eeg-skill
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.
npx skills add BioTender-max/awesome-bio-agent-skills --skill eeg-skill --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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`. 5. After execution, save al
- Overview
- Quick Reference (Common EEG Tasks – Updated 2026-03-25)
- Installation (Handled by dependency-planner)
- NeuroClaw recommended wrapper script
- Important Notes & Limitations
- When to Call This Skill
- Post-Execution Verification (Harness Integration)
- Complementary / Related Skills
- Reference
What does the eeg-skill skill do?
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.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill eeg-skill --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.