Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add CUHK-AIM-Group/NeuroClaw --skill mne-eeg-toolgit clone --depth 1 https://github.com/CUHK-AIM-Group/NeuroClawWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cuhk-aim-group/neuroclaw/mne-eeg-tool)<a href="https://agentmods.dev/skills/cuhk-aim-group/neuroclaw/mne-eeg-tool"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/mne-eeg-tool/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cuhk-aim-group/neuroclaw/mne-eeg-tool"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/mne-eeg-tool.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00073 | $0.01712 |
| Opus 5 | $0.00036 | $0.00856 |
| Sonnet 5 | $0.00015 | $0.00342 |
| Haiku 4.5 | $0.00007 | $0.00171 |
Grade A, and why
mne-eeg-tool scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MNE-EEG Tool (Base/Tool Layer)
Overview
mne-eeg-tool is the NeuroClaw base/tool skill that provides all concrete MNE-Python implementation for EEG processing.
It is never called directly by the user. It is exclusively delegated to by the modality-layer skill eeg-skill (and any future EEG-related modality skills).
This skill:
- Contains the complete, ready-to-run MNE-Python code (covers all standard preprocessing and feature extraction tasks).
- Handles environment setup verification.
- Provides a single, well-documented wrapper script (
eeg_pipeline.py) that implements all common EEG tasks, including the newly added continuous-data branch, functional connectivity, ERP features, frontal alpha asymmetry, and microstate analysis. - Routes every execution through
claw-shellfor safety and logging.
Research use only — outputs are for scientific analysis.
Agent Reference Rule
When the agent needs MNE-EEG implementation code, it should first consult the curated snippet in skills/mne-eeg-tool/scripts/ instead of copying from the embedded wrapper below.
Reference snippet available:
scripts/eeg_pipeline_reference.py-> full EEG pipeline: load, bad-channel detection, filtering, ICA, epoching, frequency bands, connectivity, ERP features, alpha asymmetry, microstates
Example:
python skills/mne-eeg-tool/scripts/eeg_pipeline_reference.py \
--input path/to/data.set \
--resting \
--output-dir eeg_output/
Quick Reference (Core Functions)
| Function | Purpose | New in this update? |
|---|---|---|
load_eeg() |
Load .set / .edf / .bdf / .fif / BIDS + validation | — |
detect_and_interpolate_bad_channels() |
Auto-detect + interpolate noisy channels | Yes |
preprocess_filtering() |
Resample + high-pass + notch + bandpass | — |
remove_artifacts() |
ICA + AutoReject + EOG/ECG regression | Yes |
continuous_data_cleaning() |
Resting-state pipeline (no events) | Yes |
rereference_and_epoch() |
Average reference + epoching + baseline correction | — |
extract_frequency_bands() |
Split into δ/θ/α/β/γ bands + power matrices | — |
extract_features() |
Band power, CSP, Hjorth, sample entropy, etc. | — |
compute_connectivity() |
PLV, coherence, wPLI, imaginary coherence | Yes |
extract_erp_features() |
Peak amplitude, latency, area under curve | Yes |
compute_alpha_asymmetry() |
Frontal alpha asymmetry (emotion studies) | Yes |
run_microstate_analysis() |
EEG microstates (resting-state) | Yes |
full_eeg_pipeline() |
One-click end-to-end pipeline (any combination) | — |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 165 lines · 73 tokens per session scan A 7f9bd733af27
mne-eeg-tool is a skill published in the GitHub repository CUHK-AIM-Group/NeuroClaw (85 stars, last pushed 6d ago), licensed MIT. It adds 73 tokens to every session and 1,712 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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