# How to use EvalFlow CI Lab

**Quick start:** Open App. Choose `Multinomial Naive Bayes` as baseline, `Hybrid TF-IDF` as candidate, and `Harder challenge · 54` as split. Click `Run release audit`. The candidate should show 77.8% Accuracy and the default research policy should return PASS.

- **Command Center:** see exact metrics and gate results.
- **Pipeline Replay:** review seven stages and the executable CLI command.
- **Paired Regressions:** filter repaired examples, newly incorrect examples and changed predictions. Search by example ID or source text.
- **Release Gates:** try changing minimum Accuracy from 0.75 to 0.95; it should BLOCK. Use reset to return to the documented default.
- **Slice Diagnostics:** use language/label groupings. The challenge split contains only one `mixed` domain, shown as a warning. For domain slices, use the controlled IID split.
- **Robustness Checks:** inspect typo/context flip rates and example coverage. Truncation is destructive and not scored.
- **Run Registry:** downloads are essential because browser sessions are not persisted.
- **CI Integration:** instructions to activate the optional workflow on GitHub.
- **Export & Provenance:** download CSV, JSON and Markdown. Custom evaluation JSON stays in the browser and is marked unverified. Restore original dataset anytime.