This release is a pre-release and may not be stable for production use.
Auto EEG Analysis (AEA)
AEA provides reusable EEG analysis skills and study recipes for large language model coding agents. MNE-Python is the primary computation backend. Selected EEGLAB and FieldTrip routes are described in the bundled documentation.
This package installs the resource library and a project initialization command. It includes 22 skills, 10 study recipes, analysis helpers, templates and setup documentation. It does not install or configure a model client or an account.
Install and create a project
Use Python 3.10 or newer in an environment of your choice.
python -m pip install auto-eeg-analysis==0.3.3rc1
aea-eeg init ./my-eeg-study --agent codex
cd my-eeg-study
Use --agent claude for Claude Code or --agent both for both clients.
The command copies the library into a new or empty directory and creates
project-local skill links using AEA's existing installer. Existing nonempty
directories are refused. It does not change global client configuration.
python -m auto_eeg_analysis accepts the same arguments as aea-eeg.
The default installation has no scientific runtime dependencies. Reuse your
existing MNE environment, use the included environment.yml to create one,
or install the analysis dependencies from the existing environment specification.
python -m pip install 'auto-eeg-analysis[analysis]==0.3.3rc1'
Read AGENT_GUIDE.md, select procedures through RESOURCE_INDEX.md, and approve
the study-specific analysis plan. Start the separately installed coding client
from the initialized project directory. aea-eeg path shows the installed
resource directory.
Version and evidence
This packaging candidate uses published AEA source commit
cdc0c30105cc4547aed8e5ece41739a8462cb47a. The package version identifies this
distribution. Retained scientific validation records and plugin versions keep
their original identifiers. Packaging checks do not extend the numerical
validation coverage in docs/CERTIFICATION_LEVELS.md.
The package contains no participant datasets, model credentials or archived model sessions. The Git repository remains the development source and the place for contributions and support.
License and citation
Code and skills use the repository's MIT license. Study recipes use CC BY 4.0
as stated in recipes/README.md. Preserve the recipe citations and original
license notices. CITATION.cff retains the source repository's citation metadata.
Metadata
Release files for auto-eeg-analysis 0.3.3rc1
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Total release size: 3.4 MB
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