import type { AgentConfig } from "../types/config.js";
import type { RunResult } from "../types/output.js";
export interface JudgeCallOptions {
    /** Scenario key for the judge run (e.g., "__env_eval__"). */
    scenarioKey: string;
    /** Human-readable name for the judge run. */
    scenarioName: string;
    /**
     * Candidate judge agents in precedence order. When omitted, the judge runs
     * as the same agent that produced the transcript (the agent scores itself).
     * Otherwise see {@link resolveJudgeAgent} for selection rules.
     */
    judging?: AgentConfig[];
}
/**
 * Pick the judge agent for a run from a precedence-ordered list.
 *
 * Prefers the first entry whose adapter name differs from the run's own
 * agent so a fresh perspective evaluates the work. If every entry matches
 * the run's own agent (e.g. a single-agent benchmark), the first entry is
 * still used — the configuration represents an intent to use a
 * specific judge, even if it happens to coincide with the run's agent.
 */
export declare function resolveJudgeAgent(runResult: RunResult, judging: AgentConfig[] | undefined): AgentConfig;
/**
 * Build a human-readable identifier for a judge agent: `<adapter>|<model>` when
 * a model is pinned, otherwise just `<adapter>`. Mirrors the runtime agent name
 * format produced by `normalizeAgents` in the runner so logs and report text
 * line up.
 */
export declare function formatJudgeLabel(judging: AgentConfig): string;
/**
 * Call an LLM judge using either a configured judge agent (when `options.judging`
 * is set) or the same adapter as the test run.
 *
 * Uses the agent's original workspace when available so the judge can
 * independently verify the agent's actual work (files created, endpoints
 * deployed, etc.). Falls back to a disposable temp directory only when
 * no workspace is set (e.g. programmatic API usage without the runner).
 */
export declare function callJudge(runResult: RunResult, prompt: string, options: JudgeCallOptions): Promise<string>;
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