chai1-structure-prediction

chai1-structure-prediction is a skill for Claude Code, Codex from BioTender-max/awesome-bio-agent-skills. It costs 121 tokens per session (2,032 once invoked), scanned A, original, no licence file.

A workflow for predicting the three-dimensional shapes of protein complexes and protein–ligand complexes with Chai-1.

In plain words
What is it for?
Use it for complex-structure prediction, binder-design validation, ligand modelling, and high-throughput predictions through the Chai API.
Why use it?
It provides an alternative to AlphaFold2 for checking whether designed binders or molecular interactions may fit together.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it for complex-structure prediction, binder-design validation, ligand modelling, and high-throughput predictions through the Chai API.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/biotender-max/awesome-bio-agent-skills/chai1-structure-prediction
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add BioTender-max/awesome-bio-agent-skills --skill chai1-structure-prediction
Clone the repo
git clone --depth 1 https://github.com/BioTender-max/awesome-bio-agent-skills

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.

agentmods badge for chai1-structure-prediction

README.md
[![agentmods](https://agentmods.dev/badge/skills/biotender-max/awesome-bio-agent-skills/chai1-structure-prediction/github.svg)](https://agentmods.dev/skills/biotender-max/awesome-bio-agent-skills/chai1-structure-prediction)
Your own site
<a href="https://agentmods.dev/skills/biotender-max/awesome-bio-agent-skills/chai1-structure-prediction"><img src="https://agentmods.dev/badge/skills/biotender-max/awesome-bio-agent-skills/chai1-structure-prediction/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.

agentmods 80×15 button for chai1-structure-prediction

Your own site · 80×15
<a href="https://agentmods.dev/skills/biotender-max/awesome-bio-agent-skills/chai1-structure-prediction"><img src="https://agentmods.dev/badge/skills/biotender-max/awesome-bio-agent-skills/chai1-structure-prediction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 121 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,032 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.
Origin unknown 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00121 $0.02032
Opus 5 $0.00060 $0.01016
Sonnet 5 $0.00024 $0.00406
Haiku 4.5 $0.00012 $0.00203

Measured 8d ago against content hash d26f706489b6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

chai1-structure-prediction 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 8d 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/bioclaw_hub/chai1-structure-prediction/SKILL.md · 291 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

Files

What ships with it

2 files 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.

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.

  1. 8d ago First seen · 291 lines · 121 tokens per session scan A d26f706489b6

Subscribe to this mod's changes

chai1-structure-prediction is a skill published in the GitHub repository BioTender-max/awesome-bio-agent-skills (178 stars, last pushed 2mo ago), with no licence file. It adds 121 tokens to every session and 2,032 once invoked, about $0.0006 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 2026-09-03.

Related

Other skills, from other repositories

alphafold

Validate protein designs using AlphaFold2 structure prediction. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5) Multi-chain complex prediction…

FridrichMethod/awesome-skills · 100 tokens

chai1-structure-prediction

Chai-1 structure prediction for protein complexes and design validation. Use this skill when: (1) Predicting protein-protein complex structures, (2) Validating designed binders, (3) Predicting protein-ligand complexes, (4) Using the Chai API for high-throughput prediction, (5) Need an alternative to AlphaFold2. For QC…

zongtingwei/Bioclaw_Skills_Hub · 121 tokens

chai

Structure prediction using Chai-1, a foundation model for molecular structure. Use this skill when: (1) Predicting protein-protein complex structures, (2) Validating designed binders, (3) Predicting protein-ligand complexes, (4) Using the Chai API for high-throughput prediction, (5) Need an alternative to AlphaFold2.…

adaptyvbio/protein-design-skills · 107 tokens

alphafold

Validate protein designs using AlphaFold2 structure prediction. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5) Multi-chain complex prediction…

FreedomIntelligence/OpenClaw-Medical-Skills · 100 tokens

alphafold2-multimer

AlphaFold2 / AlphaFold-Multimer structure prediction for validation and confidence scoring. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5)…

zongtingwei/Bioclaw_Skills_Hub · 117 tokens

boltz-structure-prediction

Boltz-1 / Boltz-2 structure prediction for proteins, complexes, and ligand-aware validation. 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…

zongtingwei/Bioclaw_Skills_Hub · 121 tokens