import assert from "node:assert/strict";
import test from "node:test";

import { candidateSetId } from "../src/lib/rectification-agentic/core/build-state.ts";
import { asInferenceState } from "../src/lib/rectification-agentic/core/compose-receipt.ts";
import { INFERENCE_ALGORITHM_VERSION } from "../src/lib/rectification-agentic/core/types.ts";
import type { ConflictProbe } from "../src/lib/rectification-agentic/core/types.ts";
import {
  decideFromDossier,
  rectificationFollowupCatalog,
  type DecisionDossier,
} from "../src/lib/rectification-agentic/v9/decision-from-dossier.ts";
import {
  persistNextInterviewAfterChoice,
  persistNextInterviewIfIdle,
} from "../src/lib/rectification-agentic/v9/answer-choice.ts";
import { resetDeliveryTurnGuardForTests } from "../src/lib/rectification-agentic/v9/delivery-turn-guard.ts";
import { publicNextAction } from "../src/lib/rectification-agentic/core/rectification-decision.ts";
import { evidenceLedgerFingerprint } from "../src/lib/rectification-agentic/v9/tool-service.ts";
import {
  COLLECT_FLOW_BANNED_PHRASES,
  targetedCollectPool,
} from "../src/lib/rectification-agentic/v9/collection-question-pool.ts";
import { rangeDeliveryForSnapshot } from "../src/lib/rectification-agentic/v9/divergence-panel.ts";
import {
  buildMethodFollowupPlan,
} from "../src/lib/rectification-agentic/v9/method-followup.ts";
import {
  alignedProbeId,
  refreshDatedDiscriminatorPoolIfNeeded,
  resetRefreshDiscriminatorProbesForTests,
  setRefreshDiscriminatorProbesForTests,
} from "../src/lib/rectification-agentic/v9/refresh-discriminator-probes.ts";
import { RECTIFICATION_USER_COPY } from "../src/lib/rectification-agentic/user-copy.ts";
import { persistServerOwnedFocus, FOCUS_TARGET_KIND_CHECK } from "../src/lib/rectification-agentic/v9/server-focus.ts";
import type { DiscriminatingEventProbe } from "../src/lib/rectification-agentic/v9/refinement-packet.ts";
import { rectificationQuestionGapState } from "../src/lib/rectification-surface-state.ts";
import {
  CASE_ID,
  FOCUS_ID,
  TURN_ID,
  USER_ID,
  activeFocusFixture,
  candidateSnapshotFixture,
  computeFixture,
  conversationSummaryFixture,
  dossierFixture,
  fakeAccounting,
  receiptHandlers,
} from "./rectification-v9-test-support.ts";

const EXISTENCE_OPTIONS = [
  { label: "明确发生且时间吻合", answer_class: "yes" as const },
  { label: "发生过但程度较弱", answer_class: "weak_yes" as const },
  { label: "明确没有发生", answer_class: "no" as const },
  { label: "这段记不清楚", answer_class: "unsure" as const },
];
const VARGA_OPTIONS = [
  { label: "相处里更在意照顾对方的感受", answer_class: "yes" as const, sign: "巨蟹座" },
  { label: "习惯带头，也不排斥站到台前", answer_class: "weak_yes" as const, sign: "狮子座" },
];
const TIMES = ["04:48", "04:53", "04:54", "04:59", "05:06", "05:07"] as const;
const SCORES: Record<string, number> = {
  "04:48": 10,
  "04:53": 15,
  "04:54": 14,
  "04:59": 13,
  "05:06": 13,
  "05:07": 12,
};

const educationStart = {
  id: "e-edu-start",
  status: "confirmed" as const,
  domain: "education",
  datePrecision: "month" as const,
  occurredFrom: "2016-09-01",
  occurredTo: "2016-09-30",
  eventKind: "education_start",
  summary: "2016年9月上大学",
};
const educationEnd = {
  id: "e-edu-end",
  status: "confirmed" as const,
  domain: "education",
  datePrecision: "month" as const,
  occurredFrom: "2020-06-01",
  occurredTo: "2020-06-30",
  eventKind: "education_completion",
  summary: "2020年6月毕业",
};
const careerIntern = {
  id: "e-career-intern",
  status: "confirmed" as const,
  domain: "career",
  datePrecision: "month" as const,
  occurredFrom: "2020-04-01",
  occurredTo: null,
  eventKind: "career_entry",
  summary: "2020年4月入职实习",
};
const careerLeave = {
  id: "e-career-leave",
  status: "confirmed" as const,
  domain: "career",
  datePrecision: "month" as const,
  occurredFrom: "2020-10-01",
  occurredTo: null,
  eventKind: "career_exit",
  summary: "2020年10月离职",
};
const EVIDENCE = [educationStart, educationEnd, careerIntern, careerLeave];

function uuidAt(index: number) {
  return `00000000-0000-4000-8000-${String(index + 1).padStart(12, "0")}`;
}

function existenceProbe(input: {
  key: string;
  domain: string;
  year: number;
  month?: number;
  question: string;
  source?: string;
  choiceKind?: ConflictProbe["choice_kind"];
}): ConflictProbe {
  return {
    id: `probe:${input.key}`,
    semantic_key: input.key,
    candidate_split_hash: input.key,
    domain: input.domain,
    year: input.year,
    question: input.question,
    candidate_ids: [...TIMES],
    expected_outcomes: [
      { answer_class: "yes", supports: ["04:54"], conflicts: ["05:06"] },
      { answer_class: "weak_yes", supports: [], conflicts: [] },
      { answer_class: "no", supports: ["05:06"], conflicts: ["04:54"] },
      { answer_class: "unsure", supports: [], conflicts: [] },
    ],
    information_gain: 0.4,
    source: input.source ?? "dasha_boundary",
    choice_kind: input.choiceKind ?? "existence",
    style_options: EXISTENCE_OPTIONS,
  };
}

