Boltz

What it does

When your agent uses it

• Predicting protein complex structures
• Validating designed binders
• Need open-source alternative to AF2
• Predicting protein-ligand complexes

Example prompts

• “/boltz”

Requirements

• Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 59dd633. 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:

  • modal
  • pip

  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 1.3k tokens when it runs. Until then it costs about 102 tokens; SKILL.md has 336 words of instructions outside code blocks.

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

~102

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

~1.3k

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

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 adaptyvbio/protein-design-skills at commit 59dd633, republished under its MIT licence (© adaptyvbio). 336 words, ~1,271 tokens.

name

boltz

description

Structure prediction using Boltz-1/Boltz-2, an open biomolecular structure predictor. Use this skill when: (1) Predicting protein complex structures, (2) Validating designed binders, (3) Need open-source alternative to AF2, (4) Predicting protein-ligand complexes, (5) Using local GPU resources. For QC thresholds, use protein-qc. For AlphaFold2 prediction, use alphafold. For Chai prediction, use chai.

license

MIT

category

design-tools

tags

structure-prediction, validation, open-source

biomodals_script

modal_boltz.py

cd biomodals
modal run modal_boltz.py \
  --input-faa complex.fasta \
  --out-dir predictions/

pip install boltz

boltz predict \
  --fasta complex.fasta \
  --output predictions/

>protein_A
MKTAYIAKQRQISFVK...
>protein_B
MVLSPADKTNVKAAWG...

predictions/
├── model_0.cif       # Best model (CIF format)
├── confidence.json   # pLDDT, pTM, ipTM
└── pae.npy          # PAE matrix

from Bio.PDB import MMCIFParser, PDBIO
parser = MMCIFParser()
structure = parser.get_structure("model", "model_0.cif")
io = PDBIO()
io.set_structure(structure)
io.save("model_0.pdb")

$ boltz predict --fasta complex.fasta --output predictions/
[INFO] Loading Boltz-1 weights...
[INFO] Predicting structure...
[INFO] Saved model to predictions/model_0.cif

predictions/confidence.json:
{
  "ptm": 0.78,
  "iptm": 0.65,
  "plddt": 0.81
}

Should I use Boltz?
│
├─ What are you predicting?
│  ├─ Protein-protein complex → Boltz ✓ or Chai or ColabFold
│  ├─ Protein + ligand → Boltz ✓ or Chai
│  └─ Single protein → Use ESMFold (faster)
│
├─ Need MSA?
│  ├─ No / want speed → Boltz ✓
│  └─ Yes / maximum accuracy → ColabFold
│
└─ Why Boltz over Chai?
   ├─ Open weights preference → Boltz ✓
   ├─ Boltz-2 speed → Boltz ✓
   └─ DNA/RNA support → Consider Chai

find predictions -name "*.cif" | wc -l  # Should match input count

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

Files

Just SKILL.md in skills/boltz of adaptyvbio/protein-design-skills.

Open the folder on GitHubat commit 59dd633

Used in 4 other repositories

We found 6 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 4 other GitHub owners. This page covers the copy in adaptyvbio/protein-design-skills, which our catalogue first saw on October 7, 2026.

• majiayu000/claude-skill-registryskills/ai-ml/boltz-adaptyvbio-protein-design-skill-2skills/ai-ml/boltz-adaptyvbio-protein-design-skill-3+1 more
• NeverSight/learn-skills.devdata/skills-md/adaptyvbio/protein-design-skills/boltz
• FreedomIntelligence/OpenClaw-Medical-Skillsskills/boltz
• BioTender-max/awesome-bio-agent-skillsskills/adaptyv/boltz