltz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "boltz", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add lamm-mit/scienceclaw --skill boltz -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install lamm-mit/scienceclaw boltz --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/lamm-mit/scienceclaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/boltz .cursor/skills/boltz && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "boltz" agent skill from https://github.com/lamm-mit/scienceclaw/tree/main/skills/boltz into .cursor/skills/boltz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "boltz", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/lamm-mit/scienceclaw.git --path skills/boltz

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add lamm-mit/scienceclaw --skill boltz -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install lamm-mit/scienceclaw boltz --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/lamm-mit/scienceclaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/boltz .gemini/skills/boltz && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "boltz" agent skill from https://github.com/lamm-mit/scienceclaw/tree/main/skills/boltz into .gemini/skills/boltz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "boltz", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install lamm-mit/scienceclaw boltz

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add lamm-mit/scienceclaw --skill boltz -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/lamm-mit/scienceclaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/boltz .github/skills/boltz && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "boltz" agent skill from https://github.com/lamm-mit/scienceclaw/tree/main/skills/boltz into .github/skills/boltz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "boltz", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add lamm-mit/scienceclaw --skill boltz -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install lamm-mit/scienceclaw boltz --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/lamm-mit/scienceclaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/boltz .opencode/skills/boltz && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "boltz" agent skill from https://github.com/lamm-mit/scienceclaw/tree/main/skills/boltz into .opencode/skills/boltz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "boltz", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: boltz
GitHub stars: 244
Token cost: ~879 tokens
SKILL.md length: 123 words
Files: 1
Skills in repo: 85
Repo updated: Aug 21, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

A skill your agent uses when predicting biomolecular structures (proteins, RNA, DNA, ligands) with the open-source Boltz diffusion model as an alternative to AlphaFold3.

Predicting biomolecular structures (proteins
SKILL.md covers Requirements, Installation, Input Format (YAML) and Running Predictions, plus 6 more sections
Calls pip and python3
Ligands) with the open-source Boltz diffusion model as an alternative to AlphaFold3

What it does

Boltz is an agent skill from lamm-mit/scienceclaw. Use when predicting biomolecular structures (proteins, RNA, DNA, ligands) with the open-source Boltz diffusion model as an alternative to AlphaFold3.

Its SKILL.md is about 880 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Diffusion and image models. The licence is Apache-2.0.

When your agent uses it

Predicting biomolecular structures (proteins
Ligands) with the open-source Boltz diffusion model as an alternative to AlphaFold3

Example prompts

“/boltz”

Requirements

Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit ab9aba1. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- pip
- python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Boltz loads about 879 tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 123 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~39
When it runs · the whole SKILL.md, loaded when a task matches: ~879

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 passed

The automated check found no risky patterns in SKILL.md.

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 lamm-mit/scienceclaw at commit ab9aba1, republished under its Apache-2.0 licence (© lamm-mit). 123 words, ~879 tokens.

Download SKILL.mdSave it as .claude/skills/boltz/SKILL.md (or your agent's skills folder).

name: boltz
description: Use when predicting biomolecular structures (proteins, RNA, DNA, ligands) with the open-source Boltz diffusion model as an alternative to AlphaFold3.

Boltz Structure Prediction

Predict biomolecular structures using Boltz, an open-source diffusion model. Boltz handles proteins, RNA, DNA, small molecules, ions, and covalent modifications in a single model without requiring multiple sequence alignments (MSA-optional). It serves as a strong open-source alternative to AlphaFold3.

Requirements

Python 3.10+
24 GB GPU VRAM minimum (A10G/A100 recommended)
~10 GB disk for model weights

Installation

bash

pip install boltz

Input Format (YAML)

Boltz uses YAML for flexible entity specification:

yaml

# complex.yaml — protein + ligand
version: 1
sequences:
  - protein:
      id: A
      sequence: MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSY...
  - ligand:
      id: B
      smiles: "CC1=CC=C(C=C1)S(=O)(=O)N"  # or CCD code
      ccd: ATP  # alternative: use CCD code

# binder-target complex
version: 1
sequences:
  - protein:
      id: [A, B]  # homodimer
      sequence: MTEYKLVVVGAGGVGKS...
      count: 2
  - protein:
      id: C
      sequence: EVQLVESGGGLVQPGG...  # binder

Running Predictions

bash

# Single prediction
boltz predict complex.yaml \
    --out_dir results/ \
    --accelerator gpu \
    --devices 1 \
    --num_workers 4

# Batch prediction (multiple YAML files)
boltz predict inputs/ \
    --out_dir results/ \
    --accelerator gpu

# Without MSA (faster, slightly lower accuracy for monomers)
boltz predict complex.yaml \
    --out_dir results/ \
    --use_msa_server false

Python API

python

from boltz.main import predict

predict(
    data="complex.yaml",
    out_dir="results/",
    accelerator="gpu",
    devices=1,
    num_predictions=1,  # ensemble size
    recycling_steps=3,
    diffusion_samples=1
)

Output Files

results/
  boltz_results_complex/
    predictions/
      complex/
        complex_model_0.cif          # Predicted structure (CIF format)
        complex_confidence_model_0.json  # Confidence scores
    lightning_logs/                  # Training logs (ignore)

