fix(web): rank remaining-minute probes by split and match choice kind

Choice cards used a hardcoded domain menu and always asked existence.
Rank scoring layers by remaining-minute entropy, keep finance and health
volunteer-only, and ask D9/D10 style or exam quality so taps match outcomes.

Co-authored-by: Cursor <cursoragent@cursor.com>

frontend/src/lib/rectification-agentic/core/build-state.ts

@@ -251,13 +251,27 @@ export function answersFromEvidence(
   });
 }
 
-export function classifyChoiceAnswer(key: string): AnswerClass {
+export function classifyChoiceAnswer(key: string, schema?: unknown): AnswerClass {
   if (key === "A") return "yes";
   if (key === "B") return "weak_yes";
-  if (key === "C") return "no";
+  if (key === "C") {
+    if (schemaMapsCToUnsure(schema)) return "unsure";
+    return "no";
+  }
   return "unsure";
 }
 
+function schemaMapsCToUnsure(schema: unknown): boolean {
+  if (!schema || typeof schema !== "object") return false;
+  const row = schema as Record<string, unknown>;
+  if (row.choice_kind !== "varga_style") return false;
+  const choice = row.choice && typeof row.choice === "object" && !Array.isArray(row.choice)
+    ? row.choice as Record<string, unknown>
+    : row;
+  const optionC = typeof choice.option_c === "string" ? choice.option_c : "";
+  return optionC.includes("都不像");
+}
+
 function rebuildWithAnswers(state: InferenceState, incoming: readonly ProbeAnswer[]): InferenceState {
   return buildInferenceState({
     range_start: state.range_start,

frontend/src/lib/rectification-agentic/core/candidate-contrast-packet.ts

@@ -4,6 +4,15 @@
  */
 
 import type { AnswerClass, ConflictProbe } from "./types.ts";
+import { d9StyleLabel, d10StyleLabel } from "../v9/varga-type-tables.ts";
+
+export type ContrastChoiceKind = "existence" | "varga_style" | "event_quality";
+
+export type ContrastStyleOption = Readonly<{
+  label: string;
+  answerClass: AnswerClass;
+  sign?: string;
+}>;
 
 export type ContrastExpectedOutcome = Readonly<{
   outcomeId: string;
@@ -27,6 +36,8 @@ export type CandidateDiscriminatorProbe = Readonly<{
   domain: string | null;
   year: number | null;
   semanticKey: string;
+  choiceKind?: ContrastChoiceKind;
+  styleOptions?: readonly ContrastStyleOption[];
 }>;
 
 export type VargaDifference = Readonly<{
@@ -37,11 +48,15 @@ export type VargaDifference = Readonly<{
 export type WindowScanTransition = Readonly<{
   layer: string;
   at: string;
+  from_sign?: string;
+  to_sign?: string;
 }>;
 
 export type RemainingVargaSplit = Readonly<{
   layer: string;
   groups: readonly (readonly string[])[];
+  signs: readonly (string | null)[];
+  entropy: number;
 }>;
 
 export type CandidateContrastPacket = Readonly<{
@@ -65,12 +80,26 @@ export type EngineContrastProbe = Readonly<{
   }>[];
   left_time?: string;
   right_time?: string;
+  choice_kind?: ContrastChoiceKind;
+  style_options?: readonly Readonly<{
+    label?: string;
+    answer_class?: string;
+    sign?: string;
+  }>[];
 }>;
 
