import assert from "node:assert/strict";
import { readFileSync } from "node:fs";
import test from "node:test";

import { OPEN_ENGINE_CAPABILITY_CEILING } from "./rectification-v9-test-support.ts";

import { decideRectification } from "../src/lib/rectification-agentic/core/rectification-decision.ts";
import { trainingScoreableGate } from "../src/lib/rectification-agentic/v9/evidence-model.ts";
import { RECTIFICATION_SKILL_VERSION } from "../src/lib/rectification-agentic/v9/case-status.ts";
import { buildMethodFollowupPlan, holdoutFollowupFor } from "../src/lib/rectification-agentic/v9/method-followup.ts";
import {
  canShowRectificationSelectionCards,
  parseRectificationCandidateResult,
  workingRectificationHouseTable,
} from "../src/lib/rectification-candidate-result.ts";
import { decideFromDossier } from "../src/lib/rectification-agentic/v9/decision-from-dossier.ts";
import { persistNextInterviewIfIdle } from "../src/lib/rectification-agentic/v9/answer-choice.ts";
import { evidenceLedgerFingerprint, parseV9CaseDossier } from "../src/lib/rectification-agentic/v9/tool-service.ts";
import { latestResultToolProjection } from "../src/mastra/rectification-v9-tools.ts";
import { isRenderableChoiceOpenQuestion } from "../src/lib/rectification-agentic/v9/server-focus.ts";
import { projectCurrentQuestion } from "../src/lib/rectification-agentic/v9/turn-decision.ts";
import { interviewQuestionBlocksAdoptOffer } from "../src/lib/rectification-agentic/v9/turn-question.ts";
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 {
  CASE_ID,
  USER_ID,
  candidateSnapshotFixture,
  computeFixture,
  dossierFixture,
  fakeAccounting,
  receiptHandlers,
} from "./rectification-v9-test-support.ts";

const STYLE_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 TIED = [
  { time: "04:47", score: 12 },
  { time: "04:51", score: 12 },
  { time: "04:53", score: 11 },
  { time: "04:59", score: 11 },
  { time: "05:00", score: 11 },
  { time: "05:07", score: 11 },
  { time: "05:12", score: 11 },
  { time: "05:14", score: 8 },
  { time: "05:15", score: 7 },
];

const NARROW_LEAD = [
  { time: "04:47", score: 34 },
  { time: "04:51", score: 33 },
  { time: "04:53", score: 33 },
];

function dated(
  id: string,
  domain: string,
  eventKind: string,
  occurredFrom: string,
  extra: {
    occurredTo?: string | null;
    datePrecision?: "year" | "month" | "day" | "range" | "unknown";
    status?: "confirmed" | "draft";
  } = {},
) {
  return {
    id,
    status: extra.status ?? ("confirmed" as const),
    domain,
    datePrecision: extra.datePrecision ?? ("month" as const),
    occurredFrom,
    occurredTo: extra.occurredTo ?? null,
    eventKind,
  };
}

/** 19-row ledger from the stalled case: 15 scoreable, 4 domains; occupation never recorded. */
const CASE_EVIDENCE = [
  dated("e-edu-start", "education", "education_start", "2016-09-01"),
  dated("e-edu-complete", "education", "education_completion", "2020-06-01"),
  dated("e-edu-interrupt", "education", "education_interruption", "2021-01-01", {
    occurredTo: "2023-07-01",
    datePrecision: "range",
  }),
  dated("e-edu-change", "education", "education_change", "2023-01-01", { datePrecision: "year" }),
  dated("e-career-entry-2020", "career", "career_entry", "2020-04-01"),
  dated("e-career-exit-2020", "career", "career_exit", "2020-10-01"),
  dated("e-career-entry-2024", "career", "career_entry", "2024-04-07", { datePrecision: "day" }),
  dated("e-career-exit-2026", "career", "career_exit", "2026-08-11", { datePrecision: "day" }),
  dated("e-career-change-2022", "career", "career_change", "2022-12-01"),
  dated("e-career-change-2024", "career", "career_change", "2024-01-01", { datePrecision: "year" }),
  dated("e-career-range", "career", "career_change", "2020-04-01", {
    occurredTo: "2020-10-01",
    datePrecision: "range",
  }),
  dated("e-career-draft-a", "career", "career_change", "", {
    datePrecision: "unknown",
    status: "draft",
    occurredTo: null,
  }),
  dated("e-career-draft-b", "career", "career_entry", "", {
    datePrecision: "unknown",
    status: "draft",
    occurredTo: null,
  }),
  dated("e-rel-2024-05", "relationship", "relationship_change", "2024-05-01"),
  dated("e-rel-start", "relationship", "relationship_start", "2024-06-01"),
  dated("e-rel-end", "relationship", "relationship_end", "2024-08-08", { datePrecision: "day" }),
  dated("e-reloc", "relocation", "home_change", "2022-10-01"),
  dated("e-family", "family", "family_event", "2016-05-01"),
].map((item) => ({
  ...item,
  occurredFrom: item.occurredFrom || null,
}));

