import type { BaseGrader } from "./baseGrader.js";
import type { AgentRun, Grade, Input } from "./types.js";
export type GraderGrade = {
    grader: BaseGrader;
    grade: Grade;
};
export type InputGrades = {
    input: Input;
    run: AgentRun;
    grades: GraderGrade[];
    gatesPassed: boolean;
};
/**
 * Weighted mean of every grade for one input: a scalar grade contributes its
 * value, a binary grade contributes 1.0 (pass) or 0.0 (fail). `mustPass` is an
 * orthogonal gate (a failed gate zeroes the whole input via the Scorecard); it
 * does not change whether a grade contributes here. An input with no grades
 * scores 0.
 */
export declare function inputObjective(grades: GraderGrade[]): number;
/** Per-candidate grading result: per-input grades plus derived gate/objective readouts. */
export declare class Scorecard {
    readonly perInput: InputGrades[];
    constructor(perInput: InputGrades[]);
    gatesPassed(): boolean;
    /** Per-input objective; a gate-failed input scores 0. */
    inputScores(): number[];
    objective(): number;
    /** The canonical gate-aware comparison score: the raw objective when every
     *  `mustPass` gate is satisfied, otherwise 0. This is what every optimizer
     *  uses to compare candidates, and what `OptimizeResult.trainObjective` and
     *  `baselineObjective` report. Prefer this over inlining
     *  `s.gatesPassed() ? s.objective() : 0`. */
    gatedObjective(): number;
}