const ASKED_PROBES = [
  existenceProbe({
    key: "career.2023.05.dasha_boundary",
    domain: "career",
    year: 2023,
    month: 5,
    question: "2023 年 5 月前后有没有入职或换工作",
  }),
  existenceProbe({
    key: "relationship.2023.05.dasha_boundary",
    domain: "relationship",
    year: 2023,
    month: 5,
    question: "2023 年 5 月前后感情有没有明显变化",
  }),
  existenceProbe({
    key: "relocation.2015.05.dasha_boundary",
    domain: "relocation",
    year: 2015,
    month: 5,
    question: "2015 年 5 月前后有没有搬家",
  }),
  existenceProbe({
    key: "education.2016.quality",
    domain: "education",
    year: 2016,
    question: "2016 年那次学业发挥怎么样",
    source: "known_event_quality",
    choiceKind: "event_quality",
  }),
  existenceProbe({
    key: "career.2024.04.dasha_boundary",
    domain: "career",
    year: 2024,
    month: 4,
    question: "2024 年 4 月前后有没有入职或换工作",
  }),
  existenceProbe({
    key: "relationship.2024.04.dasha_boundary",
    domain: "relationship",
    year: 2024,
    month: 4,
    question: "2024 年 4 月前后感情有没有明显变化",
  }),
];

const SIXTH = ASKED_PROBES[5]!;

const LEFTOVER_SAME_YEAR = existenceProbe({
  key: "career.2023.dasha_activation",
  domain: "career",
  year: 2023,
  question: "2023 年前后有没有职责加重",
  source: "dasha_activation",
});

const D10_STYLE: ConflictProbe = {
  id: "probe:varga.d10.狮子座/处女座",
  semantic_key: "varga.d10.狮子座/处女座",
  candidate_split_hash: "04:48-05:07:04:49,04:53:varga.d10.狮子座/处女座",
  domain: "career",
  year: 0,
  question: "平时做事，你更接近下面哪一种？",
  candidate_ids: [...TIMES],
  expected_outcomes: [
    { answer_class: "yes", supports: ["04:54"], conflicts: ["05:06"] },
    { answer_class: "weak_yes", supports: ["05:06"], conflicts: ["04:54"] },
    { answer_class: "no", supports: [], conflicts: [] },
    { answer_class: "unsure", supports: [], conflicts: [] },
  ],
  information_gain: 0.9,
  source: "varga_contrast",
  choice_kind: "varga_style",
  style_options: VARGA_OPTIONS,
};

const NAKSHATRA: ConflictProbe = {
  id: "probe:nakshatra.boundary",
  semantic_key: "nakshatra.boundary.a/b",
  candidate_split_hash: "nakshatra.boundary.a/b",
  domain: "other",
  year: 0,
  question: "两组月宿性格里更接近哪一种？",
  candidate_ids: ["04:54", "05:06"],
  expected_outcomes: [
    { answer_class: "yes", supports: ["04:54"], conflicts: ["05:06"] },
    { answer_class: "weak_yes", supports: ["05:06"], conflicts: ["04:54"] },
    { answer_class: "no", supports: [], conflicts: [] },
    { answer_class: "unsure", supports: [], conflicts: [] },
  ],
  information_gain: 0.01,
  source: "nakshatra_boundary",
  choice_kind: "varga_style",
  style_options: VARGA_OPTIONS,
};

function liveState(answeredCount: number) {
  const answered = ASKED_PROBES.slice(0, answeredCount);
  const leftoverYearless = [1, 2, 3, 4, 5].map((index) => existenceProbe({
    key: `yearless.existence.${index}`,
    domain: "career",
    year: 0,
    question: "有没有过一次说不清年份的工作变化",
    source: "varga_contrast",
  }));
  const probes = [
    ...answered,
    LEFTOVER_SAME_YEAR,
    ...leftoverYearless,
    D10_STYLE,
    NAKSHATRA,
  ];
  const candidates = TIMES.map((time, index) => ({
    id: time,
    time,
    cluster_range: [time, time] as const,
    prior_score: SCORES[time] ?? 0,
    posterior_score: SCORES[time] ?? 0,
    probability: (SCORES[time] ?? 0) / 76,
    status: "active" as const,
    rank: index + 1,
    strong_conflict_count: 0,
  }));
  const raw = {
    algorithm_version: INFERENCE_ALGORITHM_VERSION,
    candidate_set_id: candidateSetId("04:48", "05:07", TIMES),
    revision: answeredCount,
    phase: "discrimination" as const,
    result_status: "discriminating" as const,
    range_start: "04:48",
    range_end: "05:07",
    candidates,
    events: [
      { id: educationStart.id, domain: "education", year: 2016, precision: "month" as const, usage: "training" as const },
      { id: educationEnd.id, domain: "education", year: 2020, precision: "month" as const, usage: "training" as const },
      { id: careerIntern.id, domain: "career", year: 2020, precision: "month" as const, usage: "training" as const },
      { id: careerLeave.id, domain: "career", year: 2020, precision: "month" as const, usage: "holdout" as const },
    ],
    probes,
    answered_probes: answered.map((probe) => ({
      probe_id: probe.id,
      semantic_key: probe.semantic_key,
      candidate_split_hash: probe.candidate_split_hash,
      answer_class: probe.semantic_key.includes("2024.04") && probe.domain === "career" ? "yes" as const : "no" as const,
      classified_from: "choice" as const,
    })),
    rounds: answered.map((probe, index) => ({
      round: index + 1,
      phase: "discrimination" as const,
      probe_id: probe.id,
      scores_before: { "04:53": 15 },
      scores_after: { "04:53": 15 },
      entropy_before: 1.4,
      entropy_after: 1.4,
      eliminated_ids: [] as string[],
      winner_id: null,
      kind: "informative" as const,
    })),
    last_inference_round: null,
    entropy: 1.4,
    representative_time: "04:53",
    credible_range: ["04:48", "05:07"] as const,
    holdout_passed: null,
    refresh_count: 0,
    transitions: [
      { layer: "d9", at: "04:52", from_sign: "Cancer", to_sign: "Leo" },
      { layer: "d10", at: "05:00", from_sign: "Cancer", to_sign: "Leo" },
      { layer: "d4", at: "05:00", from_sign: "Aries", to_sign: "Taurus" },
      { layer: "d12", at: "05:00", from_sign: "Aries", to_sign: "Taurus" },
      { layer: "d24", at: "05:00", from_sign: "Aries", to_sign: "Taurus" },
      { layer: "d2", at: "05:00", from_sign: "Aries", to_sign: "Taurus" },
      { layer: "d24", at: "05:06", from_sign: "Taurus", to_sign: "Gemini" },
      { layer: "d11", at: "05:07", from_sign: "Aries", to_sign: "Taurus" },
    ],
  };
  const loaded = asInferenceState(raw);
  assert.ok(loaded);
  return loaded;
}

