Skip to main content
Change of provenance

The repository or configuration that created this release differ from a previous release. View details.

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==0.3.3
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]==0.3.3'

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 distribution uses published AEA source commit 62944027e4484b051614dc2f1bd397db97f5823c. 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.

Project · Setup guide · Validation coverage

Metadata

Release files for auto-eeg-analysis 0.3.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Change of provenance

The repository or configuration that created these release files differ from that of a previous release.

We recommend inspecting the repository and configuration before proceeding. View details.

Source distribution (sdist)

Source distribution for auto-eeg-analysis 0.3.3
File Size Uploaded Provenance Actions
auto_eeg_analysis-0.3.3.tar.gz 1.6 MB With provenance Details for auto_eeg_analysis-0.3.3.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for auto-eeg-analysis 0.3.3
File Interpreter ABI Platform Actions
auto_eeg_analysis-0.3.3-py3-none-any.whl Python 3 none any Details for auto_eeg_analysis-0.3.3-py3-none-any.whl

Total release size: 3.4 MB

Release files / auto_eeg_analysis-0.3.3.tar.gz

Change of provenance

This file belongs to a release with changed provenance: the repository or configuration that created the release files differ from that of a previous release.

We recommend inspecting the repository and configuration before proceeding. View details.

Download URL auto_eeg_analysis-0.3.3.tar.gz
Size 1.6 MB
Tags Source
SHA-256 checksum
How to use checksums
b4243ffc33934d24a160c16e807a22e3c7c557e1389446823a391eac368996e8
BLAKE2b-256 checksum
How to use checksums
ba5ff4da6118f9b9d7c1cd29d758273faf80ef9cfbf7bf7cb8f142b70a227356
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.16

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Nov 12, 2026.

Transparency log

Release files / auto_eeg_analysis-0.3.3-py3-none-any.whl

Change of provenance

This file belongs to a release with changed provenance: the repository or configuration that created the release files differ from that of a previous release.

We recommend inspecting the repository and configuration before proceeding. View details.

Download URL auto_eeg_analysis-0.3.3-py3-none-any.whl
Size 1.8 MB
Tags Python 3
SHA-256 checksum
How to use checksums
79b4477fb97dd7ee08949451fd9d593b4cb7c8c6af5114b5b52587f8d57f707d
BLAKE2b-256 checksum
How to use checksums
eb4c5018c25d975dbee14b590da7cc5c740368279dea975cfd5e430bc982dd1d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.16

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Nov 12, 2026.

Transparency log

Security for auto-eeg-analysis 0.3.3

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Change of provenance

The repository and configuration that created this release differ from a previous release.

While this could reflect a routine change by the project maintainers, it may also indicate that the release files have been compromised.

Select from 2 files

Attestation for auto_eeg_analysis-0.3.3.tar.gz

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Nov 12, 2026.

Transparency log

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page