const OCCUPATION_FOCUS = {
  intent: "collect_method_evidence" as const,
  targetDomain: "occupation",
  targetKind: "occupation_note",
  questionId: "collect:occupation:collect_method_evidence",
};

function yearlessProbe(layer: string, gain: number, domain: string) {
  return {
    probeId: `contrast:varga.${layer}.04:47/05:00`,
    candidateSetVersion: "04:47-05:15",
    question: `当前几个候选在 ${layer} 上还分得开。`,
    expectedOutcomes: [
      { outcomeId: "yes" as const, supportsCandidateIds: ["04:47"], conflictsCandidateIds: ["05:00"] },
      { outcomeId: "no" as const, supportsCandidateIds: ["05:00"], conflictsCandidateIds: ["04:47"] },
    ],
    candidateSplitHash: `varga.${layer}.04:47/05:00`,
    informationGain: gain,
    sourceFeatures: [{ technique: layer.toUpperCase(), calculationResultId: null }],
    domain,
    year: null as number | null,
    semanticKey: `varga.${layer}.04:47/05:00`,
    choiceKind: "existence" as const,
    styleOptions: STYLE_OPTIONS.map((item) => ({
      label: item.label,
      answerClass: item.answer_class,
    })),
  };
}

const YEARLESS_PACKET = {
  candidateSetVersion: "04:47-05:15",
  vargaDifferences: [] as const,
  probes: [
    yearlessProbe("d24", 2.5, "education"),
    yearlessProbe("d7", 1.22, "family"),
    yearlessProbe("d4", 0.99, "relocation"),
    yearlessProbe("d5", 0.5, "education"),
  ],
};

function occupationPlan(
  extra: Partial<Parameters<typeof buildMethodFollowupPlan>[0]> = {},
) {
  return buildMethodFollowupPlan({
    evidence: CASE_EVIDENCE,
    contrastPacket: YEARLESS_PACKET,
    candidatesSeparated: false,
    ...extra,
  });
}

function twelveHouses(sign: string, occupant?: string) {
  return Array.from({ length: 12 }, (_, index) => ({
    house: index + 1,
    sign,
    occupants: index === 0 && occupant ? [occupant] : [],
  }));
}

const CANDIDATE_IDS = [
  "88888888-8888-4888-8888-888888888881",
  "88888888-8888-4888-8888-888888888882",
] as const;

test("skill version stays 10.0.15 after the range-delivery bump", () => {
  assert.equal(RECTIFICATION_SKILL_VERSION, "10.0.15");
});

test("nineteen-row ledger opens the training gate with four scoreable domains", () => {
  const gate = trainingScoreableGate(CASE_EVIDENCE);
  assert.equal(gate.open, true);
  assert.ok(gate.trainingCount >= 3);
  assert.ok(gate.trainingDomainCount >= 2);
  assert.ok(CASE_EVIDENCE.length >= 15);
});

test("career answers under an occupation collect focus do not cover occupation before ledger norm", () => {
  const plan = occupationPlan();
  assert.equal(plan.methods.find((item) => item.method_id === "occupation")?.status, "uncovered");
  assert.equal(
    CASE_EVIDENCE.some((item) => item.domain === "occupation" && item.eventKind === "occupation_note"),
    false,
  );
});

test("answering occupation collect remaps a career-domain job description onto occupation_note", async () => {
  const { applyOccupationCollectLedgerNorm } = await import(
    "../src/lib/rectification-agentic/v9/evidence-model.ts"
  );
  const remapped = applyOccupationCollectLedgerNorm(OCCUPATION_FOCUS, [{
    domain: "career",
    eventKind: "career_entry" as const,
    datePrecision: "unknown" as const,
    occurredFrom: null,
    occurredTo: null,
    summary: "长期做有机合成",
    quote: "有机合成",
    subject: "self" as const,
  }]);
  assert.equal(remapped[0]?.domain, "occupation");
  assert.equal(remapped[0]?.eventKind, "occupation_note");
  const plan = occupationPlan({
    evidence: [
      ...CASE_EVIDENCE,
      {
        status: "confirmed" as const,
        domain: remapped[0]!.domain,
        datePrecision: remapped[0]!.datePrecision,
        occurredFrom: remapped[0]!.occurredFrom,
        occurredTo: remapped[0]!.occurredTo,
        eventKind: remapped[0]!.eventKind,
        summary: remapped[0]!.summary,
      },
    ],
    contrastPacket: { candidateSetVersion: "04:47-05:15", vargaDifferences: [], probes: [] },
  });
  assert.equal(plan.methods.find((item) => item.method_id === "occupation")?.status, "covered");
  assert.notEqual(plan.next_followup?.method_id, "occupation");
  assert.notEqual(plan.next_followup?.ask_theme, "occupation");
});