-const REMAINING_LAYER_ORDER = ["d24", "d5", "d10", "d9", "d4"] as const;
+const REMAINING_LAYERS = ["d24", "d5", "d10", "d9", "d4", "d7", "d12", "d2", "d11", "d30"] as const;
+const VOLUNTEER_LAYER_DOMAIN: Readonly<Record<string, string>> = {
+  d2: "finance",
+  d11: "finance",
+  d30: "health_pressure",
+};
 const DUTY_ANSWERED_RE = /技术执行|算法|分析|数据处理|系统维护|组织型|第三个|照顾、家庭|台前|带人|公开担责|程序员|前端|工程师|开发/;
 const EXAM_QUALITY_RE = /失利|失常|复读|没考好|考砸|发挥不好|发挥失常|压力很大/;
 const RELOCATION_RE = /搬家|离乡|迁居|长期异地|离开家/;
+const FAMILY_RE = /家人|父母|子女|兄弟|亲戚/;
+const FINANCE_RE = /收入|资产|财务|欠债|投资/;
+const HEALTH_RE = /健康|住院|手术|事故|持续压力/;
 const LIVE_EVIDENCE = new Set(["confirmed", "draft", "pending_confirmation"]);
 const ANSWER_CLASSES: ReadonlySet<string> = new Set(["yes", "weak_yes", "no", "unsure"]);
 
@@ -109,15 +138,55 @@ export function remainingLayerGroups(
 export function remainingVargaSplits(
   candidateTimes: readonly string[],
   transitions: readonly WindowScanTransition[],
+  volunteeredDomains: readonly string[] = [],
 ): readonly RemainingVargaSplit[] {
   if (candidateTimes.length < 2) return [];
+  const volunteered = new Set(volunteeredDomains);
   const rows: RemainingVargaSplit[] = [];
-  for (const layer of REMAINING_LAYER_ORDER) {
+  for (const layer of REMAINING_LAYERS) {
+    const volunteerDomain = VOLUNTEER_LAYER_DOMAIN[layer];
+    if (volunteerDomain && !volunteered.has(volunteerDomain)) continue;
     const groups = remainingLayerGroups(candidateTimes, transitions, layer);
     if (groups.length < 2) continue;
-    rows.push({ layer, groups });
+    rows.push({
+      layer,
+      groups,
+      signs: remainingGroupSigns(groups, transitions, layer),
+      entropy: groupEntropy(groups),
+    });
   }
-  return rows;
+  return rows.sort((left, right) => (
+    right.entropy - left.entropy
+    || right.groups.length - left.groups.length
+    || left.layer.localeCompare(right.layer)
+  ));
+}
+
+function groupEntropy(groups: readonly (readonly string[])[]): number {
+  const sizes = groups.map((group) => group.length);
+  const total = sizes.reduce((sum, size) => sum + size, 0);
+  if (total <= 0) return 0;
+  return -sizes.reduce((sum, size) => (
+    size > 0 ? sum + (size / total) * Math.log2(size / total) : sum
+  ), 0);
+}
+
+function remainingGroupSigns(
+  groups: readonly (readonly string[])[],
+  transitions: readonly WindowScanTransition[],
+  layer: string,
+): readonly (string | null)[] {
+  const changes = transitions
+    .filter((item) => item.layer === layer)
+    .filter((item) => /^(?:[01]\d|2[0-3]):[0-5]\d$/.test(item.at))
+    .sort((left, right) => clockMinutes(left.at) - clockMinutes(right.at));
+  return groups.map((group) => {
+    const time = group[0];
+    if (!time) return null;
+    const crossed = changes.filter((item) => clockMinutes(item.at) <= clockMinutes(time));
+    if (crossed.length === 0) return changes[0]?.from_sign ?? null;
+    return crossed[crossed.length - 1]?.to_sign ?? changes[0]?.from_sign ?? null;
+  });
 }
 
 export function askedKeysFromLedgerEvidence(
@@ -140,10 +209,34 @@ export function askedKeysFromLedgerEvidence(
     }
     const relocation = item.domain === "relocation" || item.eventKind === "home_change";
     if (relocation || RELOCATION_RE.test(summary)) keys.add("varga.d4");
+    const family = item.domain === "family" || FAMILY_RE.test(summary);
+    if (family) {
+      keys.add("varga.d7");
+      keys.add("varga.d12");
+    }
+    if (item.domain === "finance" || FINANCE_RE.test(summary)) {
+      keys.add("varga.d2");
+      keys.add("varga.d11");
+    }
+    if (item.domain === "health_pressure" || HEALTH_RE.test(summary)) keys.add("varga.d30");
   }
   return [...keys];
 }
 
