eeg-skill

EEG data workflows are orchestrated by generating a numbered execution plan that delegates loading, preprocessing, epoching, filtering, and feature extraction steps to a specialized base tool. This coordination ensures reproducible and auditable processing.

Task-based and resting-state EEG datasets can both be processed using this single orchestration pipeline. The workflow handles loading, preprocessing, epoching, and feature extraction, generating structured outputs for clinical and BCI datasets.

Artifact removal and signal processing are handled by delegating filtering and preprocessing steps to the base EEG tool. The orchestration skill plans these steps to ensure data quality validation and structured outputs in the eeg_output directory.

MNE is listed as a keyword dependency for EEG feature extraction and signal processing. The skill coordinates the workflow by planning and delegating the extraction steps to the base tool, which executes the configured plan.

Automating EEG epoching and filtering is best handled through high-level workflow orchestration that defines each step and delegates execution. This approach includes post-execution verification to validate data quality automatically.

EEG data analysis pipelines often fail when steps like loading, preprocessing, and epoching are stitched together manually. Using a high-level orchestration to plan and delegate steps ensures safe execution and post-execution verification.