test("occupation coverage fallback uses a closed occupation collect focus plus career evidence", () => {
  const uncovered = occupationPlan({
    contrastPacket: { candidateSetVersion: "04:47-05:15", vargaDifferences: [], probes: [] },
  });
  assert.equal(uncovered.methods.find((item) => item.method_id === "occupation")?.status, "uncovered");
  const covered = occupationPlan({
    contrastPacket: { candidateSetVersion: "04:47-05:15", vargaDifferences: [], probes: [] },
    closedCollectFocuses: [{
      questionId: OCCUPATION_FOCUS.questionId,
      targetDomain: "occupation",
      intent: "collect_method_evidence",
      status: "resolved",
    }],
  });
  assert.equal(covered.methods.find((item) => item.method_id === "occupation")?.status, "covered");
  assert.notEqual(covered.next_followup?.method_id, "occupation");
});

test("career evidence alone still does not cover occupation", () => {
  const plan = occupationPlan({
    contrastPacket: { candidateSetVersion: "04:47-05:15", vargaDifferences: [], probes: [] },
  });
  assert.equal(plan.methods.find((item) => item.method_id === "occupation")?.status, "uncovered");
  // 原值: occupation
  // 新值: d2_finance
  // 原因: 家人已覆盖且无区分卡时，BUG-546 继续收未用带年份域；职业仍未覆盖，只是还没轮到
  assert.equal(plan.next_followup?.method_id, "d2_finance");
});

test("training gate open does not mint yearless existence or quality varga cards", () => {
  const plan = occupationPlan();
  assert.equal(plan.methods.find((item) => item.method_id === "occupation")?.status, "uncovered");
  assert.doesNotMatch(plan.next_followup?.semantic_key ?? "", /^varga\.d(24|7|4|5)\./);
  assert.equal(plan.dropped_probes.some((item) => item.reason === "yearless_ungrounded_contrast"), true);
  // 原值: occupation
  // 新值: d2_finance
  // 原因: yearless 存在/质量卡被丢掉后没有可渲染区分卡，BUG-546 先收财务采集
  assert.equal(plan.next_followup?.method_id, "d2_finance");
  assert.equal(plan.next_followup?.intent, "collect_method_evidence");
  assert.equal(plan.next_followup?.choice_frame, null);
});

test("training gate open still asks a signed yearless D10 style card", () => {
  const d10 = {
    probeId: "contrast:varga.d10.巨蟹座/狮子座",
    candidateSetVersion: "04:47-05:15",
    question: "平时做事，你更接近下面哪一种？",
    expectedOutcomes: [
      { outcomeId: "yes" as const, supportsCandidateIds: ["04:47"], conflictsCandidateIds: ["05:00"] },
      { outcomeId: "weak_yes" as const, supportsCandidateIds: ["05:00"], conflictsCandidateIds: ["04:47"] },
    ],
    candidateSplitHash: "varga.d10.巨蟹座/狮子座",
    informationGain: 1.4,
    sourceFeatures: [{ technique: "D10", calculationResultId: null }],
    domain: "career",
    year: null as number | null,
    semanticKey: "varga.d10.巨蟹座/狮子座",
    choiceKind: "varga_style" as const,
    styleOptions: [
      { label: "做事以照顾人为主，在意团队里的感受", answerClass: "yes" as const, sign: "巨蟹座" },
      { label: "习惯带头，也不排斥站到台前", answerClass: "weak_yes" as const, sign: "狮子座" },
    ],
  };
  const plan = occupationPlan({
    contrastPacket: {
      ...YEARLESS_PACKET,
      probes: [...YEARLESS_PACKET.probes, d10],
    },
  });
  assert.equal(plan.next_followup?.intent, "distinguish_candidates");
  assert.ok(plan.next_followup?.choice_frame);
  assert.equal(plan.next_followup?.semantic_key, d10.semanticKey);
  assert.equal(plan.next_followup?.choice_kind, "varga_style");
});