function eventProbeRow(probe: ConflictProbe): DiscriminatingEventProbe {
  return {
    year: probe.year,
    year_label: probe.year > 0 ? `${probe.year} 年前后` : "",
    domain: probe.domain as DiscriminatingEventProbe["domain"],
    event_family: probe.domain === "family" ? "家人结婚、添丁或住院" : probe.domain,
    source: probe.source === "dasha_activation" || probe.source === "dasha_boundary"
      || probe.source === "known_event_quality"
      ? probe.source
      : "dasha_boundary",
    tracks: ["vimshottari", "narayana"],
    tracks_agree: true,
    unique_minute_claim: false,
    user_meaning: probe.question,
    role: "distinguish",
    information_gain: probe.information_gain,
    semantic_key: probe.semantic_key,
    candidate_split_hash: probe.candidate_split_hash,
    candidate_ids: probe.candidate_ids,
    expected_outcomes: probe.expected_outcomes,
    ...(probe.choice_kind ? { choice_kind: probe.choice_kind } : {}),
    ...(probe.style_options?.length ? { style_options: probe.style_options } : {}),
  };
}

const FAMILY_REFRESH = existenceProbe({
  key: "family.2018.05.dasha_boundary",
  domain: "family",
  year: 2018,
  month: 5,
  question: "2018 年 5 月前后家里有没有添丁或长辈住院",
});

const TARGETED_DECLINED = {
  target_domain: "family",
  status: "declined",
  intent: "collect_method_evidence",
  questionId: "collect:targeted:family",
  target_kind: "targeted:family",
} as const;

const TARGETED_ALL_DECLINED = [
  "relationship",
  "relocation",
  "family",
  "finance",
  "health_pressure",
].map((domain) => ({
  target_domain: domain,
  status: "declined",
  intent: "collect_method_evidence",
  questionId: `collect:targeted:${domain}`,
  target_kind: `targeted:${domain}`,
}));

function accidentDossier(answeredCount: number, extra: {
  activeFocus?: ReturnType<typeof activeFocusFixture> | null;
  refreshCount?: number;
  declinedTopics?: readonly Readonly<Record<string, unknown>>[];
} = {}): DecisionDossier {
  const loaded = liveState(answeredCount);
  const state = extra.refreshCount != null
    ? {
        ...loaded,
        refresh_count: extra.refreshCount,
        refresh_attempts: extra.refreshCount >= 1
          ? [{
              candidate_set_id: loaded.candidate_set_id,
              answer_count: loaded.answered_probes.length,
              result: "no_new_probes" as const,
              at: "2026-09-11T00:00:00.000Z",
            }]
          : loaded.refresh_attempts,
      }
    : loaded;
  const fingerprint = evidenceLedgerFingerprint(EVIDENCE as never);
  return {
    evidence: EVIDENCE,
    conversationSummary: {
      activeFocus: extra.activeFocus
        ? {
            id: extra.activeFocus.id,
            intent: extra.activeFocus.intent,
            targetDomain: extra.activeFocus.target_domain,
            targetKind: extra.activeFocus.target_kind,
            expectedAnswerSchema: extra.activeFocus.expected_answer_schema,
          }
        : null,
      declinedSkippedTopics: [{
        target_domain: "other",
        status: "declined",
        intent: "collect_method_evidence",
        questionId: "collect:invite:more",
        target_kind: "invite_more",
      }, ...(extra.declinedTopics ?? [])],
    },
    latestResult: {
      resultId: "55555555-5555-4555-8555-555555555555",
      selectionAllowed: true,
      confirmationAllowed: false,
      evidenceLedgerFingerprint: fingerprint,
      candidates: TIMES.map((time, index) => ({
        candidateId: uuidAt(index),
        time,
        rank: index + 1,
        relativeSupport: SCORES[time] ?? 0,
      })),
      representativeTime: "04:53",
      decisionReceipt: {
        accept_allowed: true,
        acceptance_allowed: true,
        propose_allowed: true,
        selection_allowed: true,
        confirmation_allowed: false,
        acceptance_reasons: [],
        inference_state: state,
        discriminating_event_probes: [
          ...ASKED_PROBES.map(eventProbeRow),
          eventProbeRow(LEFTOVER_SAME_YEAR),
          eventProbeRow(D10_STYLE),
        ],
        oos_blind_prompts: [],
      },
    },
    case: { acceptedTime: null, status: "collecting_evidence" },
  };
}

function rpcDossier(decision: DecisionDossier, extra: {
  activeFocus?: ReturnType<typeof activeFocusFixture> | null;
} = {}) {
  const evidence = decision.evidence.map((item) => ({
    id: item.id ?? "e-unknown",
    source_turn_id: TURN_ID,
    subject: "self",
    event_kind: item.eventKind ?? item.domain,
    domain: item.domain,
    occurred_from: item.occurredFrom,
    occurred_to: item.occurredTo,
    date_precision: item.datePrecision,
    summary: item.summary ?? item.domain,
    status: item.status,
    supersedes_evidence_id: null,
    created_at: "2026-09-11T00:00:00.000Z",
  }));
  return dossierFixture({
    evidence,
    evidenceCount: evidence.length,
    latestResult: candidateSnapshotFixture({
      selectionAllowed: true,
      confirmationAllowed: false,
      representativeTime: "04:53",
      evidenceLedgerFingerprint: evidenceLedgerFingerprint(decision.evidence as never),
      candidates: decision.latestResult?.candidates?.map((item, index) => ({
        candidate_id: item.candidateId ?? uuidAt(index),
        time: item.time,
        rank: item.rank ?? index + 1,
        relative_support: Math.max(0, Math.min(100, item.relativeSupport ?? 0)),
        tied_minute_count: 1,
      })) ?? [],
      decisionReceipt: { ...(decision.latestResult?.decisionReceipt ?? {}) },
    }),
    conversationSummary: conversationSummaryFixture({
      activeFocus: extra.activeFocus ?? null,
      declinedSkippedTopics: [...decision.conversationSummary.declinedSkippedTopics],
    }),
  });
}

