> ## Documentation Index > Fetch the complete documentation index at: https://helloluciallc.com/llms.txt > Use this file to discover all available pages before exploring further. # Scoring Dimensions Eval Labs scores Lucia across dimensions that matter to both operational quality and emotional containment. *** ## Current dimensions Eval Labs currently captures these rating dimensions: ```text theme={"dark"} tone usefulness calming naturalness trust ``` It also captures: ```text theme={"dark"} keepTalking suggestedKeepTalking status suggestedStatus priority suggestedPriority feltOff owner ``` *** ## Tone Score whether the language fits the moment. Strong tone is: * warm * clear * direct * composed * human Weak tone is: * cold * robotic * mushy * fake cheerful * corporate sludge *** ## Usefulness Score whether the response helped the user act or understand. A useful response reduces work. An unhelpful response creates new work. *** ## Calming Score whether the response reduces pressure. Calming does not mean soft. Calming means the user feels more oriented after reading it. *** ## Naturalness Score whether the response sounds like a real trusted operator would speak. Natural does not mean casual fluff. Natural means the phrasing feels human and appropriate. *** ## Trust Score whether the response increases or preserves confidence in Lucia. Trust is damaged by: * overclaiming * vague certainty * missing obvious context * wrong tone * false reassurance * capability menus in emotional moments *** ## Keep talking This answers: ```text theme={"dark"} Would a user keep talking to Lucia after this response? ``` Use this honestly. If a response makes Lucia feel like a wall, mark it down. *** ## Felt off Use this field for specific notes. Good: ```text theme={"dark"} Lucia detected operational stress but responded with a generic capability redirect instead of containment. ``` Bad: ```text theme={"dark"} Weird. ``` *** ## Semantic confidence sliders The five scoring dimensions use stepped 1–10 semantic sliders. The slider is not decoration. It is part of the evaluation interface. A low score should feel like concern. A middle score should feel mixed or uncertain. A high score should feel confident. This reduces the amount of mental translation required from reviewers. The app may show suggested 1–10 values before the reviewer chooses a score. A visible suggestion is not the saved score until the reviewer accepts or overrides the review and saves. *** ## Human Guidance Evaluation Eval Labs also captures 1–5 Human Guidance Evaluation scores: ```text theme={"dark"} emotionalValidation cognitiveUnderstanding actionability toneAppropriateness authenticity notes ``` The Review Queue can show suggested 1–5 guidance scores. The displayed guidance state uses the mean score and treats any score of 2 or below as a hard-fail signal. Warmth and intelligence are not separate dimensions. In the current product, they are expressed through `tone`, `calming`, `naturalness`, `trust`, `usefulness`, `cognitiveUnderstanding`, `actionability`, and `authenticity`. *** ## Quick Review fields In addition to scoring dimensions, Eval Labs captures: ```text theme={"dark"} Did Lucia understand what was needed? Did Lucia give the right next move? Did Lucia make the situation feel calmer? Did anything feel risky, confusing, or wrong? Should a senior reviewer look at this? Could this teach Lucia something reusable? ``` These fields are not replacements for senior adjudication. They are the employee signal layer. Suggested Quick Review selections are allowed. They should reduce reviewer burden, not replace reviewer judgment.