test("training gate closed still withholds yearless varga cards", () => {
  const short = [
    dated("e-edu", "education", "education_start", "2016-09-01"),
    dated("e-career", "career", "career_entry", "2020-04-01"),
  ];
  assert.equal(trainingScoreableGate(short).open, false);
  const plan = buildMethodFollowupPlan({
    evidence: short,
    contrastPacket: YEARLESS_PACKET,
    candidatesSeparated: false,
  });
  assert.doesNotMatch(plan.next_followup?.semantic_key ?? "", /^varga\.d(24|7|4|5)\./);
  assert.notEqual(plan.next_followup?.intent, "distinguish_candidates");
});

test("training complete with no renderable distinguish card still allows adopt when the engine does", () => {
  const blocked = decideRectification({
    engineCeiling: OPEN_ENGINE_CAPABILITY_CEILING,
    methodCoverageAll: false,
    trainingGateOpen: true,
    candidateScores: NARROW_LEAD,
    discriminatorProbe: null,
  });
  // 原断言 canAdopt=false、sessionOutcome=provisional_range
  // → 新断言 canAdopt=true、sessionOutcome=adopt_representative。
  // coverage（含 occupation）只做问询路由，不再挡采用；确认门仍 fail-closed。
  assert.equal(blocked.canOfferRange, true);
  assert.equal(blocked.canAdopt, true);
  assert.equal(blocked.canConfirmExactMinute, false);
  assert.equal(blocked.nextAction, "offer_provisional_range");
  assert.equal(blocked.sessionOutcome, "adopt_representative");
  const stillClosed = decideRectification({
    engineCeiling: OPEN_ENGINE_CAPABILITY_CEILING,
    methodCoverageAll: false,
    trainingGateOpen: false,
    candidateScores: NARROW_LEAD,
    discriminatorProbe: null,
  });
  assert.equal(stillClosed.canOfferRange, false);
  assert.equal(stillClosed.canAdopt, false);
  assert.equal(stillClosed.nextAction, "ask_fact_collection");
});

test("decideFromDossier offers a range with adopt when training is complete and occupation is still uncovered", () => {
  const decision = decideFromDossier({
    evidence: CASE_EVIDENCE,
    conversationSummary: { activeFocus: null, declinedSkippedTopics: [] },
    latestResult: {
      resultId: "55555555-5555-4555-8555-555555555555",
      selectionAllowed: true,
      confirmationAllowed: false,
      candidates: NARROW_LEAD.map((item, index) => ({
        candidateId: `88888888-8888-4888-8888-88888888888${index}`,
        time: item.time,
        rank: index + 1,
        relativeSupport: item.score,
      })),
      representativeTime: "04:47",
      evidenceLedgerFingerprint: evidenceLedgerFingerprint(CASE_EVIDENCE as never),
      decisionReceipt: {
        accept_allowed: true,
        acceptance_allowed: true,
        propose_allowed: true,
        selection_allowed: true,
        confirmation_allowed: false,
      },
    },
    case: { acceptedTime: null },
  });
  // 旧：训练门开、职业未覆盖即可出牌。新：财务/健康/职业口述未问完保持采集。
  assert.equal(decision.canOfferRange, false);
  assert.equal(decision.sessionOutcome, "collect_evidence");
  assert.equal(decision.nextAction, "ask_fact_collection");
  assert.equal(decision.canConfirmExactMinute, false);
});

test("agent route narrates a numeric range exit and persists a collect when no renderable distinguish card remains", () => {
  const route = readFileSync(new URL("../src/app/api/rectification/agent/route.ts", import.meta.url), "utf8");
  assert.match(route, /nonConvergingRangeNarration/);
  assert.doesNotMatch(route, /可以先按当前区间看盘，也可以再补一件记得时间的经历/);
  const fastPath = route.slice(
    route.indexOf('if (action === "message")'),
    route.indexOf("const requestTime"),
  );
  assert.match(fastPath, /persistNextInterviewIfIdle|isNonConvergingRangeOffer|canOfferRange/);
  assert.doesNotMatch(fastPath, /USER_STOP_PATTERN|parseChoiceKeyFromUserMessage/);
});