+export function volunteeredDomainsFromEvidence(
+  evidence: readonly Readonly<{
+    status?: string | null;
+    domain?: string | null;
+  }>[],
+): string[] {
+  const domains = new Set<string>();
+  for (const item of evidence) {
+    if (item.status && !LIVE_EVIDENCE.has(item.status)) continue;
+    if (item.domain) domains.add(item.domain);
+  }
+  return [...domains];
+}
+
 export function askedKeysFromOccupationEvidence(
   evidence: readonly Readonly<{
     status?: string | null;
@@ -164,6 +257,7 @@ export function buildCandidateContrastPacket(input: {
   candidateTimes?: readonly string[];
   transitions?: readonly WindowScanTransition[];
   askedKeys?: readonly string[];
+  volunteeredDomains?: readonly string[];
 }): CandidateContrastPacket {
   const asked = new Set(input.askedKeys ?? []);
   const fromEngine = (input.engineProbes ?? []).flatMap((probe) => {
@@ -175,7 +269,11 @@ export function buildCandidateContrastPacket(input: {
     return [built];
   });
   const remainingSplits = input.remainingSplits
-    ?? remainingVargaSplits(input.candidateTimes ?? [], input.transitions ?? []);
+    ?? remainingVargaSplits(
+      input.candidateTimes ?? [],
+      input.transitions ?? [],
+      input.volunteeredDomains ?? [],
+    );
   const vargaDifferences = vargaDifferencesForPacket({
     remainingSplits,
     windowDifferences: input.vargaDifferences ?? [],
@@ -292,9 +390,30 @@ function probeFromEngine(
     domain: probe.domain ?? null,
     year: probe.year ?? null,
     semanticKey,
+    choiceKind: probe.choice_kind,
+    styleOptions: styleOptionsFromEngine(probe.style_options),
   };
 }
 
+function styleOptionsFromEngine(
+  rows: EngineContrastProbe["style_options"],
+): readonly ContrastStyleOption[] | undefined {
+  if (!rows?.length) return undefined;
+  const parsed = rows.flatMap((row) => {
+    const label = typeof row.label === "string" ? row.label.trim() : "";
+    const answerClass = typeof row.answer_class === "string" && ANSWER_CLASSES.has(row.answer_class)
+      ? row.answer_class as AnswerClass
+      : null;
+    if (!label || !answerClass) return [];
+    return [{
+      label,
+      answerClass,
+      ...(typeof row.sign === "string" && row.sign.trim() ? { sign: row.sign.trim() } : {}),
+    }];
+  });
+  return parsed.length > 0 ? parsed : undefined;
+}
+
 function vargaProbe(
   remainingSplits: readonly RemainingVargaSplit[],
   candidateSetVersion: string,
@@ -320,49 +439,115 @@ function vargaProbeFromRemaining(
   calculationResultId: string | null,
 ): CandidateDiscriminatorProbe {
   const allMinutes = split.groups.flat();
-  const outcomes = remainingOutcomes(split.groups, allMinutes);
+  const choiceKind = remainingChoiceKind(split.layer);
+  const outcomes = remainingOutcomes(split.groups, allMinutes, choiceKind);
   const semanticKey = `varga.${split.layer}.${split.groups.map((group) => group.join("|")).join("/")}`;
   const layerLabel = split.layer.toUpperCase();
   const domain = remainingDomain(split.layer);
-  const question = remainingQuestion(split.layer, layerLabel);
+  const styleOptions = remainingStyleOptions(split, choiceKind);
+  const question = remainingQuestion(split.layer, layerLabel, styleOptions);
   return {
     probeId: `contrast:${semanticKey}`,
     candidateSetVersion,
     question,
     expectedOutcomes: outcomes,
     candidateSplitHash: semanticKey,
-    informationGain: split.layer === "d24" || split.layer === "d5" ? 0.16 : 0.12,
+    informationGain: split.entropy,
     sourceFeatures: [{ technique: layerLabel, calculationResultId }],
     domain,
     year: null,
     semanticKey,
+    choiceKind,
+    ...(styleOptions ? { styleOptions } : {}),
   };
 }
 