function idleHandlers(decision: DecisionDossier, extra: {
  activeFocus?: ReturnType<typeof activeFocusFixture> | null;
  throwOnFocus?: boolean;
  transitions?: Record<string, unknown>[];
} = {}) {
  return fakeAccounting({
    ...receiptHandlers,
    get_agentic_rectification_case_dossier: () => {
      const base = rpcDossier(decision, extra);
      const last = extra.transitions?.at(-1);
      const inference = last?.p_inference_state;
      const latest = base.latest_result as {
        decision_receipt?: Record<string, unknown>;
      } | null | undefined;
      if (!inference || typeof inference !== "object" || !latest) return base;
      return {
        ...base,
        latest_result: {
          ...latest,
          decision_receipt: {
            ...(latest.decision_receipt ?? {}),
            inference_state: inference,
            refresh_attempts: (inference as { refresh_attempts?: unknown }).refresh_attempts,
          },
        },
      };
    },
    get_agentic_rectification_case_compute: () => computeFixture(),
    append_agentic_rectification_turn: () => ({ turn_id: TURN_ID, idempotent: false }),
    apply_agentic_rectification_choice_action: (_fn, args) => ({
      action_id: args.p_action_id,
      status: "applied",
      idempotent: false,
      question_id: args.p_question_id,
      option_id: args.p_option_id,
      probe_id: SIXTH.id,
      revision: Number(args.p_expected_revision) + 1,
      source_quote: args.p_source_quote,
      derived_context: args.p_derived_context,
      narration: args.p_narration,
      focus_status: args.p_focus_status,
    }),
    set_agentic_rectification_conversation_focus: extra.throwOnFocus
      ? () => {
        throw new Error("persist skipped");
      }
      : (_fn, args) => ({
        focus: {
          id: FOCUS_ID,
          case_id: CASE_ID,
          question_id: args.p_question_id,
          intent: args.p_intent,
          target_evidence_id: args.p_target_evidence_id,
          target_domain: args.p_target_domain,
          target_kind: args.p_target_kind,
          expected_answer_schema: args.p_expected_answer_schema,
          status: "active",
          asked_at: "2026-09-11T00:00:00.000Z",
          resolved_at: null,
          asked_turn_id: args.p_asked_turn_id ?? null,
        },
        idempotent: false,
      }),
    finalize_agentic_rectification_turn: () => ({ turn_id: TURN_ID, status: "completed", idempotent: false }),
    get_agentic_rectification_turn_receipt: () => null,
    append_agentic_rectification_inference_transition: (_fn, args) => {
      extra.transitions?.push(args as Record<string, unknown>);
      const inference = args.p_inference_state as {
        candidates?: unknown[];
        candidate_set_id?: string;
        refresh_count?: number;
      } | undefined;
      return {
        result_id: "55555555-5555-4555-8555-555555555555",
        revision: Number(args.p_expected_revision ?? 0) + 1,
        idempotent: false,
        decision_receipt: {
          inference_state: args.p_inference_state,
        },
        decision_state_fingerprint: args.p_decision_state_fingerprint,
        reason: args.p_reason,
        candidates: inference?.candidates?.length ?? 0,
        candidate_set_id: args.p_candidate_set_id ?? inference?.candidate_set_id,
        refresh_count: inference?.refresh_count ?? 0,
      };
    },
  });
}

function warnLines(run: () => Promise<unknown> | unknown) {
  const lines: string[] = [];
  const original = console.warn;
  console.warn = (...args: unknown[]) => {
    lines.push(args.map((item) => String(item)).join(" "));
    original.apply(console, args);
  };
  return Promise.resolve(run()).finally(() => {
    console.warn = original;
  }).then((result) => ({ result, lines }));
}

function followupPlan(dossier: DecisionDossier, sessionOutcome: string) {
  const catalog = rectificationFollowupCatalog(dossier.latestResult, dossier.evidence);
  return buildMethodFollowupPlan({
    ...catalog,
    evidence: dossier.evidence,
    declinedTopics: dossier.conversationSummary.declinedSkippedTopics,
    sessionOutcome: sessionOutcome as never,
    candidatesSeparated: false,
    birthDate: "1997-08-08",
  });
}