test("public house_table and natal_recast follow the representative minute", () => {
  const matched = parseRectificationCandidateResult({
    resultId: "11111111-1111-4111-8111-111111111111",
    candidates: [
      { candidateId: CANDIDATE_IDS[0], rank: 1, time: "04:47", relativeSupport: 12, tiedMinuteCount: 1 },
      { candidateId: CANDIDATE_IDS[1], rank: 2, time: "05:00", relativeSupport: 11, tiedMinuteCount: 1 },
    ],
    overallConfidence: "low",
    selectionAllowed: true,
    confirmationAllowed: false,
    representativeTime: "04:47",
    selectedTime: null,
    decisionReceipt: {
      house_table: { time: "05:00", lagna: "双子座", houses: twelveHouses("双子座", "水星") },
      house_tables_by_time: {
        "04:47": { time: "04:47", lagna: "金牛座", houses: twelveHouses("金牛座", "太阳") },
        "05:00": { time: "05:00", lagna: "双子座", houses: twelveHouses("双子座", "水星") },
      },
      natal_recast: {
        time: "05:00",
        lagna: "双子座",
        user_meaning: "本命宫位已按 05:00 重算（上升 双子座）。下面是本轮实际执行的技法，不能当作唯一分钟确认。",
        unique_minute_claim: false,
        confirmation_allowed: false,
      },
    },
  });
  assert.equal(matched?.representativeTime, "04:47");
  assert.equal(matched?.houseTable?.time, "04:47");
  assert.equal(matched?.houseTable?.lagna, "金牛座");
  assert.equal(matched?.natalRecast?.time, "04:47");
  assert.equal(workingRectificationHouseTable(matched!)?.time, "04:47");
});

test("a mismatched receipt house_table is not emitted with another representative minute", () => {
  const mismatched = parseRectificationCandidateResult({
    resultId: "11111111-1111-4111-8111-111111111111",
    candidates: [
      { candidateId: CANDIDATE_IDS[0], rank: 1, time: "04:47", relativeSupport: 12, tiedMinuteCount: 1 },
      { candidateId: CANDIDATE_IDS[1], rank: 2, time: "05:00", relativeSupport: 11, tiedMinuteCount: 1 },
    ],
    overallConfidence: "low",
    selectionAllowed: true,
    confirmationAllowed: false,
    representativeTime: "04:47",
    selectedTime: null,
    decisionReceipt: {
      house_table: { time: "05:00", lagna: "双子座", houses: twelveHouses("双子座", "水星") },
      natal_recast: {
        time: "05:00",
        lagna: "双子座",
        user_meaning: "本命宫位已按 05:00 重算（上升 双子座）。下面是本轮实际执行的技法，不能当作唯一分钟确认。",
        unique_minute_claim: false,
        confirmation_allowed: false,
      },
    },
  });
  assert.equal(mismatched?.representativeTime, "04:47");
  assert.notEqual(mismatched?.houseTable?.time, "05:00");
  assert.equal(mismatched?.houseTable, null);
  assert.notEqual(mismatched?.natalRecast?.time, "05:00");
});

test("tool projection does not pair a 05:00 house table with a 04:47 representative time", () => {
  const decision = decideRectification({
    engineCeiling: OPEN_ENGINE_CAPABILITY_CEILING,
    methodCoverageAll: true,
    trainingGateOpen: true,
    candidateScores: TIED,
    discriminatorProbe: null,
  });
  const projection = latestResultToolProjection({
    resultId: "55555555-5555-4555-8555-555555555555",
    candidates: TIED.map((item, index) => ({
      candidateId: `88888888-8888-4888-8888-88888888888${index}`,
      time: item.time,
      rank: index + 1,
      relativeSupport: item.score,
      tiedMinuteCount: 1,
    })),
    selectionAllowed: true,
    confirmationAllowed: false,
    representativeTime: "04:47",
    selectedTime: null,
    selectionKind: null,
    algorithmVersion: "test",
    decisionReceipt: {
      house_table: { time: "05:00", lagna: "双子座", houses: twelveHouses("双子座", "水星") },
      natal_recast: {
        time: "05:00",
        lagna: "双子座",
        user_meaning: "本命宫位已按 05:00 重算（上升 双子座）。",
        unique_minute_claim: false,
        confirmation_allowed: false,
      },
    },
  }, decision);
  assert.notEqual(projection.house_table && (projection.house_table as { time?: string }).time, "05:00");
  if (projection.representative_time === "04:47" && projection.house_table) {
    assert.equal((projection.house_table as { time?: string }).time, "04:47");
  }
});

test("collect focus is still not a renderable choice card", () => {
  assert.equal(isRenderableChoiceOpenQuestion({
    question_id: OCCUPATION_FOCUS.questionId,
    prompt: "你平时主要做什么工作？",
    status: "already_open",
    kind: "collect_spoken",
    intent: "collect_method_evidence",
    domain: "occupation",
    focus_id: "11111111-1111-4111-8111-111111111111",
    probe_id: null,
  }), false);
});

const ACCIDENT_EVIDENCE = [
  dated("e-edu-1", "education", "education_start", "2016-09-01"),
  dated("e-edu-2", "education", "education_completion", "2020-06-01"),
  dated("e-rel-1", "relationship", "relationship_start", "2018-05-01"),
  dated("e-rel-2", "relationship", "relationship_end", "2021-08-01"),
  dated("e-fin-1", "finance", "finance_change", "2024-03-01"),
  dated("e-career-1", "career", "career_entry", "2020-04-01"),
  dated("e-career-2", "career", "career_change", "2023-07-01"),
  dated("e-reloc-1", "relocation", "home_change", "2022-10-01"),
  dated("e-health-1", "health", "self_health_event", "2021-11-01"),
  {
    id: "e-occ-1",
    status: "confirmed" as const,
    domain: "occupation",
    datePrecision: "unknown" as const,
    occurredFrom: null,
    occurredTo: null,
    eventKind: "occupation_note",
  },
];

