/**
 * The scoring orchestrator (M7): engine answers -> the AI Visibility Score.
 *
 * Pass 1 (deterministic) analyzes every answer; the judge pass (optional, ≤30%
 * of answers, cost-guarded) refines only the ambiguous ones; then per-engine
 * and composite scores, share of voice, and sources are aggregated into a
 * {@link ScoreReport}. All judge I/O is injected.
 */
import { CostGuard } from '../costs.js';
import { type BrandProfile, type EngineAnswer, type EngineScore, type JudgeClient, type MentionResult, type ScoreReport } from '../types.js';
export interface ScoreDeps {
    /** Judge for pass 2; omit to skip it (ambiguous results stay as pass 1). */
    judge?: JudgeClient;
    guard?: CostGuard;
}
export interface ScoreOptions {
    /** Max share of answers judged in pass 2 (default {@link JUDGE_RATE_CAP}). */
    judgeRateCap?: number;
    generatedAt?: string;
    /**
     * Prompts that named the brand (M5's "trust" intent). Their answers are kept
     * OUT of the visibility score - naming the brand guarantees a mention - and
     * summarized separately as {@link Reputation}. Empty/omitted = score every
     * answer as before.
     */
    brandedPrompts?: string[];
}
/** Score a run's engine answers against the brand profile. */
export declare function scoreAnswers(answers: EngineAnswer[], profile: BrandProfile, deps: ScoreDeps, opts?: ScoreOptions): Promise<ScoreReport>;
/**
 * Group results by engine (in first-seen order) and score each.
 *
 * Exported because M12a scores products with the SAME per-engine aggregation
 * (including the retrieval accounting that decides how much of the grounded
 * premium an engine earned). A second copy of this in `core/shopping` would be
 * a second scoring methodology in everything but name.
 */
export declare function scorePerEngine(answers: EngineAnswer[], results: MentionResult[]): EngineScore[];