dictlearning SKILL.md skillA
dictlearning from cuhk-aim-group/neurodiscovery is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add cuhk-aim-group/neurodiscovery/dictlearning@git:20260505.e9ddd22Pins 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/dictlearning/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260505.e9ddd22, committed May 5, 2026
- Size
- 4,317 bytes
- Repository stars
- 93
- License
- MIT
Use this model doc whenever the user wants to perform resting-state network decomposition using DictLearning. This is a non-deep-learning unsupervised route focused on sparse component extraction, network map discovery, and subject-level time series from resting-state fMRI.
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
# DictLearning Model Doc ## Overview DictLearning is a classical non-deep-learning method for resting-state network decomposition. - Model family: non-deep-learning unsupervised decomposition method - Typical objectives: - identify sparse resting-state networks from preprocessed fMRI - extract dictionary component maps and subject-level time series - derive interpretable network summaries for downstream connectivity or clustering - Primary input: preprocessed resting-state fMRI, optional mask, optional group subject list - Primary output: dictionary component maps, subject time series, optional connectomes or reports In NeuroClaw, this document is model-level guidance for DictLearning-based resting-state decomposition workflows rather than phenotype prediction. Upstream preparation should usually be delegated to: - `fmri-skill` for rs-fMRI preprocessing, nuisance regression, filtering, and standard-space alignment - `nilearn-tool` for concrete DictLearning fitting and component export **Research use only.** --- ## Quick Start ### 1) Prepare resting-state inputs Expected inputs: - preprocessed resting-state BOLD images - optional confounds TSV files …
Read the whole file at its exact version.
How to install
mdr add cuhk-aim-group/neurodiscovery/dictlearning@sha256:b8debfc5c94b6158The 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.
[](https://markdownregistry.com/a/art_xxe6spkmqcvtz4n2)
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Versions
The registry has recorded 1 version of this file, committed on May 5, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (4317 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
cuhk-aim-group/neurodiscovery · 93 stars · license MIT · pushed 2026-10-23 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_xxe6spkmqcvtz4n2 GET https://markdownregistry.com/api/v1/resolve?ref=cuhk-aim-group/neurodiscovery/dictlearning GET https://markdownregistry.com/api/v1/blob/b8debfc5c94b61583642352c2d815e0b59166496ff0ee132d214dd1d91708193
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.