const FAMILY_DECLINED_TOPIC = [{
  target_domain: "family",
  status: "declined",
  questionId: "collect:family:collect_method_evidence",
  intent: "collect_method_evidence",
}];

const CLOSED_FINANCE_FOCUS = [{
  questionId: "collect:finance:collect_method_evidence",
  targetDomain: "finance",
  intent: "collect_method_evidence",
  status: "resolved",
}];

const ACCIDENT_YEARLESS = {
  candidateSetVersion: "04:51-04:53",
  vargaDifferences: [] as const,
  probes: [
    yearlessProbe("d11", 2.5, "finance"),
    yearlessProbe("d2", 2.2, "finance"),
    yearlessProbe("d24", 1.2, "education"),
    yearlessProbe("d5", 0.5, "education"),
    yearlessProbe("d4", 0.99, "relocation"),
    yearlessProbe("d7", 1.22, "family"),
    yearlessProbe("d12", 1.1, "family"),
  ],
};

const ANSWERED_SIX = [
  { semantic_key: "varga.d9.天秤座|天蝎座", answer_class: "yes" },
  { semantic_key: "varga.d10.巨蟹座|狮子座", answer_class: "yes" },
  { semantic_key: "career.2020", answer_class: "yes" },
  { semantic_key: "career.2023", answer_class: "no" },
  { semantic_key: "relocation.2022", answer_class: "no" },
  { semantic_key: "finance.2024", answer_class: "no" },
];

function coveredDomainPlan(
  extra: Partial<Parameters<typeof buildMethodFollowupPlan>[0]> = {},
) {
  return buildMethodFollowupPlan({
    evidence: ACCIDENT_EVIDENCE,
    contrastPacket: ACCIDENT_YEARLESS,
    declinedTopics: FAMILY_DECLINED_TOPIC,
    closedCollectFocuses: CLOSED_FINANCE_FOCUS,
    answeredProbes: ANSWERED_SIX,
    sessionOutcome: "adopt_representative",
    ...extra,
  });
}

test("yearless-to-collect does not re-ask a covered domain after occupation is done", () => {
  const plan = coveredDomainPlan();
  // 原值: next_followup.domain = finance（L2224 取 yearless[0]=D11）
  // 新值: null
  // 原因: 财务已有带年月事件且采集焦点已关闭；守卫跳过已覆盖领域后交付
  assert.equal(plan.next_followup, null);
});

test("yearless-to-collect still asks an uncovered relocation domain", () => {
  const plan = coveredDomainPlan({
    evidence: ACCIDENT_EVIDENCE.filter((item) => item.domain !== "relocation"),
    closedCollectFocuses: CLOSED_FINANCE_FOCUS,
  });
  // 原值: finance（D11 仍排第一）
  // 新值: relocation
  // 原因: 守卫只跳过已覆盖领域，不是删 yearless→采集分支
  assert.equal(plan.next_followup?.domain, "relocation");
  assert.equal(plan.next_followup?.intent, "collect_method_evidence");
  assert.equal(plan.next_followup?.choice_frame, null);
});

function rpcAccidentEvidence(rows: readonly typeof ACCIDENT_EVIDENCE[number][]) {
  return rows.map((item, index) => ({
    id: item.id ?? `e-${index}`,
    source_turn_id: "33333333-3333-4333-8333-333333333333",
    subject: "self",
    event_kind: item.eventKind ?? item.domain,
    domain: item.domain,
    occurred_from: item.occurredFrom,
    occurred_to: item.occurredTo,
    date_precision: item.datePrecision,
    summary: "",
    status: item.status,
    supersedes_evidence_id: null,
    created_at: "2026-09-08T00:00:00.000Z",
  }));
}

function accidentEvidenceFingerprint() {
  return evidenceLedgerFingerprint(rpcAccidentEvidence(ACCIDENT_EVIDENCE).map((item) => ({
    id: item.id,
    eventKind: item.event_kind,
    domain: item.domain,
    occurredFrom: item.occurred_from,
    occurredTo: item.occurred_to,
    datePrecision: item.date_precision,
    summary: item.summary,
    status: item.status,
  })) as never);
}