+function remainingChoiceKind(layer: string): ContrastChoiceKind {
+  if (layer === "d10" || layer === "d9") return "varga_style";
+  if (layer === "d24" || layer === "d5") return "event_quality";
+  return "existence";
+}
+
+function remainingStyleOptions(
+  split: RemainingVargaSplit,
+  kind: ContrastChoiceKind,
+): readonly ContrastStyleOption[] | undefined {
+  if (kind !== "varga_style") return undefined;
+  const classes = ["yes", "weak_yes", "no"] as const;
+  const options = split.groups.slice(0, 3).flatMap((group, index) => {
+    const sign = split.signs[index];
+    if (!sign) return [];
+    const label = split.layer === "d10" ? d10StyleLabel(sign) : d9StyleLabel(sign);
+    return [{ label, answerClass: classes[index] ?? "unsure", sign }];
+  });
+  return options.length >= 2 ? uniquifyStyleLabels(options) : undefined;
+}
+
+function uniquifyStyleLabels(
+  options: readonly ContrastStyleOption[],
+): readonly ContrastStyleOption[] {
+  const seen = new Set<string>();
+  return options.map((option) => {
+    let label = option.label;
+    if (seen.has(label) && option.sign) label = `${label}（${option.sign}）`;
+    seen.add(label);
+    return { ...option, label };
+  });
+}
+
 function remainingDomain(layer: string): string {
   if (layer === "d24" || layer === "d5") return "education";
   if (layer === "d10") return "career";
   if (layer === "d4") return "relocation";
+  if (layer === "d7" || layer === "d12") return "family";
+  if (layer === "d2" || layer === "d11") return "finance";
+  if (layer === "d30") return "health_pressure";
   return "relationship";
 }
 
-function remainingQuestion(layer: string, layerLabel: string): string {
+function remainingQuestion(
+  layer: string,
+  layerLabel: string,
+  styleOptions?: readonly ContrastStyleOption[],
+): string {
   if (layer === "d24" || layer === "d5") {
     return "当前几个候选在学业盘上还分得开。请核对一段还没用进评分的学业前事：那次高考或重要考试有没有发挥明显失常、压力很大？";
   }
   if (layer === "d10") {
-    return "当前几个候选在事业盘上还分得开。请核对一段还没用进评分的职业前事：长期更接近照顾或家庭，还是台前带人，还是技术执行或分析？";
+    return styleOptions?.length
+      ? "当前几个候选在事业盘上还分得开。长期工作更接近哪一类？"
+      : "当前几个候选在事业盘上还分得开。请核对一段还没用进评分的职业前事：长期更接近照顾或家庭，还是台前带人，还是技术执行或分析？";
+  }
+  if (layer === "d9") {
+    return "当前几个候选在关系盘上还分得开。这段关系更接近哪一种相处？";
   }
   if (layer === "d4") {
     return "当前几个候选在居所盘上还分得开。请核对一段还没用进评分的搬家或离乡：那几年有没有明显搬家、离乡或长期异地？";
   }
+  if (layer === "d7" || layer === "d12") {
+    return "当前几个候选在家人盘上还分得开。那几年有没有家人相关的明显变化？";
+  }
+  if (layer === "d2" || layer === "d11") {
+    return "当前几个候选在财帛盘上还分得开。那几年有没有收入、资产或财务明显变化？";
+  }
+  if (layer === "d30") {
+    return "当前几个候选在健康盘上还分得开。那几年有没有健康、事故或持续压力明显变化？";
+  }
   return `当前几个候选在关系盘上还分得开。请核对一段还没用进评分的感情前事，用来对照 ${layerLabel} 差异。`;
 }
 
