import { Brain } from './Brain';
import { TaskExecutor } from './TaskExecutor';
import { ClassifiedTask } from './IntentClassifier';
import { MissionState } from './MissionState';
import { ExecutionIntent } from './ExecutionIntent';
export declare class OrchestrationLoop {
    private brain;
    private taskExecutor;
    private deriveServiceId;
    private planner;
    private reviewer;
    private synthesizer;
    private registry;
    private capabilityRouter;
    private missionStore;
    private memoryCurator;
    private parallelLoop;
    private agentScoring;
    private dynamicAgentBuilder;
    private squadRegistry;
    private squadRouter;
    private skillRegistry;
    private learningRouter;
    private promotionPipeline;
    private operationalMemory;
    private promotionEngine;
    private promotionGate;
    private reuseEngine;
    private squadScoring;
    private skillScoring;
    private dynamicAgentExecutor;
    private assetReuseRouter;
    private governance;
    private executionModePolicy;
    private governanceScopePolicy;
    private securityEventStore;
    private governanceConsentStore;
    private sandboxPolicy;
    private runtimePolicy;
    private performanceScorecard;
    private benchmarkEngine;
    private optimizationLoop;
    private executionBoard;
    private roleHandoff;
    private cadenceEngine;
    private operatingSystem;
    private releaseGate;
    private squadAutoCreator;
    private subagentLifecycle;
    private serviceCompletionPolicy;
    private outcomeSimulator;
    private consequenceForecaster;
    private serviceStateStore;
    private executionRouter;
    private jobLifecycle;
    private agentTeamRegistry;
    private skillNetworkRegistry;
    constructor(brain: Brain, taskExecutor: TaskExecutor);
    private inferDomainFromGoal;
    private persistMissionAndService;
    run(task: ClassifiedTask, input: string, userId: string, recentHistory: string, intent?: Partial<ExecutionIntent>): Promise<{
        state: MissionState;
        response: string;
        missionPath: string;
    }>;
    /**
     * Story 5.5 — Post-mission learning hook.
     *
     * Fires after the final return of run(). Best-effort:
     *   1. SkillLearningLoop.add() — record a candidate if the mission
     *      surfaced an actionable gap.
     *   2. OmniMemory.saveFact() — index the consequence thought-trace
     *      so future missions with similar intent retrieve prior rationale.
     *
     * Disable via OPENLIFE_POST_MISSION_HOOK=off.
     *
     * NOTE: completely silent on failure — this is advisory, never a gate.
     */
    private firePostMissionHook;
    /**
     * Story 8.3 helper — summarize the mission's consequence thought-trace
     * via Brain and persist it to OmniMemory so future missions retrieve
     * prior rationale. Silent on every failure path; never blocks.
     */
    private consolidateToMemory;
    /**
     * Story 13.1 (v1.5) — Brain-driven post-mission evaluation.
     *
     * Judges the completed mission against its `successCriteria` and writes
     * a structured evaluation to `.openlife/evaluations/<taskId>.json` via
     * `MissionEvaluationStore`. Two paths:
     *
     *   • Brain available → asks Brain for `{ score: 0-100, verdict: 'ready_for_review' | 'needs_iteration', risks: string[], rationale: string }`.
     *   • No Brain key → falls back to the existing heuristic `judge()` so
     *     callers always get a record.
     *
     * Silent on every failure path. The evaluation file is additive — it
     * never overwrites the mission state itself.
     */
    private evaluateMission;
    private parseEvaluationJson;
}