function yearlessInferenceProbe(layer: string, domain: string, gain: number) {
  return {
    id: `contrast:varga.${layer}.unsigned`,
    semantic_key: `varga.${layer}.unsigned`,
    candidate_split_hash: `varga.${layer}.04:51/04:53`,
    domain,
    year: 0,
    question: `当前几个候选在 ${layer} 上还分得开。`,
    candidate_ids: ["04:51", "04:53"],
    expected_outcomes: [
      { answer_class: "yes" as const, supports: ["04:51"], conflicts: ["04:53"] },
      { answer_class: "no" as const, supports: ["04:53"], conflicts: ["04:51"] },
    ],
    information_gain: gain,
    source: "varga_contrast",
    choice_kind: "existence" as const,
    style_options: STYLE_OPTIONS,
  };
}

function accidentIdleState() {
  const times = ["04:51", "04:52", "04:53"] as const;
  const raw = {
    algorithm_version: INFERENCE_ALGORITHM_VERSION,
    candidate_set_id: candidateSetId("04:51", "04:53", times),
    revision: 6,
    phase: "discrimination" as const,
    result_status: "discriminating" as const,
    range_start: "04:51",
    range_end: "04:53",
    candidates: times.map((time, index) => ({
      id: time,
      time,
      cluster_range: [time, time] as const,
      prior_score: 30 - index,
      posterior_score: 30 - index,
      probability: index === 0 ? 0.5 : 0.25,
      status: "active" as const,
      rank: index + 1,
      strong_conflict_count: 0,
    })),
    events: [
      { id: "e-edu-1", domain: "education", year: 2016, precision: "month" as const, usage: "training" as const },
      { id: "e-edu-2", domain: "education", year: 2020, precision: "month" as const, usage: "training" as const },
      { id: "e-rel-1", domain: "relationship", year: 2018, precision: "month" as const, usage: "training" as const },
      { id: "e-rel-2", domain: "relationship", year: 2021, precision: "month" as const, usage: "holdout" as const },
      { id: "e-fin-1", domain: "finance", year: 2024, precision: "month" as const, usage: "holdout" as const },
      { id: "e-career-1", domain: "career", year: 2020, precision: "month" as const, usage: "training" as const },
      { id: "e-career-2", domain: "career", year: 2023, precision: "month" as const, usage: "training" as const },
      { id: "e-reloc-1", domain: "relocation", year: 2022, precision: "month" as const, usage: "training" as const },
      { id: "e-health-1", domain: "health", year: 2021, precision: "month" as const, usage: "training" as const },
    ],
    probes: [
      yearlessInferenceProbe("d11", "finance", 2.5),
      yearlessInferenceProbe("d24", "education", 1.2),
      yearlessInferenceProbe("d4", "relocation", 0.99),
      yearlessInferenceProbe("d7", "family", 1.22),
    ],
    answered_probes: ANSWERED_SIX.map((item) => ({
      probe_id: `probe:${item.semantic_key}`,
      semantic_key: item.semantic_key,
      candidate_split_hash: item.semantic_key,
      answer_class: item.answer_class as "yes" | "no",
      classified_from: "choice" as const,
    })),
    rounds: ANSWERED_SIX.map((item, index) => ({
      round: index + 1,
      phase: "discrimination" as const,
      probe_id: `probe:${item.semantic_key}`,
      scores_before: { "04:51": 30, "04:52": 29, "04:53": 28 },
      scores_after: { "04:51": 32, "04:52": 29, "04:53": 28 },
      entropy_before: 1.1,
      entropy_after: 1.0,
      eliminated_ids: [] as string[],
      winner_id: null,
      kind: "informative" as const,
    })),
    last_inference_round: null,
    entropy: 1.0,
    representative_time: "04:51",
    credible_range: ["04:51", "04:53"] as const,
    holdout_passed: null,
  };
  const loaded = asInferenceState(raw);
  assert.ok(loaded, "covered-domain accident inference must parse");
  return loaded;
}

function accidentIdleDossier() {
  const fingerprint = accidentEvidenceFingerprint();
  const state = accidentIdleState();
  return dossierFixture({
    evidence: rpcAccidentEvidence(ACCIDENT_EVIDENCE),
    evidenceCount: ACCIDENT_EVIDENCE.length,
    latestResult: candidateSnapshotFixture({
      selectionAllowed: true,
      representativeTime: "04:51",
      evidenceLedgerFingerprint: fingerprint,
      candidates: [
        { candidate_id: "88888888-8888-4888-8888-888888888881", rank: 1, time: "04:51", relative_support: 40, tied_minute_count: 1 },
        { candidate_id: "88888888-8888-4888-8888-888888888882", rank: 2, time: "04:52", relative_support: 35, tied_minute_count: 1 },
        { candidate_id: "88888888-8888-4888-8888-888888888883", rank: 3, time: "04:53", relative_support: 25, tied_minute_count: 1 },
      ],
      decisionReceipt: {
        accept_allowed: true,
        acceptance_allowed: true,
        propose_allowed: true,
        selection_allowed: true,
        confirmation_allowed: false,
        inference_state: state,
      },
    }),
    conversationSummary: {
      confirmed_evidence_summary: [],
      pending_revisions: [],
      active_focus: null,
      declined_skipped_topics: FAMILY_DECLINED_TOPIC,
      candidate_divergence_summary: null,
      missing_evidence_categories: [],
      last_result_policy: null,
      summary_version: 1,
      updated_at: "2026-09-08T00:00:00.000Z",
    },
  });
}

