Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/naity/FM4Lifenpx agentmods add skills/naity/fm4life/rfdiffusionWrote 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.
[](https://agentmods.dev/skills/naity/fm4life/rfdiffusion)<a href="https://agentmods.dev/skills/naity/fm4life/rfdiffusion"><img src="https://agentmods.dev/badge/skills/naity/fm4life/rfdiffusion/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.
<a href="https://agentmods.dev/skills/naity/fm4life/rfdiffusion"><img src="https://agentmods.dev/badge/skills/naity/fm4life/rfdiffusion.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00132 | $0.02680 |
| Opus 5 | $0.00066 | $0.01340 |
| Sonnet 5 | $0.00026 | $0.00536 |
| Haiku 4.5 | $0.00013 | $0.00268 |
Grade A, and why
rfdiffusion scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
wget http://files.ipd.uw.edu/pub/RFdiffusion/6f5902ac237024bdd0c176cb93063dc4/Base_ckpt.pt How it starts
The opening of the file, as written. The whole thing — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RFdiffusion: De Novo Protein Backbone Generation
Overview
RFdiffusion generates protein backbones via a denoising diffusion process. It starts from random noise and iteratively refines toward a plausible protein structure. It is the backbone generation half of the modern protein design pipeline:
RFdiffusion (backbone) → ProteinMPNN (sequence) → AlphaFold2 (validation)
Core design modes:
- Unconditional generation — design monomers of specified length
- Motif scaffolding — build a new protein around a fixed functional motif
- Binder design — create proteins that bind a target surface
- Symmetric oligomers — cyclic (Cn), dihedral (Dn), tetrahedral, octahedral, icosahedral
- Partial diffusion — diversify an existing backbone (keep fold, vary details)
- Active site scaffolding — design enzymes around catalytic residues
- Cyclic peptides — macrocyclic monomers and binders
- Sequence inpainting — redesign selected residues in context
Installation
git clone https://github.com/RosettaCommons/RFdiffusion.git
cd RFdiffusion
# Create environment
conda env create -f env/SE3nv.yml
conda activate SE3nv
# Install SE3-Transformer
cd env/SE3Transformer
pip install --no-cache-dir -r requirements.txt
python setup.py install
cd ../..
# Install RFdiffusion
pip install -e .
Download model weights
mkdir models && cd models
# Base (unconditional + motif scaffolding)
wget http://files.ipd.uw.edu/pub/RFdiffusion/6f5902ac237024bdd0c176cb93063dc4/Base_ckpt.pt
# Binder / PPI design
wget http://files.ipd.uw.edu/pub/RFdiffusion/e29311f6f1bf1af907f9ef9f44b8328b/Complex_base_ckpt.pt
# Active site scaffolding
wget http://files.ipd.uw.edu/pub/RFdiffusion/5532d2e1f3a4738decd58b19d633b3c3/ActiveSite_ckpt.pt
# Sequence inpainting
wget http://files.ipd.uw.edu/pub/RFdiffusion/74f51cfb8b440f50d70878e05361d8f0/InpaintSeq_ckpt.pt
# Epoch 8 (metal binding, symmetric oligomers)
wget http://files.ipd.uw.edu/pub/RFdiffusion/12fc204edeae5b57713c5ad7dcb97d39/Base_epoch8_ckpt.pt
What ships with it
1 file 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.
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.
- 9d ago First seen · 256 lines · 132 tokens per session scan A cffe85dce3f2
rfdiffusion is a skill published in the GitHub repository naity/FM4Life (2 stars, last pushed 5mo ago), licensed MIT. It adds 132 tokens to every session and 2,680 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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