v0.1.0 — first public release

First public release of BCI Dataset Cards — a small, beginner-friendly CLI for
inspecting public EEG/BCI datasets and running honest, reproducible baselines.

Features

• bcicards scan — generate a Markdown dataset card from MOABB metadata.
• bcicards benchmark — run a CSP + LDA motor-imagery baseline (fixed seed), save
  JSON results and a metrics plot.
• Subject-aware (leave-one-subject-out) splitting for multiple subjects; stratified
  holdout for a single subject.
• Explicit leakage warnings and "what this does not prove" sections in every card.

Verified on BNCI2014_001 (seed 42)

• Within-subject (subject 1, stratified holdout): 0.751 accuracy
• Cross-subject (subjects 1-3, leave-one-subject-out): 0.429 accuracy
• Chance for 4 classes is 0.25 — the gap shows why the split method must be stated.

Quality

• Mocked unit tests; CI on Windows + Linux, Python 3.11 + 3.12.
• MIT licensed. Not medical software; no diagnostic or "mind reading" claims.