test("idle persist on the covered-domain accident delivers adopt and writes no focus", async () => {
  const rpc = accidentIdleDossier();
  const dossier = parseV9CaseDossier(rpc);
  assert.ok(dossier, "covered-domain accident RPC dossier must parse");
  const decision = decideFromDossier(dossier, { birthDate: "1997-08-08" });
  assert.equal(decision.sessionOutcome, "adopt_representative");
  assert.equal(decision.canAdopt, true);
  assert.equal(decision.stopReason, "probe_pool_exhausted");

  const accounting = fakeAccounting({
    ...receiptHandlers,
    get_agentic_rectification_case_dossier: () => rpc,
    get_agentic_rectification_case_compute: () => computeFixture(),
    set_agentic_rectification_conversation_focus: (_fn, args) => {
      throw new Error(`must not persist ${String(args.p_question_id)}`);
    },
    append_agentic_rectification_turn: () => ({ turn_id: "33333333-3333-4333-8333-333333333333", idempotent: false }),
    finalize_agentic_rectification_turn: () => ({
      turn_id: "33333333-3333-4333-8333-333333333333",
      status: "completed",
      idempotent: false,
    }),
    get_agentic_rectification_turn_receipt: () => null,
  });
  const idle = await persistNextInterviewIfIdle({
    accounting: accounting.client,
    userId: USER_ID,
    caseId: CASE_ID,
  });
  assert.equal(
    accounting.calls.some((item) => item.fn === "set_agentic_rectification_conversation_focus"),
    false,
  );
  assert.equal(idle.terminalNote, true);
  assert.ok(idle.hostNarration);
  assert.equal(projectCurrentQuestion(null), null);
  assert.equal(interviewQuestionBlocksAdoptOffer(null, false), false);
});

test("agent-run still writes the exhaustion gate when idle persist returns terminalNote", () => {
  const agent = readFileSync(new URL("../src/lib/rectification-agentic/v9/agent-run.ts", import.meta.url), "utf8");
  const chat = readFileSync(new URL("../src/components/rectification-agentic-chat.tsx", import.meta.url), "utf8");
  assert.match(agent, /idle\.terminalNote && idle\.hostNarration/);
  assert.match(agent, /persistExhaustionGateTurn/);
  assert.match(chat, /canOfferCards = canShowRectificationSelectionCards/);
  const offer = canShowRectificationSelectionCards(
    parseRectificationCandidateResult({
      resultId: "55555555-5555-4555-8555-555555555555",
      candidates: [
        { candidateId: CANDIDATE_IDS[0], rank: 1, time: "04:51", relativeSupport: 40, tiedMinuteCount: 1 },
        { candidateId: CANDIDATE_IDS[1], rank: 2, time: "04:53", relativeSupport: 35, tiedMinuteCount: 1 },
      ],
      overallConfidence: "medium",
      selectionAllowed: true,
      canAdopt: true,
      confirmationAllowed: false,
      representativeTime: "04:51",
      selectedTime: null,
      sessionOutcome: "adopt_representative",
      decisionReceipt: {
        accept_allowed: true,
        acceptance_allowed: true,
        selection_allowed: true,
        propose_allowed: true,
        confirmation_allowed: false,
      },
    }),
  );
  assert.equal(offer, true);
});

test("holdout occupied treats health and health_pressure as the same line", () => {
  const evidence = [
    ...ACCIDENT_EVIDENCE.filter((item) => item.domain !== "health"),
    dated("e-health-ledger", "health", "self_health_event", "2021-11-01"),
  ];
  const fields = holdoutFollowupFor({
    evidence,
    oosBlindPrompts: [{
      domain: "health_pressure",
      user_meaning: "身体这条线还没用过。",
      used_for_scoring: false,
    }],
  }, new Set());
  // 原值: health_pressure
  // 新值: null
  // 原因: occupied 不认 health / health_pressure 同义时会再问一遍健康
  assert.equal(fields, null);
});