test("T0: sixth dated answer must refresh or targeted-collect, not deliver a card", async () => {
  resetDeliveryTurnGuardForTests();
  resetRefreshDiscriminatorProbesForTests();
  setRefreshDiscriminatorProbesForTests(async ({ state }) => ({
    state: { ...state, refresh_count: (state.refresh_count ?? 0) + 1 },
    eventProbes: [],
    candidateSetId: state.candidate_set_id,
    refreshCount: (state.refresh_count ?? 0) + 1,
  }));
  const dossier = accidentDossier(6);
  const decision = decideFromDossier(dossier, { birthDate: "1997-08-08" });
  const plan = followupPlan(dossier, decision.sessionOutcome);
  // 原值: sixth answer → offer_provisional_range / complete_with_range
  // 新值: ask_fact_collection until refresh + targeted collect are exhausted
  // 原因: BUG-654 带年月池空不等于结束
  assert.equal(decision.nextAction, "ask_fact_collection", decision.nextAction);
  assert.equal(decision.canOfferRange, false);
  assert.equal(plan.next_followup?.choice_kind, "existence");
  assert.notEqual(plan.next_followup?.choice_kind, "varga_style");
  assert.notEqual(plan.next_followup?.source, "nakshatra_boundary");
  assert.match(plan.next_followup?.collection_key ?? "", /collect:targeted:relationship/);
  // 原值: 题干「结过婚或订过婚吗？」
  // 新值: 领域全称问法「哪一年都算」
  // 原因: D5 存在性题问整个领域
  assert.equal(
    plan.next_followup?.choice_frame?.prompt,
    "感情上有没有过开始一段认真关系、分手、订婚或结婚，哪一年都算？",
  );
  assert.match(plan.next_followup?.spoken_prompt ?? "", /现在还剩 04:48–05:07 里 6 个候选/);
  assert.doesNotMatch(plan.next_followup?.spoken_prompt ?? "", /能把 04:48 和 05:07 分开/);
  const idleAccounting = idleHandlers(dossier);
  const { result: idle } = await warnLines(() => persistNextInterviewIfIdle({
    accounting: idleAccounting.client,
    userId: USER_ID,
    caseId: CASE_ID,
  }));
  const persisted = idle as Awaited<ReturnType<typeof persistNextInterviewIfIdle>>;
  const host = persisted.hostNarration ?? "";
  assert.ok(host.trim(), "answer/idle transaction must leave a carrier");
  assert.match(host, /家里|收入|搬家|感情|还能再收窄|添丁|住院|结过婚|现在还剩/);
  assert.doesNotMatch(host, /这次给出|最终|做不了|才会变|没有拿到下一个问题/);
  assert.doesNotMatch(host, /能把 04:48 和 05:07 分开/);
  assert.equal(persisted.choiceReady, true);
  const focusWrite = idleAccounting.calls.find((item) => item.fn === "set_agentic_rectification_conversation_focus");
  assert.ok(focusWrite, "targeted collect must become the active focus");
  assert.match(String(focusWrite.args.p_question_id ?? ""), /collect:targeted:/);
  assert.ok(
    (FOCUS_TARGET_KIND_CHECK as readonly string[]).includes(String(focusWrite.args.p_target_kind ?? "")),
    String(focusWrite.args.p_target_kind),
  );
  const schema = focusWrite.args.p_expected_answer_schema as Record<string, unknown> | undefined;
  assert.equal(schema?.targeted_collect, true);
  assert.equal(
    (schema?.choice as { prompt?: string } | undefined)?.prompt,
    "感情上有没有过开始一段认真关系、分手、订婚或结婚，哪一年都算？",
  );
  for (const phrase of COLLECT_FLOW_BANNED_PHRASES) {
    if (phrase === "领域") continue;
    assert.equal(host.includes(phrase), false, phrase);
  }
  resetRefreshDiscriminatorProbesForTests();
});

test("T1: sixth-answer persist refreshes a dated family probe without changing the candidate set", async () => {
  resetDeliveryTurnGuardForTests();
  resetRefreshDiscriminatorProbesForTests();
  setRefreshDiscriminatorProbesForTests(async ({ state }) => {
    const nextCount = (state.refresh_count ?? 0) + 1;
    return {
      state: {
        ...state,
        refresh_count: nextCount,
        probes: [...state.probes, FAMILY_REFRESH],
      },
      eventProbes: [eventProbeRow(FAMILY_REFRESH)],
      candidateSetId: state.candidate_set_id,
      refreshCount: nextCount,
    };
  });
  const dossier = accidentDossier(6);
  const beforeSet = liveState(6).candidate_set_id;
  const decision = decideFromDossier(dossier, { birthDate: "1997-08-08" });
  const accounting = idleHandlers(dossier);
  const next = await persistNextInterviewAfterChoice({
    accounting: accounting.client,
    userId: USER_ID,
    caseId: CASE_ID,
    dossier,
    decisionState: liveState(6),
    nextAction: publicNextAction(decision),
    decision,
    birthDate: "1997-08-08",
  });
  assert.equal(next.choiceReady, true, next.hostNarration);
  assert.match(next.hostNarration, /2018|家里|添丁|住院/);
  assert.doesNotMatch(next.hostNarration, /平时做事|月宿性格/);
  const live = asInferenceState(
    (next as { followup?: { semantic_key?: string } }).followup
      ? dossier.latestResult?.decisionReceipt?.inference_state
      : liveState(6),
  );
  assert.equal(beforeSet, candidateSetId("04:48", "05:07", TIMES));
  assert.equal(live?.candidate_set_id, beforeSet);
  assert.equal(liveState(6).rounds.every((item) => item.kind === "informative"), true);
  assert.match(next.followup?.semantic_key ?? "", /family\.2018|finance\.|relocation\./);
  assert.ok((next.followup?.probe_year ?? 0) >= 2015);
  assert.ok((next.followup?.probe_year ?? 0) <= 2026);
  resetRefreshDiscriminatorProbesForTests();
});

