boltz-protein-design
SkillDesign new protein binders with Boltz. Use when generating protein, peptide, antibody, nanobody, or custom binder candidates for a target. Not for screening existing proteins or small molecules.
Install
git clone https://github.com/boltz-bio/boltz-api-skills.git ~/.claude/skills/boltz-protein-designWhat is boltz-protein-design?
Design new protein binders with Boltz. Use when generating protein, peptide, antibody, nanobody, or custom binder candidates for a target. Not for screening existing proteins or small molecules.
What this can do
Capabilities declared in this component's own frontmatter — not inferred.
Inherit all session tools
Declares no tool restrictions — inherits every session tool
~49 tokens of context used while enabled, before you invoke anything
Documentation
README · ~9 min readWorkflow
If boltz-api is missing from PATH, use boltz-cli-setup for install/update guidance before retrying.
If a command reports missing or expired authentication, use boltz-cli-setup to start boltz-api auth login --device-code before retrying; do not ask permission first.
If the agent host sandbox blocks boltz-api install/auth/API calls, use boltz-cli-setup to request the host sandbox bypass/escalation needed for user-wide CLI install, browser login, credential storage, temp files, or API access before retrying.
Use this skill when the user wants de novo protein / peptide / antibody / nanobody binders.
-
Decide on target exploration first (new targets). For a new target where the user hasn't already fixed the binding site and crop, your first action — before authoring a payload, normalizing the target, or running
estimate-cost— is to raise the choice between a target-exploration pass and designing directly, with a recommendation for this target:- Unknown site, or a multi-domain / large target → recommend exploration (it scouts different input configurations for generation, ≈50 designs each, and finds the best before a full run).
- A well-characterized site → it's fine to recommend going (mostly) direct, perhaps with a quick check of whether conditioning on the epitope beats letting the model find its own spot. State this plainly, as part of a conversation with the user about their target and goals, and let them choose.
Phrase it as a question that works with the user (they may know their target's biology), e.g.:
"This is a fresh target — I'd suggest a quick exploration pass that scouts a few framings and picks the best before a full run. Or, if you already know the site and crop, we can design directly. Which would you like?"
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