eeg-skill skillA
eeg-skill is agent-read markdown (skill) from cuhk-aim-group/neurodiscovery: Use this skill whenever the user wants to load, preprocess, epoch, filter, or extract features from EEG data (resting-state, task-based, BCI, clinical, motor imagery, emotion, epilepsy, fatigue, etc.). Triggers include: 'eeg', 'EEG preprocessing', 'EEG feature extraction', 'band power', 'downsample to frequency bands', 'motor imagery BCI', 'emotion EEG', 'epilepsy detection', or any request involving .set/.edf/.bdf/.fif/.bids files..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# EEG Skill (Modality Layer) ## Overview `eeg-skill` is the NeuroClaw **modality-layer** interface skill responsible for all EEG data processing tasks. It strictly follows the NeuroClaw hierarchical design principles: - This skill **only describes WHAT needs to be done** and **which tool skill to delegate to**. - It contains **no full implementation code**. - All concrete execution (MNE-Python calls, torchaudio, scipy, file I/O, etc.) is delegated to the dedicated base/tool skill `mne-eeg-tool`. - Waveform-to-spectrogram conversion uses `torchaudio.transforms.MelSpectrogram`. - Frequency-band energy extraction uses continuous wavelet transform (`scipy.signal.cwt` with `morlet2` wavelet). **Core workflow (never bypassed):** 1. Identify the user-provided EEG files (BIDS, .set, .edf, .bdf, .fif, etc.). 2. Generate a **numbered execution plan** that clearly states WHAT needs to be done and which tool skill will handle each step. 3. Present the full plan, estimated runtime, resource requirements, and risks to the user and wait for explicit confirmation (“YES” / “execute” / “proceed”). 4. On confirmation, delegate every step to `mne-eeg-tool` via `claw-shell`. …
Read the whole file at its exact version.
How to install
mdr add cuhk-aim-group/neurodiscovery/eeg-skill@git:20260506.86420c0mdr add cuhk-aim-group/neurodiscovery/eeg-skill@sha256:b7565ce13fbcb8e1Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_taln54bq45kmvmfo)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260506.86420c0 latest | 2026-05-06 | 86420c0 | 10,461 B | A | view · diff |
| git:20260505.e9ddd22 | 2026-05-05 | e9ddd22 | 10,470 B | A | view · diff |
| git:20260404.fa7f354 | 2026-04-04 | fa7f354 | 10,388 B | A | view · diff |
| git:20260328.891ed93 | 2026-03-28 | 891ed93 | 7,777 B | A | view · diff |
| git:20260325.72d2cbf | 2026-03-25 | 72d2cbf | 7,918 B | A | view |
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 (10461 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 · 91 stars · license MIT · pushed 2026-09-22 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_taln54bq45kmvmfo GET https://markdownregistry.com/api/v1/resolve?ref=cuhk-aim-group/neurodiscovery/eeg-skill GET https://markdownregistry.com/api/v1/blob/b7565ce13fbcb8e1f312ca3d296b9936f4af0cb14843a01f65a171830dcca915
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