test("T3: skipped persist still leaves a non-empty carrier; 没有了 delivers the range card", async () => {
  resetDeliveryTurnGuardForTests();
  resetRefreshDiscriminatorProbesForTests();
  setRefreshDiscriminatorProbesForTests(async ({ state }) => ({
    state: { ...state, refresh_count: (state.refresh_count ?? 0) + 1 },
    eventProbes: [],
    candidateSetId: state.candidate_set_id,
    refreshCount: (state.refresh_count ?? 0) + 1,
  }));
  const dossier = accidentDossier(6);
  const decision = decideFromDossier(dossier, { birthDate: "1997-08-08" });
  const accounting = idleHandlers(dossier, { throwOnFocus: true });
  const { result, lines } = await warnLines(() => persistNextInterviewAfterChoice({
    accounting: accounting.client,
    userId: USER_ID,
    caseId: CASE_ID,
    dossier,
    decisionState: liveState(6),
    nextAction: publicNextAction(decision),
    decision,
    birthDate: "1997-08-08",
  }));
  const next = result as Awaited<ReturnType<typeof persistNextInterviewAfterChoice>>;
  assert.ok((next.hostNarration ?? "").trim(), "BUG-652: never silent empty carrier");
  // 原值: /目前范围|范围已经收到|能问的都问完了/
  // 新值: 门槛未达时写引导收窄句
  // 原因: D1 20 分钟窗不出卡，改问引导题
  assert.match(next.hostNarration, /目前范围|范围已经收到|能问的都问完了|再对照几件经历会更准/);
  assert.doesNotMatch(next.hostNarration, /没有拿到下一个问题/);
  const skippedDirect = await persistServerOwnedFocus({
    accounting: accounting.client,
    userId: USER_ID,
    caseId: CASE_ID,
    activeFocus: null,
    decisionReceipt: dossier.latestResult?.decisionReceipt ?? null,
    followup: {
      method_id: "d10_career",
      intent: "distinguish_candidates",
      ask_theme: "career_style",
      domain: "career",
      kind_hint: null,
      user_prompt_hint: "ask",
      must_not_label: false,
      choice_frame: null,
      source: "event_probe",
      semantic_key: D10_STYLE.semantic_key,
      choice_kind: "varga_style",
    },
  });
  assert.equal(skippedDirect.status, "skipped");
  const declined = accidentDossier(6, {
    refreshCount: 1,
    declinedTopics: [TARGETED_DECLINED],
  });
  const stillAsking = decideFromDossier(declined, { birthDate: "1997-08-08" });
  // 原值: 拒答任意一条定向补事即出范围卡
  // 新值: 只关掉 family 这条线后仍问剩余线
  // 原因: BUG-661 逐条点选
  assert.equal(stillAsking.nextAction, "ask_fact_collection", stillAsking.nextAction);
  const stillCatalog = rectificationFollowupCatalog(declined.latestResult, declined.evidence);
  assert.ok(
    targetedCollectPool(
      stillCatalog.remainingLayers,
      declined.evidence,
      declined.conversationSummary.declinedSkippedTopics,
      stillCatalog.remainingSplitTimes,
      stillCatalog.remainingCandidateCount,
    ).length > 0,
  );
  const allDeclined = accidentDossier(6, {
    refreshCount: 1,
    declinedTopics: TARGETED_ALL_DECLINED,
  });
  const delivered = decideFromDossier(allDeclined, { birthDate: "1997-08-08" });
  // 原值: 风格题前置把 closed-ceiling 也 hold 成 ask_candidate_discriminator
  // 新值: 耗尽/收口路径直接交付
  // 原因: BUG-688 D2
  assert.ok(
    delivered.nextAction === "offer_provisional_range"
    || delivered.nextAction === "ready_to_adopt"
    || delivered.nextAction === "complete_with_range",
    delivered.nextAction,
  );
  assert.equal(delivered.canOfferRange, true);
  const catalog = rectificationFollowupCatalog(allDeclined.latestResult, allDeclined.evidence);
  assert.equal(
    targetedCollectPool(
      catalog.remainingLayers,
      allDeclined.evidence,
      allDeclined.conversationSummary.declinedSkippedTopics,
      catalog.remainingSplitTimes,
      catalog.remainingCandidateCount,
    ).length,
    0,
  );
  assert.ok(skippedDirect.status === "skipped" || lines.length >= 0);
  resetRefreshDiscriminatorProbesForTests();
});

test("T4: exhausted refresh and declined targeted collect titles the card 目前范围", async () => {
  resetDeliveryTurnGuardForTests();
  resetRefreshDiscriminatorProbesForTests();
  const dossier = accidentDossier(6, {
    refreshCount: 1,
    declinedTopics: TARGETED_ALL_DECLINED,
  });
  const decision = decideFromDossier(dossier, { birthDate: "1997-08-08" });
  // 原值: heldForTieBreak 把 closed-ceiling 压成 ask_candidate_discriminator
  // 新值: 定向补事关完后交付范围卡
  // 原因: BUG-688 D2 耗尽/收口不得 hold
  assert.ok(
    decision.nextAction === "offer_provisional_range"
    || decision.nextAction === "ready_to_adopt"
    || decision.nextAction === "complete_with_range",
    decision.nextAction,
  );
  const delivery = rangeDeliveryForSnapshot({
    decisionReceipt: dossier.latestResult?.decisionReceipt,
    candidates: dossier.latestResult?.candidates,
    representativeTime: decision.representativeTime,
    credibleRange: decision.credibleRange,
    evidence: dossier.evidence,
    declinedTopics: dossier.conversationSummary.declinedSkippedTopics,
  });
  assert.ok((delivery.columns?.length ?? 0) >= 3);
  // 原值: 这次给出的范围 04:48–05:07 · 对照了 4 件经历
  // 新值: 目前范围 04:48–05:07（对照了 4 件经历）
  // 原因: BUG-654 卡片不得把当前范围写成结束
  assert.equal(RECTIFICATION_USER_COPY.rangeDeliveryTitle, "目前范围");
  const title = `${RECTIFICATION_USER_COPY.rangeDeliveryTitle} ${delivery.range?.[0]}–${delivery.range?.[1]}（对照了 ${delivery.event_count} 件经历）`;
  assert.match(title, /^目前范围 04:48–05:07（对照了 4 件经历）$/);
  assert.doesNotMatch(title, /这次给出|最终|结束| · /);
  assert.match(delivery.narrow_hint ?? "", /现在还剩 04:48–05:07 里 6 个候选/);
  // 原值: 收口改为不限领域的补充邀请
  // 新值: 交付卡只写「按现有信息分不开」，不再邀请自由打字
  // 原因: D3 删除自由文本邀请
  assert.match(delivery.narrow_hint ?? "", /按现有信息分不开/);
  assert.doesNotMatch(delivery.narrow_hint ?? "", /不限领域|确切哪一天|问完了/);
  assert.doesNotMatch(delivery.narrow_hint ?? "", /还能再收窄：如果记得/);
  assert.doesNotMatch(delivery.narrow_hint ?? "", /能把 04:48 和 05:07 分开/);
  assert.doesNotMatch(delivery.narrow_hint ?? "", /这次给出|最终/);
  const publicAction = publicNextAction(decision);
  assert.equal(publicAction.can_offer_range, true);
  assert.equal(rectificationQuestionGapState({
    liveQuestionVisible: false,
    questionMissing: true,
    questionLoadFailed: false,
    collectWaiting: false,
    busy: false,
    readonly: false,
    regenerating: false,
    snapshotLoaded: true,
    resumableCase: true,
    retryAttempts: 0,
    offerAwaitingReader: publicAction.can_offer_range,
  }), "idle");
  const idle = await persistNextInterviewIfIdle({
    accounting: idleHandlers(dossier).client,
    userId: USER_ID,
    caseId: CASE_ID,
  });
  // 原值: /目前范围|范围已经收到|能问的都问完了/
  // 新值: 追加 /现在还剩 .+ 里 \d+ 个候选/
  // 原因: persistNextInterviewIfIdle 自己重算决策，没有 options 里的门槛覆盖，
  //       所以它写的是采集侧的区间旁白；禁词断言不变（BUG-751）
  assert.match(
    idle.hostNarration ?? "",
    /目前范围|范围已经收到|能问的都问完了|现在还剩 .+ 里 \d+ 个候选/,
  );
  assert.doesNotMatch(idle.hostNarration ?? "", /这次给出|最终/);
  assert.doesNotMatch(idle.hostNarration ?? "", /平时做事|月宿性格/);
});

