RFDiffusion

RFDiffusion is an AI Engineering skill for Claude Code, published by BioTender-max in awesome-bio-agent-skills.

174 stars30 forkson BioTender-max/awesome-bio-agent-skillsAdded 2026/09/07+1% in starsRepository updated 2026/07/01

agent-skillsai-agentai-agentsawesomeawesome-listbioinformaticsbiomedicalclaudeclaude-codeclaude-skillscomputational-biologydrug-discoverygenomicsllmmcpprotein-designproteomicssingle-cellskillstranscriptomics

Install in seconds

Install RFDiffusion

Copy RFDiffusion into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/BioTender-max/awesome-bio-agent-skills/tree/main/skills/adaptyv/rfdiffusion ~/.claude/skills/rfdiffusion

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/BioTender-max/awesome-bio-agent-skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/adaptyv/rfdiffusion/SKILL.md in BioTender-max/awesome-bio-agent-skills
Installs to: ~/.claude/skills/rfdiffusion
Collection: One of 25 skills cataloged from this repository
Category: AI Engineering — 3475 skills

What RFDiffusion does

RFDiffusion generates protein backbones for de novo design, binder scaffolds, motif scaffolding, and symmetric oligomers. Use it when you need a backbone to pass to proteinmpnn, alphafold, chai, or protein-qc.

RFDiffusion is cataloged under AI Engineering on DirSkills. RFDiffusion comes from a repository tagged agent-skills, ai-agent, ai-agents, awesome and awesome-list.

Documentation

README

Excerpt

RFdiffusion Backbone Generation

Prerequisites

Requirement	Minimum	Recommended
Python	3.9+	3.10
CUDA	11.7+	12.0+
GPU VRAM	16GB	24GB (A10G)
RAM	16GB	32GB

How to run

First time? See Installation Guide to set up Modal and biomodals.

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

# Basic binder design
modal run modal_rfdiffusion.py \
  --pdb target.pdb \
  --contigs "A1-150/0 70-100" \
  --hotspot "A45,A67,A89" \
  --num-designs 100

# With custom GPU/timeout
GPU=A100 TIMEOUT=60 modal run modal_rfdiffusion.py \
  --pdb target.pdb \
  --contigs "A1-150/0 70-100" \
  --num-designs 100

This is the opening of the README. Read the full README on GitHub.

Frequently asked about RFDiffusion

What else does BioTender-max publish alongside RFDiffusion?
RFDiffusion is one of 25 skills that DirSkills catalogs from BioTender-max/awesome-bio-agent-skills, the repository it ships in. Its siblings there include ATAC Seq, AlphaFold and BindCraft Binder Design. Each one is a separate skill with its own page in this directory, installs the same way RFDiffusion does, and is maintained by BioTender-max in that same repository. The rest of the collection is listed on the BioTender-max/awesome-bio-agent-skills page.
How does RFDiffusion compare to other AI Engineering skills?
RFDiffusion ranks #3239 by stars among the 3475 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of RFDiffusion against them. Open each page to compare what they document and how they install.