Confidence Metrics

python

import json

with open("complex_confidence_model_0.json") as f:
    conf = json.load(f)

# Key metrics
plddt = conf["plddt"]                    # Per-residue confidence (0-100)
ptm = conf["ptm"]                        # Global fold confidence (0-1)
iptm = conf["iptm"]                      # Interface confidence (0-1)
ligand_iptm = conf.get("ligand_iptm")    # Ligand interface confidence
pde = conf.get("pde")                    # Predicted Distance Error

print(f"pTM={ptm:.3f}, ipTM={iptm:.3f}")

Quality Thresholds

Metric	Marginal	Acceptable	Good
pLDDT (mean)	<60	60–80	>80
ipTM	<0.5	0.5–0.7	>0.7
pTM	<0.4	0.4–0.6	>0.6

vs. AlphaFold2/3

Feature	Boltz	AF2	AF3
Open source	✓	✓ (weights)	✗
Ligands	✓	✗	✓
RNA/DNA	✓	✗	✓
MSA required	Optional	Yes	Optional
Local run	✓	✓	Limited
CIF output	✓	PDB	CIF

Convert CIF to PDB

bash

# Using BioPython
python3 -c "
from Bio.PDB import MMCIFParser, PDBIO
parser = MMCIFParser()
structure = parser.get_structure('pred', 'complex_model_0.cif')
io = PDBIO()
io.set_structure(structure)
io.save('complex_model_0.pdb')
"

Files

Just SKILL.md in skills/boltz of lamm-mit/scienceclaw.

Open the folder on GitHubat commit ab9aba1

Compare with similar skills

Boltz next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Boltz compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Boltz this skilllamm-mit/scienceclaw	244	—	~879	Automated safety check: Pass	Apache-2.0	1 mo ago
Adapt New Diffusion Modelintel/auto-round	1.6k	—	~2.8k	Automated safety check: Pass	Apache-2.0	today
Add Pipelineverl-project/verl-omni	1.2k	—	~1k	Automated safety check: Pass	Apache-2.0	yesterday
Comfyui AnimatoolShiroEirin/comfyui-good-anima	478	—	~4.6k	Automated safety check: Pass	GPL-3.0	3 mo ago
Stage1 Add VaeEnd2End-Diffusion/diffusion-bench	105	—	~1.1k	Automated safety check: Pass	None	3 mo ago
Comfyui Agent Skill MieMieMieeeee/comfyui-agent-skill	116	—	~3.9k	Automated safety check: Pass	Apache-2.0	4 days ago

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Questions about Boltz

What does Boltz do?

A skill your agent uses when predicting biomolecular structures (proteins, RNA, DNA, ligands) with the open-source Boltz diffusion model as an alternative to AlphaFold3. Boltz is an agent skill from lamm-mit/scienceclaw. Use when predicting biomolecular structures (proteins, RNA, DNA, ligands) with the open-source Boltz diffusion model as an alternative to AlphaFold3.

When should I use Boltz?

Boltz fits situations like: predicting biomolecular structures (proteins; ligands) with the open-source Boltz diffusion model as an alternative to AlphaFold3.

How do I install Boltz in Claude Code?

Run `npx skills add lamm-mit/scienceclaw --skill boltz -a claude-code`. Or copy the skill folder (skills/boltz in lamm-mit/scienceclaw) into .claude/skills/boltz in your project. Claude Code loads it when a task matches its description.

How do I install Boltz in Codex?

Run `npx skills add lamm-mit/scienceclaw --skill boltz -a codex`. Or copy the skill folder (skills/boltz in lamm-mit/scienceclaw) into .agents/skills/boltz in your project. Codex loads it when a task matches its description.

Can I use Boltz 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 lamm-mit/scienceclaw --skill boltz -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/boltz, .gemini/skills/boltz, .github/skills/boltz and .opencode/skills/boltz in your project.

What does Boltz need to run?

Going by SKILL.md and its folder, Boltz needs the command-line tools its instructions call (pip and python3). Our summary lists: Python 3.

Does Boltz access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Boltz safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Boltz use?

Boltz is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Boltz use?

About 879 tokens (SKILL.md is roughly 3.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Boltz?

Skills that share tags, products or a category with Boltz: Adapt New Diffusion Model (intel/auto-round, 1.6k stars), Add Pipeline (verl-project/verl-omni, 1.2k stars), Comfyui Animatool (ShiroEirin/comfyui-good-anima, 478 stars) and Stage1 Add Vae (End2End-Diffusion/diffusion-bench, 105 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Boltz?

lamm-mit (a GitHub user) maintains it in lamm-mit/scienceclaw, which has 244 GitHub stars. The repository holds 85 skills in this directory. The repository was last updated on August 21, 2026.

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

Install Boltz

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Boltz Structure Prediction

Requirements

Installation

Input Format (YAML)

Running Predictions

Python API

Output Files

Confidence Metrics

Quality Thresholds

vs. AlphaFold2/3

Convert CIF to PDB

Files

Compare with similar skills

Similar skills

More from lamm-mit/scienceclaw

Related

Questions about Boltz