 function remainingOutcomes(
   groups: readonly (readonly string[])[],
   allMinutes: readonly string[],
+  kind: ContrastChoiceKind,
 ): ContrastExpectedOutcome[] {
+  if (kind === "varga_style" && groups.length === 2) {
+    return [
+      { outcomeId: "yes", supportsCandidateIds: groups[0], conflictsCandidateIds: groups[1] },
+      { outcomeId: "weak_yes", supportsCandidateIds: groups[1], conflictsCandidateIds: groups[0] },
+      { outcomeId: "unsure", supportsCandidateIds: [], conflictsCandidateIds: [] },
+    ];
+  }
   if (groups.length === 2) {
     return [
       { outcomeId: "yes", supportsCandidateIds: groups[0], conflictsCandidateIds: groups[1] },

frontend/src/lib/rectification-agentic/v9/answer-choice.ts

@@ -119,7 +119,7 @@ export async function applyRectificationChoice(
       optionId,
       scoring,
       appliedInference: false,
-      answerClass: outcomeIdForOption(optionId),
+      answerClass: outcomeIdForOption(optionId, schema),
       sourceQuote: optionQuoteFromSchema(schema, optionId),
       year: null,
       expectedRevision: command.expectedRevision,

frontend/src/lib/rectification-agentic/v9/choice-action.ts

@@ -6,6 +6,7 @@
  */
 
 import type { AnswerClass } from "../core/types";
+import { classifyChoiceAnswer } from "../core/build-state";
 import type { ChoiceKey, RectificationChoiceCard } from "./choice-card";
 
 export const CHOICE_ACTION = "answer_choice" as const;
@@ -30,8 +31,8 @@ export type StructuredProbeDerivedContext = Readonly<{
   answerClass: AnswerClass | null;
 }>;
 
-export function outcomeIdForOption(optionId: ChoiceKey): AnswerClass {
-  return OPTION_ANSWER_CLASS[optionId];
+export function outcomeIdForOption(optionId: ChoiceKey, schema?: unknown): AnswerClass {
+  return classifyChoiceAnswer(optionId, schema);
 }
 
 export function focusStatusForOption(optionId: ChoiceOptionId): "resolved" | "declined" | "skipped" {

frontend/src/lib/rectification-agentic/v9/choice-card.ts

@@ -7,7 +7,7 @@
  * option copy, and never parses A/B/C/D out of assistant prose.
  */
 
-import type { DiscriminatingEventProbe } from "./refinement-packet";
+import type { DiscriminatingEventProbe, EventProbeChoiceKind, EventProbeStyleOption } from "./refinement-packet";
 import type { InternalVargaObservation } from "./varga-observations";
 
 export const CHOICE_MODE = "A/B/C/D";
@@ -39,6 +39,7 @@ export type RectificationChoiceFrame = Readonly<{
   stop_label: string;
   stop_message: string;
   scoring: boolean;
+  choice_kind?: EventProbeChoiceKind;
 }>;
 
 export type AgentChoiceCopy = Readonly<{
@@ -63,6 +64,7 @@ export type RectificationChoiceCard = Readonly<{
   probe_id: string | null;
   case_revision: number | null;
   focus_id: string | null;
+  choice_kind?: EventProbeChoiceKind;
 }>;
 
 export type ChoiceCardFollowup = Readonly<{
@@ -70,6 +72,8 @@ export type ChoiceCardFollowup = Readonly<{
   ask_theme: string;
   domain: string | null;
   user_prompt_hint: string;
+  choice_kind?: EventProbeChoiceKind;
+  style_options?: readonly EventProbeStyleOption[];
 }>;
 
