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glm SKILL.md skillA

glm from cuhk-aim-group/neurodiscovery is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned

mdr add cuhk-aim-group/neurodiscovery/glm@git:20260825.cbd02ff

Pins git:20260825.cbd02ff in mdr.lock. Pin the fingerprint instead.

Audit grade: A, 17 of 17 checks passed
Kind: SKILL.md skill
Repository: cuhk-aim-group/neurodiscovery
Path: skills/glm/SKILL.md
Versions recorded: 2
Latest version: git:20260825.cbd02ff, committed Aug 25, 2026
First version recorded: May 5, 2026
Size: 5,620 bytes
Repository stars: 93
License: MIT

Use this model doc whenever the user wants to run a classical General Linear Model (GLM) for task-evoked fMRI activation analysis. This is a non-deep-learning model route focused on design matrices, first-level/second-level statistics, and statistical maps.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# GLM Model Doc

Task-fMRI first/second-level GLM remains implemented through `nilearn-tool`.
For tabular formula OLS, robust covariance, Cohen's d, mixed-effects, and
prediction baselines, route to the `statistical-ml` skill.

## Overview
GLM refers to the classical General Linear Model used for task-based fMRI activation analysis.

- Model family: non-deep-learning statistical model
- Typical objectives:
  - first-level GLM for subject/session-level task activation analysis
  - second-level GLM for group-level inference across subjects
- Primary input: preprocessed task fMRI, events, TR, optional confounds, optional brain mask
- Primary output: first-level contrast maps, second-level z maps, thresholded activation maps, region-level summaries

In NeuroClaw, this document is model-level guidance for statistical activation workflows rather than phenotype prediction.

Upstream preparation should usually be delegated to:
- `fmri-skill` for task-fMRI preprocessing and confounds preparation
- `nilearn-tool` for concrete GLM fitting, design matrix construction, and statistical map generation

**Research use only.**

---

## Quick Start

### 1) Prepare task-fMRI inputs
Expected inputs:
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint

mdr add cuhk-aim-group/neurodiscovery/glm@sha256:cfa251a02f0303d9

The line at the top of this page pins the label git:20260825.cbd02ff, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

[![mdr](https://markdownregistry.com/badge/art_tmsv3bi76hynn6lh.svg)](https://markdownregistry.com/a/art_tmsv3bi76hynn6lh)

3 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 2 versions of this file, between May 5, 2026 and Aug 25, 2026, about one every 112 days.

version	committed	commit	size	audit
git:20260825.cbd02ff latest	2026-08-25	cbd02ff	5,620 B	A	view · diff
git:20260505.e9ddd22	2026-05-05	e9ddd22	5,408 B	A	view

Audit of the latest version

A 17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.

pass: Frontmatter block present
pass: Frontmatter declares a name
pass: Frontmatter declares a description
pass: Size between 200 bytes and 200 KB (5620 bytes)
pass: No zero-width or bidi control characters
pass: No instruction hidden inside an HTML comment
pass: No link to an exfiltration or paste host
pass: No credential-shaped string
pass: No instruction to send local credentials anywhere
pass: No text hidden with inline styles
pass: No prompt-injection phrasing
pass: No curl or wget piped into a shell
pass: No recursive delete of root, home or parent
pass: No instruction to read or print local credentials
pass: No base64 blob over 200 characters
pass: No link to a raw IP address
pass: No script tag

Source

GitHub

cuhk-aim-group/neurodiscovery · 93 stars · license MIT · pushed 2026-10-23 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_tmsv3bi76hynn6lh
GET https://markdownregistry.com/api/v1/resolve?ref=cuhk-aim-group/neurodiscovery/glm
GET https://markdownregistry.com/api/v1/blob/cfa251a02f0303d9d0760467afdab71841bf51c91591e6030f3346a0d6bb1856

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.