Home / cuhk-aim-group / neurodiscovery · GitHub

filtering SKILL.md skillA

filtering 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/filtering@git:20260505.e9ddd22

Pins git:20260505.e9ddd22 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/filtering/SKILL.md
Versions recorded: 1
Latest version: git:20260505.e9ddd22, committed May 5, 2026
Size: 4,084 bytes
Repository stars: 93
License: MIT

Use this model doc whenever the user wants to perform neuroimaging signal denoising with classical temporal filtering methods. This is a non-deep-learning preprocessing route focused on temporal cleaning, frequency selection, and preparation of cleaner time series for downstream analysis.

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

# Filtering Model Doc

## Overview
Filtering is a classical non-deep-learning method for neuroimaging signal denoising.

- Model family: non-deep-learning preprocessing and denoising method
- Typical objectives:
  - remove unwanted frequency content from BOLD time series
  - retain frequency bands relevant to resting-state or task analysis
  - prepare cleaner voxel-wise or ROI-wise time series for downstream connectivity, decoding, or statistical analysis
- Primary input: preprocessed fMRI time series, optional confounds, optional mask, TR
- Primary output: denoised BOLD image, cleaned ROI time series, optional QC summaries

In NeuroClaw, this document is model-level guidance for temporal filtering workflows rather than predictive modeling.

Upstream preparation should usually be delegated to:
- `fmri-skill` for modality-level denoising planning and validated preprocessing sequences
- `nilearn-tool` for concrete filtering and cleaned image export

**Research use only.**

---

## Quick Start

### 1) Prepare denoising inputs
Expected inputs:
- preprocessed BOLD image
- repetition time (`TR`)
- optional confounds TSV
- optional brain mask
- optional requested frequency band
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint

mdr add cuhk-aim-group/neurodiscovery/filtering@sha256:5614849add582120

The line at the top of this page pins the label git:20260505.e9ddd22, 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_76wer4l3afbbgh5t.svg)](https://markdownregistry.com/a/art_76wer4l3afbbgh5t)

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

Versions

The registry has recorded 1 version of this file, committed on May 5, 2026.

version	committed	commit	size	audit
git:20260505.e9ddd22 latest	2026-05-05	e9ddd22	4,084 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 (4084 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_76wer4l3afbbgh5t
GET https://markdownregistry.com/api/v1/resolve?ref=cuhk-aim-group/neurodiscovery/filtering
GET https://markdownregistry.com/api/v1/blob/5614849add5821205e9fe65e06559d0a57b51d915a9c368275ece78a01fbad81

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.