 export type ChoiceCardEvidence = Readonly<{
@@ -84,6 +88,10 @@ const PRIMARY_C = "没有明显发生";
 const SECONDARY_D = "不记得 / 不确定";
 const OPTION_A = "是，大概就在那段时间";
 const OPTION_B = "有类似，但年份不对或不够重大";
+const STYLE_NEITHER = "两边都不像";
+const QUALITY_A = "有，失常或压力很大";
+const QUALITY_B = "有压力，但不算失常";
+const QUALITY_C = "没有明显失常";
 
 const AGE_BAND: Record<string, { lo: number; hi: number; family: string; varga: string | null }> = {
   education: { lo: 16, hi: 18, family: "升学、高考、转学或学习环境变化", varga: "D5 / D24" },
@@ -253,6 +261,8 @@ function hypothesisFor(
   }
   const domain = followupDomain(followup);
   const probe = pickProbe(probes, domain);
+  const kind = followup.choice_kind ?? probe?.choice_kind ?? "existence";
+  const styleOptions = followup.style_options ?? probe?.style_options ?? [];
   const family = probe?.event_family
     ?? (domain ? AGE_BAND[domain]?.family : null)
     ?? "带大概年份的经历";
@@ -271,6 +281,40 @@ function hypothesisFor(
       : probe?.user_meaning
         ?? "用一件带年份的具体生平分开还在比的时间窗。题干自己写，年份不得发明。";
   void observations;
+  if (kind === "varga_style" && styleOptions.length >= 2) {
+    const career = domain === "career" || followup.ask_theme === "career_style";
+    if (styleOptions.length >= 3) {
+      return {
+        prompt: career ? "长期工作更接近哪一类？" : "这段关系更接近哪一种相处？",
+        why,
+        varga,
+        a: styleOptions[0].label,
+        b: styleOptions[1].label,
+        neither: styleOptions[2].label,
+      };
+    }
+    return {
+      prompt: career ? "长期工作更接近哪一类？" : "这段关系更接近哪一种相处？",
+      why,
+      varga,
+      a: styleOptions[0].label,
+      b: styleOptions[1].label,
+      neither: STYLE_NEITHER,
+    };
+  }
+  if (kind === "event_quality") {
+    const dated = probe?.year_label && probe.year_label !== "那段时间";
+    return {
+      prompt: dated
+        ? `${probe.year_label}，那次高考或重要考试有没有发挥明显失常、压力很大？`
+        : "那次高考或重要考试有没有发挥明显失常、压力很大？",
+      why,
+      varga: varga ?? "D5 / D24",
+      a: QUALITY_A,
+      b: QUALITY_B,
+      neither: QUALITY_C,
+    };
+  }
   return eventHypothesis(period, family, why, varga);
 }
 
@@ -308,9 +352,19 @@ export function buildChoiceFrame(
     stop_label: CHOICE_STOP_LABEL,
     stop_message: CHOICE_STOP_MESSAGE,
     scoring,
+    choice_kind: hypothesisKind(followup, input.probes),
   };
 }
 
+function hypothesisKind(
+  followup: ChoiceCardFollowup,
+  probes?: readonly DiscriminatingEventProbe[],
+): EventProbeChoiceKind {
+  return followup.choice_kind
+    ?? pickProbe(probes, followupDomain(followup))?.choice_kind
+    ?? "existence";
+}
+
 function clippedCopy(value: unknown, min: number, max: number): string | null {
   if (typeof value !== "string") return null;
   const text = value.trim().replace(/\s+/g, " ");
@@ -391,6 +445,7 @@ export function mergeChoiceCard(
     probe_id: meta.probe_id ?? null,
     case_revision: meta.case_revision ?? null,
     focus_id: meta.focus_id ?? null,
+    choice_kind: frame.choice_kind,
   };
 }
 
