How do I install the Bioreason Pro skill?

Run npx skillmds@latest add lamm-mit/bioreason-pro 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 Bioreason Pro safe to use?

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

Which AI agents work with Bioreason Pro?

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 Bioreason Pro free to use?

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

Who published Bioreason Pro?

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

Bioreason Pro by lamm-mit — Agent Skill

Name: Bioreason Pro
Author: lamm-mit

File contents

bioreason_pro

Multimodal reasoning LLM for protein function prediction integrating protein embeddings with biological context to generate structured reasoning traces and functional annotations.

Code repository

https://github.com/bowang-lab/BioReason-Pro

Use this as the implementation source: clone the repo and follow its README for install, dependencies, and how to run code or experiments. The generated client prints JSON with a suggested git clone command.

Primary resource (landing page)

https://www.biorxiv.org/content/10.64898/2026.03.19.712954v1

This is the paper or artifact home from DOI/registry metadata — not a JSON API. If this URL is arXiv, the generated client can still fetch live Atom metadata (title, abstract, authors) without a BASE_URL. For other hosts, the client uses stub mode until you set a real BASE_URL for a REST service.

What “running” this client does

The *_client.py script prints JSON that combines a GitHub repository (clone URL + suggested git clone) with optional paper context from arXiv (live Atom metadata when reference_url is arXiv). Run the real code by cloning the repo and following its README — the skill is your agent-facing entrypoint, not a substitute for the repo’s install steps.

To call a REST API instead, set BASE_URL in scripts/bioreason_pro_client.py or wrap the upstream CLI with subprocess after clone.

How to run the method (from the source)

Extracted for operators and agents. Confirm against the upstream repository or paper before relying on it in production.

Prerequisites

Python 3.11+
CUDA/GPU for best performance

Installation

# Clone the repository
git clone https://github.com/bowang-lab/BioReason-Pro.git
cd BioReason-Pro

# Install package
pip install -e .

How to run

The README does not document specific CLI commands for running inference or training. However, the project provides:

Web Interface: Try BioReason-Pro directly at bioreason.net
Precomputed Predictions: Access 240,000+ precomputed protein predictions at bioreason.net/atlas
Model Checkpoints: Available on HuggingFace collection (wanglab/bioreason-pro)
- GO-GPT: https://huggingface.co/wanglab/gogpt
- BioReason-Pro SFT: https://huggingface.co/wanglab/bioreason-pro-sft
- BioReason-Pro RL: https://huggingface.co/wanglab/bioreason-pro-rl
Datasets: Training and evaluation datasets available at HuggingFace collection with detailed download and usage instructions

Configuration

The README does not document specific environment variables, API keys, or configuration parameters. For detailed usage instructions on running inference or training, refer to the repository's code or documentation at https://github.com/bowang-lab/BioReason-Pro or the project website at https://bioreason.net.

The same text lives in scripts/USAGE.md for tools that prefer reading files under scripts/.

Parameters

Usage

python3 scripts/bioreason_pro_client.py

Example Output

---name: bioreason-prodescription: Multimodal reasoning LLM for protein function prediction integrating protein embeddings with biological context to generate structured reasoning traces and functional annotations.---## bioreason_proMultimodal reasoning LLM for protein function prediction integrating protein embeddings with biological context to generate structured reasoning traces and functional annotations.### Code repository<https://github.com/bowang-lab/BioReason-Pro>**Use this as the implementation source:** clone the repo and follow its README for install, dependencies, and how to run code or experiments. The generated client prints JSON with a suggested ``git clone`` command.### Primary resource (landing page)<https://www.biorxiv.org/content/10.64898/2026.03.19.712954v1>This is the paper or artifact home from DOI/registry metadata — **not** a JSON API. If this URL is **arXiv**, the generated client can still fetch **live Atom metadata** (title, abstract, authors) without a ``BASE_URL``. For other hosts, the client uses stub mode until you set a real ``BASE_URL`` for a REST service.### What “running” this client doesThe `*_client.py` script prints **JSON** that combines a **GitHub repository** (clone URL + suggested ``git clone``) with **optional paper context** from arXiv (live Atom metadata when **reference_url** is arXiv). Run the real code by cloning the repo and following its README — the skill is your agent-facing entrypoint, not a substitute for the repo’s install steps.To call a **REST API** instead, set ``BASE_URL`` in `scripts/bioreason_pro_client.py` or wrap the upstream CLI with ``subprocess`` after clone.### How to run the method (from the source)Extracted for **operators and agents**. Confirm against the upstream repository or paper before relying on it in production.## Prerequisites- Python 3.11+- CUDA/GPU for best performance## Installation```bash# Clone the repositorygit clone https://github.com/bowang-lab/BioReason-Pro.gitcd BioReason-Pro# Install packagepip install -e .```## How to runThe README does not document specific CLI commands for running inference or training. However, the project provides:1. **Web Interface**: Try BioReason-Pro directly at [bioreason.net](https://bioreason.net)2. **Precomputed Predictions**: Access 240,000+ precomputed protein predictions at [bioreason.net/atlas](https://bioreason.net/atlas)3. **Model Checkpoints**: Available on HuggingFace collection ([wanglab/bioreason-pro](https://huggingface.co/collections/wanglab/bioreason-pro)) - GO-GPT: https://huggingface.co/wanglab/gogpt - BioReason-Pro SFT: https://huggingface.co/wanglab/bioreason-pro-sft - BioReason-Pro RL: https://huggingface.co/wanglab/bioreason-pro-rl4. **Datasets**: Training and evaluation datasets available at [HuggingFace collection](https://huggingface.co/collections/wanglab/bioreason-pro) with detailed download and usage instructions## ConfigurationThe README does not document specific environment variables, API keys, or configuration parameters. For detailed usage instructions on running inference or training, refer to the repository's code or documentation at https://github.com/bowang-lab/BioReason-Pro or the project website at https://bioreason.net.*The same text lives in* ``scripts/USAGE.md`` *for tools that prefer reading files under* ``scripts/``*.*### Parameters### Usage```bashpython3 scripts/bioreason_pro_client.py ```### Example Output```json```

Frequently asked questions

Bioreason Pro