How do I install the Rfdiffusion skill?

Run npx skillmds add vimalinx/rfdiffusion in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Rfdiffusion safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Rfdiffusion?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Rfdiffusion free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Rfdiffusion?

vimalinx (@vimalinx) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Rfdiffusion by vimalinx — Agent Skill

Name: Rfdiffusion
Rating: 4.2 (5 reviews)
Author: vimalinx

File contents

rfdiffusion

Workspace-local gateway for /home/vimalinx/Projects/bio_studio/repositories/active/RFdiffusion. The repo contains a Chinese quickstart, test_rfdiffusion.sh, design_ebola_binder.sh, a populated models/ directory, and Docker/Compose entrypoints for inference.

Quick Start

Repository: /home/vimalinx/Projects/bio_studio/repositories/active/RFdiffusion
Primary smoke test: ./test_rfdiffusion.sh
Primary build step: docker compose build

When To Use This Tool

Running RFdiffusion locally from the checked-out workspace repo
Generating monomer or binder backbones with the repo's inference script
Reusing the bundled models/ directory and test harness
Exploring the repo's Ebola binder design example

Common Patterns

# Build the RFdiffusion container stack
cd /home/vimalinx/Projects/bio_studio/repositories/active/RFdiffusion
docker compose build

# Run the repo's built-in smoke test
cd /home/vimalinx/Projects/bio_studio/repositories/active/RFdiffusion
./test_rfdiffusion.sh

# Run direct inference through the repo's compose service
docker compose run --rm --entrypoint /bin/bash rfdiffusion -c \
  "python3 scripts/run_inference.py 'contigmap.contigs=[150-150]' inference.output_prefix=outputs/test_run/test inference.num_designs=1 inference.model_directory_path=/app/RFdiffusion/models inference.input_pdb=/app/RFdiffusion/examples/input_pdbs/1qys.pdb"

Recommended Workflow

Work from the local RFdiffusion repo rather than stale absolute paths copied from older notes.
Build the Docker/Compose environment first.
Run ./test_rfdiffusion.sh before attempting custom binder or motif jobs.
Only move on to custom scripts like design_ebola_binder.sh after the compose test succeeds.

Guardrails

Docker images are not prebuilt in this workspace. docker image inspect rfdiffusion failed with No such image: rfdiffusion:latest.
The quickstart document still references /media/vimalinx/Data/bio_studio/RFdiffusion; the actual workspace repo is under /home/vimalinx/Projects/bio_studio/repositories/active/RFdiffusion.
The quickstart notes GPU memory around 8GB+ for binder design.
test_rfdiffusion.sh depends on Docker Compose and the repo's models/ directory layout.
RFdiffusion is a generative structure-design tool, not a drop-in sequence-to-structure predictor.

---name: rfdiffusiondescription: Use when working from the local RFdiffusion repository to generate protein backbones or binder designs through its Docker Compose workflows.--- # rfdiffusion Workspace-local gateway for `/home/vimalinx/Projects/bio_studio/repositories/active/RFdiffusion`. The repo contains a Chinese quickstart, `test_rfdiffusion.sh`, `design_ebola_binder.sh`, a populated `models/` directory, and Docker/Compose entrypoints for inference. ## Quick Start - **Repository:** `/home/vimalinx/Projects/bio_studio/repositories/active/RFdiffusion` - **Primary smoke test:** `./test_rfdiffusion.sh` - **Primary build step:** `docker compose build` ## When To Use This Tool - Running RFdiffusion locally from the checked-out workspace repo - Generating monomer or binder backbones with the repo's inference script - Reusing the bundled `models/` directory and test harness - Exploring the repo's Ebola binder design example ## Common Patterns ```bash # Build the RFdiffusion container stack cd /home/vimalinx/Projects/bio_studio/repositories/active/RFdiffusion docker compose build ``` ```bash # Run the repo's built-in smoke test cd /home/vimalinx/Projects/bio_studio/repositories/active/RFdiffusion ./test_rfdiffusion.sh ``` ```bash # Run direct inference through the repo's compose service docker compose run --rm --entrypoint /bin/bash rfdiffusion -c \ "python3 scripts/run_inference.py 'contigmap.contigs=[150-150]' inference.output_prefix=outputs/test_run/test inference.num_designs=1 inference.model_directory_path=/app/RFdiffusion/models inference.input_pdb=/app/RFdiffusion/examples/input_pdbs/1qys.pdb" ``` ## Recommended Workflow 1. Work from the local RFdiffusion repo rather than stale absolute paths copied from older notes. 2. Build the Docker/Compose environment first. 3. Run `./test_rfdiffusion.sh` before attempting custom binder or motif jobs. 4. Only move on to custom scripts like `design_ebola_binder.sh` after the compose test succeeds. ## Guardrails - Docker images are not prebuilt in this workspace. `docker image inspect rfdiffusion` failed with `No such image: rfdiffusion:latest`. - The quickstart document still references `/media/vimalinx/Data/bio_studio/RFdiffusion`; the actual workspace repo is under `/home/vimalinx/Projects/bio_studio/repositories/active/RFdiffusion`. - The quickstart notes GPU memory around `8GB+` for binder design. - `test_rfdiffusion.sh` depends on Docker Compose and the repo's `models/` directory layout. - RFdiffusion is a generative structure-design tool, not a drop-in sequence-to-structure predictor.

Frequently asked questions