test("T0: GET-selected receipt probe is rejected until refresh merges it into inference_state", async () => {
  resetDeliveryTurnGuardForTests();
  resetRefreshDiscriminatorProbesForTests();
  const base = accidentDossier(6);
  const mismatched = {
    ...base,
    latestResult: {
      ...base.latestResult!,
      decisionReceipt: {
        ...(base.latestResult?.decisionReceipt ?? {}),
        discriminating_event_probes: [
          ...((base.latestResult?.decisionReceipt?.discriminating_event_probes as DiscriminatingEventProbe[] | undefined) ?? []),
          eventProbeRow(FAMILY_REFRESH),
        ],
      },
    },
  };
  const getDecision = decideFromDossier(mismatched, { birthDate: "1997-08-08" });
  const getPlan = followupPlan(mismatched, getDecision.sessionOutcome);
  const getKey = getPlan.next_followup?.semantic_key ?? null;
  const persist = await persistServerOwnedFocus({
    accounting: idleHandlers(mismatched).client,
    userId: USER_ID,
    caseId: CASE_ID,
    activeFocus: null,
    decisionReceipt: mismatched.latestResult?.decisionReceipt ?? null,
    followup: getPlan.next_followup,
  });
  console.log("T0 GET probe vs persist rejection", { getKey, persistStatus: persist.status });
  assert.equal(getKey, FAMILY_REFRESH.semantic_key, String(getKey));
  assert.equal(persist.status, "invalid_choice_schema", persist.status);
});

test("T0: last inference row and GET probe key vs persist status after a real refresh", async () => {
  resetDeliveryTurnGuardForTests();
  resetRefreshDiscriminatorProbesForTests();
  setRefreshDiscriminatorProbesForTests(async ({ state }) => {
    const nextCount = (state.refresh_count ?? 0) + 1;
    return {
      state: { ...state, refresh_count: nextCount },
      eventProbes: [eventProbeRow(FAMILY_REFRESH)],
      candidateSetId: state.candidate_set_id,
      refreshCount: nextCount,
    };
  });
  const dossier = accidentDossier(6);
  const decision = decideFromDossier(dossier, { birthDate: "1997-08-08" });
  const transitions: Record<string, unknown>[] = [];
  const accounting = idleHandlers(dossier, { transitions });
  const next = await persistNextInterviewAfterChoice({
    accounting: accounting.client,
    userId: USER_ID,
    caseId: CASE_ID,
    dossier,
    decisionState: liveState(6),
    nextAction: publicNextAction(decision),
    decision,
    birthDate: "1997-08-08",
  });
  const last = transitions.at(-1);
  const inference = last?.p_inference_state as {
    candidates?: unknown[];
    candidate_set_id?: string;
    refresh_count?: number;
    probes?: ReadonlyArray<{ id: string; semantic_key: string }>;
  } | undefined;
  const lastRow = {
    reason: last?.p_reason,
    candidates: inference?.candidates?.length ?? 0,
    candidate_set_id: last?.p_candidate_set_id ?? inference?.candidate_set_id,
    refresh_count: inference?.refresh_count ?? 0,
  };
  console.log("T0 last inference row", lastRow);
  assert.equal(lastRow.reason, "supersede");
  assert.equal(lastRow.candidates, TIMES.length);
  assert.equal(lastRow.candidate_set_id, liveState(6).candidate_set_id);
  assert.equal(lastRow.refresh_count, 1);
  const merged = inference?.probes?.find((item) => item.semantic_key === FAMILY_REFRESH.semantic_key);
  assert.equal(
    merged?.id,
    alignedProbeId(FAMILY_REFRESH, liveState(6).answered_probes),
    merged?.id,
  );
  const refreshedDossier = {
    ...dossier,
    latestResult: {
      ...dossier.latestResult!,
      decisionReceipt: {
        ...(dossier.latestResult?.decisionReceipt ?? {}),
        inference_state: inference,
        discriminating_event_probes: [eventProbeRow(FAMILY_REFRESH)],
      },
    },
  };
  const getDecision = decideFromDossier(refreshedDossier, { birthDate: "1997-08-08" });
  const getPlan = followupPlan(refreshedDossier, getDecision.sessionOutcome);
  const getKey = getPlan.next_followup?.semantic_key ?? null;
  const persist = await persistServerOwnedFocus({
    accounting: accounting.client,
    userId: USER_ID,
    caseId: CASE_ID,
    activeFocus: null,
    decisionReceipt: refreshedDossier.latestResult?.decisionReceipt ?? null,
    followup: getPlan.next_followup,
  });
  console.log("T0 GET probe vs persist", { getKey, persistStatus: persist.status });
  assert.equal(getKey, FAMILY_REFRESH.semantic_key, String(getKey));
  assert.ok(
    persist.status === "created" || persist.status === "already_open",
    persist.status,
  );
  assert.equal(next.choiceReady, true, next.hostNarration);
  resetRefreshDiscriminatorProbesForTests();
});

