import type * as ElevenLabs from "../index";
/**
 * An evaluation using the transcript and a prompt for a yes/no achieved answer
 */
export interface PromptEvaluationCriteria {
    /** The unique identifier for the evaluation criteria */
    id: string;
    name: string;
    /** The type of evaluation criteria */
    type?: "prompt";
    /** The prompt that the agent should use to evaluate the conversation */
    conversationGoalPrompt: string;
    /** When evaluating the prompt, should the agent's knowledge base be used. */
    useKnowledgeBase?: boolean;
    /** The scope of transcript context used when evaluating this criterion. 'conversation' uses the full transcript; 'agent' uses only the portion where the defining agent was active. */
    scope?: ElevenLabs.AnalysisScope;
    /** LLM model to use for this evaluation criteria. If not set, uses agent's analysis_llm default. */
    llm?: ElevenLabs.Llm;
    /** How this criterion is scored. 'binary' resolves to success/failure/unknown. 'numeric_uniform' returns a number on the [0, max_score] scale which is normalized into the aggregate conversation success percentage. */
    scoringMode?: ElevenLabs.CriteriaScoringMode;
    /** Maximum value of the numeric score scale (minimum is always 0). Only used when scoring_mode is 'numeric_uniform'. */
    maxScore?: number;
    /** Optional free-text instructions describing how to assign values on the numeric scale. Only used when scoring_mode is 'numeric_uniform'. */
    scoreInstructions?: string;
}