@@ -454,5 +509,8 @@ export function parseRectificationChoiceCard(value: unknown): RectificationChoic
       ? row.case_revision
       : null,
     focus_id: typeof row.focus_id === "string" && row.focus_id.trim() ? row.focus_id : null,
+    ...(row.choice_kind === "existence" || row.choice_kind === "varga_style" || row.choice_kind === "event_quality"
+      ? { choice_kind: row.choice_kind }
+      : {}),
   };
 }

frontend/src/lib/rectification-agentic/v9/inference-adapter.ts

@@ -315,7 +315,7 @@ export function applyChoiceWithoutEvidence(
   }
   const openProbeId = nextProbe(state)?.id ?? null;
   const lastAnsweredId = state.answered_probes.at(-1)?.probe_id ?? null;
-  const answerClass = classifyChoiceAnswer(choiceKey);
+  const answerClass = classifyChoiceAnswer(choiceKey, input.schema);
   if (
     (submittedProbeId && submittedProbeId !== openProbeId && submittedProbeId !== lastAnsweredId && submittedProbeId !== probe.id && submittedProbeId !== probe.semantic_key && submittedProbeId !== `probe:${probe.semantic_key}`)
     || (openProbeId && probe.id !== openProbeId && probe.id !== lastAnsweredId)

frontend/src/lib/rectification-agentic/v9/interview-state.ts

@@ -8,6 +8,7 @@
 import {
   askedKeysFromLedgerEvidence,
   buildCandidateContrastPacket,
+  volunteeredDomainsFromEvidence,
 } from "../core/candidate-contrast-packet.ts";
 import { evaluateCandidateSeparation } from "../core/candidate-separation.ts";
 import { askedProbeKeysFromReceipt, previousInferenceFromReceipt } from "./inference-adapter";
@@ -88,6 +89,7 @@ export function choiceCardFromCaseDossier(dossier: {
     candidateTimes: candidateScores.map((item) => item.time),
     transitions: windowScan?.transitions ?? [],
     askedKeys: askedProbeKeys,
+    volunteeredDomains: volunteeredDomainsFromEvidence(dossier.evidence),
   });
   const userStopped = latestUserStoppedCollecting(dossier.turns ?? []);
   return projectRectificationChoiceCard({

frontend/src/lib/rectification-agentic/v9/method-followup.ts

@@ -94,6 +94,12 @@ export type MethodFollowup = Readonly<{
   semantic_key?: string;
   candidate_split_hash?: string;
   probe_year?: number;
+  choice_kind?: "existence" | "varga_style" | "event_quality";
+  style_options?: readonly Readonly<{
+    label: string;
+    answer_class: string;
+    sign?: string;
+  }>[];
 }>;
 
 export type MethodFollowupPlan = Readonly<{
@@ -470,6 +476,12 @@ function discriminatorFromFollowup(followup: MethodFollowup | null): CandidateDi
     domain: followup.domain,
     year: followup.probe_year ?? null,
     semanticKey: followup.semantic_key ?? followup.method_id,
+    choiceKind: followup.choice_kind,
+    styleOptions: followup.style_options?.map((item) => ({
+      label: item.label,
+      answerClass: item.answer_class as "yes" | "weak_yes" | "no" | "unsure",
+      ...(item.sign ? { sign: item.sign } : {}),
+    })),
   };
 }
 
@@ -785,6 +797,8 @@ export function buildMethodFollowupPlan(input: {
       semantic_key: conflictProbe.semantic_key ?? `${conflictProbe.domain}.${conflictProbe.year}`,
       candidate_split_hash: conflictProbe.candidate_split_hash,
       probe_year: conflictProbe.year,
+      choice_kind: conflictProbe.choice_kind ?? "existence",
+      style_options: conflictProbe.style_options,
     }, true, true);
   } else if (!relationshipCovered && !declined.has("relationship")) {
     next = makeFollowup({
@@ -860,6 +874,12 @@ export function buildMethodFollowupPlan(input: {
       semantic_key: contrastProbe.semanticKey,
       candidate_split_hash: contrastProbe.candidateSplitHash,
       probe_year: contrastProbe.year ?? undefined,
+      choice_kind: contrastProbe.choiceKind ?? "existence",
+      style_options: contrastProbe.styleOptions?.map((item) => ({
+        label: item.label,
+        answer_class: item.answerClass,
+        ...(item.sign ? { sign: item.sign } : {}),
+      })),
     }, true, true);
   } else if (stage === "lagna_frame") {
     next = makeFollowup({