test("T3: refresh without new engine probes persists an already_answered attempt", async () => {
  resetDeliveryTurnGuardForTests();
  resetRefreshDiscriminatorProbesForTests();
  let engineCalls = 0;
  setRefreshDiscriminatorProbesForTests(async ({ state }) => {
    engineCalls += 1;
    return {
      state: { ...state, refresh_count: (state.refresh_count ?? 0) + 1 },
      eventProbes: [],
      candidateSetId: state.candidate_set_id,
      refreshCount: (state.refresh_count ?? 0) + 1,
    };
  });
  const dossier = accidentDossier(6);
  const transitions: Record<string, unknown>[] = [];
  const accounting = idleHandlers(dossier, { transitions });
  const idle = await persistNextInterviewIfIdle({
    accounting: accounting.client,
    userId: USER_ID,
    caseId: CASE_ID,
  });
  const last = transitions.at(-1);
  const inference = last?.p_inference_state as {
    refresh_attempts?: ReadonlyArray<{
      candidate_set_id?: string;
      answer_count?: number;
      result?: string;
    }>;
    probes?: unknown[];
    candidate_set_id?: string;
  } | undefined;
  assert.equal(last?.p_reason, "already_answered", JSON.stringify(last ?? {}));
  assert.equal(last?.p_raw_answer, "refresh_attempt");
  assert.equal(inference?.refresh_attempts?.at(-1)?.result, "no_new_probes");
  assert.equal(inference?.refresh_attempts?.at(-1)?.answer_count, liveState(6).answered_probes.length);
  assert.equal(inference?.candidate_set_id, liveState(6).candidate_set_id);
  assert.equal((inference as { refresh_count?: number } | undefined)?.refresh_count ?? 0, 0);
  assert.equal(
    (inference?.probes ?? []).some((item) => (
      Boolean(item)
      && typeof item === "object"
      && (item as { semantic_key?: string }).semantic_key === FAMILY_REFRESH.semantic_key
    )),
    false,
  );
  assert.ok((idle.hostNarration ?? "").trim());
  const overlayed = {
    ...dossier,
    latestResult: {
      ...dossier.latestResult!,
      decisionReceipt: {
        ...(dossier.latestResult?.decisionReceipt ?? {}),
        inference_state: inference,
        refresh_attempts: inference?.refresh_attempts,
      },
    },
  };
  const getDecision = decideFromDossier(overlayed, { birthDate: "1997-08-08" });
  assert.equal(getDecision.nextAction, "ask_fact_collection", getDecision.nextAction);
  assert.match(
    followupPlan(overlayed, getDecision.sessionOutcome).next_followup?.collection_key ?? "",
    /collect:targeted:/,
  );
  const second = await persistNextInterviewIfIdle({
    accounting: accounting.client,
    userId: USER_ID,
    caseId: CASE_ID,
  });
  assert.equal(engineCalls, 1, `second refresh called the engine ${engineCalls} times`);
  assert.ok((second.hostNarration ?? idle.hostNarration ?? "").trim());
  resetRefreshDiscriminatorProbesForTests();
});

test("T3: changed candidate set is not persisted even when engine returns a probe", async () => {
  resetDeliveryTurnGuardForTests();
  resetRefreshDiscriminatorProbesForTests();
  setRefreshDiscriminatorProbesForTests(async ({ state }) => ({
    state: { ...state, candidate_set_id: "changed-set" },
    eventProbes: [eventProbeRow(FAMILY_REFRESH)],
    candidateSetId: "changed-set",
    refreshCount: 1,
  }));
  const dossier = accidentDossier(6);
  const transitions: Record<string, unknown>[] = [];
  await persistNextInterviewAfterChoice({
    accounting: idleHandlers(dossier, { transitions }).client,
    userId: USER_ID,
    caseId: CASE_ID,
    dossier,
    decisionState: liveState(6),
    nextAction: publicNextAction(decideFromDossier(dossier, { birthDate: "1997-08-08" })),
    birthDate: "1997-08-08",
  });
  const last = transitions.at(-1);
  assert.equal(last?.p_reason, "already_answered");
  assert.notEqual(last?.p_reason, "supersede");
  assert.equal(last?.p_candidate_set_id, liveState(6).candidate_set_id);
  const inference = last?.p_inference_state as { candidate_set_id?: string; candidates?: unknown[] } | undefined;
  assert.equal(inference?.candidate_set_id, liveState(6).candidate_set_id);
  assert.equal(inference?.candidates?.length, TIMES.length);
  resetRefreshDiscriminatorProbesForTests();
});

test("T3: empty candidate list is not persisted even when engine returns a probe", async () => {
  resetDeliveryTurnGuardForTests();
  resetRefreshDiscriminatorProbesForTests();
  setRefreshDiscriminatorProbesForTests(async ({ state }) => ({
    state: { ...state, candidates: [] },
    eventProbes: [eventProbeRow(FAMILY_REFRESH)],
    candidateSetId: state.candidate_set_id,
    refreshCount: 1,
  }));
  const dossier = accidentDossier(6);
  const transitions: Record<string, unknown>[] = [];
  const refreshed = await refreshDatedDiscriminatorPoolIfNeeded({
    accounting: idleHandlers(dossier, { transitions }).client,
    userId: USER_ID,
    caseId: CASE_ID,
    dossier,
    state: liveState(6),
    hasDatedProbe: false,
  });
  assert.equal(refreshed.refreshed, false);
  assert.equal(refreshed.attemptRecorded, true);
  const last = transitions.at(-1);
  assert.equal(last?.p_reason, "already_answered");
  assert.notEqual(last?.p_reason, "supersede");
  const inference = last?.p_inference_state as { candidates?: unknown[] } | undefined;
  assert.equal(inference?.candidates?.length, TIMES.length);
  resetRefreshDiscriminatorProbesForTests();
});

test("T3: merged probe ids follow the answered naming rule", () => {
  const hashedIncoming = {
    ...FAMILY_REFRESH,
    id: `probe:${FAMILY_REFRESH.semantic_key}:${FAMILY_REFRESH.candidate_split_hash}`,
  };
  assert.equal(
    alignedProbeId(hashedIncoming, liveState(6).answered_probes),
    `probe:${FAMILY_REFRESH.semantic_key}`,
  );
  const hashedAnswers = liveState(6).answered_probes.map((item) => ({
    ...item,
    probe_id: `probe:${item.semantic_key}:${item.candidate_split_hash}`,
  }));
  assert.equal(
    alignedProbeId(FAMILY_REFRESH, hashedAnswers),
    `probe:${FAMILY_REFRESH.semantic_key}:${FAMILY_REFRESH.candidate_split_hash}`,
  );
});