BrainGNN (Claude Skill)

Run BrainGNN for fMRI phenotype prediction, including graph construction, training, and evaluation.

Type	Claude Skill
Supplier	CUHK-AIM-Group (community OSS, MIT)
Availability	GA — part of the NeuroClaw neuroimaging skill library
Pricing	Free / OSS (MIT)
Capabilities	Read/Write — Claude runs the skill’s Python locally (Bash), not as an MCP tool

How to install

• Claude Code — clone and copy the skill into your skills directory:

  git clone https://github.com/CUHK-AIM-Group/NeuroClaw
  cp -r NeuroClaw/skills/brain_gnn ~/.claude/skills/
  

  Project-scoped alternative: copy into .claude/skills/ instead. NeuroClaw skills assume the collection’s shared helpers (claw-shell, modality tool skills) and the upstream neuroimaging stack (FreeSurfer/FSL/fMRIPrep/etc.) — install those dependencies, or run the bundled installer for the full environment:

  cd NeuroClaw && python installer/setup.py
  

  which configures the Python env, CUDA/GPU, and the neuroimaging tools.

What it does

Use this model doc whenever the user wants to run BrainGNN for fMRI phenotype prediction, including graph construction, training, and evaluation. This document focuses on model-level usage and delegates upstream preprocessing to fmri-skill (and optionally hcpya-skill for HCP data).

Primary use cases: Run BrainGNN for fMRI phenotype prediction, including graph construction, training, and evaluation.

Notes

Distributed as a SKILL.md (plus code examples) in the NeuroClaw skill library — Claude executes it locally via Bash/Python rather than as an MCP server. Upstream license: MIT. The skill directory upstream is skills/brain_gnn.

Sources

• CUHK-AIM-Group/NeuroClaw
• skills/brain_gnn/SKILL.md

---

Installed this tool?

Share feedback — install path, OS, errors, workarounds. The form opens with this tool pre-selected and a link back to this page.