> ## Documentation Index
> Fetch the complete documentation index at: https://helloluciallc.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Reviewer Cognitive Load Doctrine

<Note>
  Eval Labs must make reviewing Lucia feel simple, calm, and low-pressure because reviewer fatigue damages evaluation quality.
</Note>

***

## Doctrine

Reviewer cognitive load is not a UI detail.

It is a data-quality risk.

If employees feel confused, intimidated, or forced to think like AI experts, the review signal becomes weaker.

***

## What reviewers should not have to do

Reviewers should not have to:

* understand AI training theory
* invent intent labels
* decide taxonomy names
* write long analytical notes
* explain model behavior
* know what adjudication metadata means

***

## What reviewers should do

Reviewers should:

* read the prompt
* read Lucia’s response
* use guided controls
* answer quickly and honestly
* flag senior review when uncertain
* add a short note only when it helps

***

## Interface rule

Eval Labs should prefer:

```text theme={"dark"}
guided choices
over
open-ended interpretation
```

and:

```text theme={"dark"}
visual cognition
over
form-filling
```

***

## Why semantic UI matters

Semantic controls such as confidence sliders reduce translation burden.

The reviewer should feel the difference between:

```text theme={"dark"}
weak / concerning
uncertain / mixed
strong / confident
```

without needing to reread a scoring guide every time.

***

## Canon rule

<Warning>
  A review interface that creates psychological paralysis will produce worse training signal, even if the schema is technically correct.
</Warning>