frontend/src/lib/rectification-agentic/v9/refinement-packet.ts

@@ -92,6 +92,8 @@ export type WindowScanTransition = Readonly<{
   layer: WindowScanLayer;
   at: string;
   user_meaning: string;
+  from_sign?: string;
+  to_sign?: string;
 }>;
 
 export type EventDashaLedgerRow = Readonly<{
@@ -179,6 +181,14 @@ export type EventProbeSource =
 
 export type EventProbeRole = "distinguish" | "reverse_verify";
 
+export type EventProbeChoiceKind = "existence" | "varga_style" | "event_quality";
+
+export type EventProbeStyleOption = Readonly<{
+  label: string;
+  answer_class: string;
+  sign?: string;
+}>;
+
 export type DiscriminatingEventProbe = Readonly<{
   year: number;
   year_label: string;
@@ -200,6 +210,8 @@ export type DiscriminatingEventProbe = Readonly<{
   }>[];
   left_time?: string;
   right_time?: string;
+  choice_kind?: EventProbeChoiceKind;
+  style_options?: readonly EventProbeStyleOption[];
 }>;
 
 function asRecord(value: unknown): Readonly<Record<string, unknown>> | null {
@@ -262,6 +274,8 @@ export function parseWindowScanTransitions(value: unknown): readonly WindowScanT
       layer,
       at,
       user_meaning: `${LAYER_LABEL[layer]} 在 ${at} 发生变化`,
+      ...(asText(row.from_sign, 12) ? { from_sign: asText(row.from_sign, 12)! } : {}),
+      ...(asText(row.to_sign, 12) ? { to_sign: asText(row.to_sign, 12)! } : {}),
     });
   }
   return rows;
@@ -474,6 +488,22 @@ export function parseDiscriminatingEventProbes(value: unknown): readonly Discrim
       ...(asText(row.candidate_split_hash, 120) ? { candidate_split_hash: asText(row.candidate_split_hash, 120)! } : {}),
       ...(asTime(row.left_time) ? { left_time: asTime(row.left_time)! } : {}),
       ...(asTime(row.right_time) ? { right_time: asTime(row.right_time)! } : {}),
+      ...(row.choice_kind === "existence" || row.choice_kind === "varga_style" || row.choice_kind === "event_quality"
+        ? { choice_kind: row.choice_kind }
+        : {}),
+      ...(Array.isArray(row.style_options) ? {
+        style_options: row.style_options.flatMap((item) => {
+          const option = asRecord(item);
+          const label = asText(option?.label, 80);
+          const answer = typeof option?.answer_class === "string" ? option.answer_class : "";
+          if (!option || !label || !answer) return [];
+          return [{
+            label,
+            answer_class: answer,
+            ...(asText(option.sign, 12) ? { sign: asText(option.sign, 12)! } : {}),
+          }];
+        }),
+      } : {}),
       ...(Array.isArray(row.expected_outcomes) ? {
         expected_outcomes: row.expected_outcomes.flatMap((item) => {
           const outcome = asRecord(item);

frontend/src/lib/rectification-agentic/v9/server-focus.ts

@@ -69,6 +69,7 @@ function expectedAnswerSchemaFor(
     },
     semantic_key: followup.semantic_key ?? null,
     candidate_split_hash: followup.candidate_split_hash ?? null,
+    choice_kind: frame.choice_kind ?? followup.choice_kind ?? "existence",
   };
   return stampChoiceSchemaWithProbe(
     schema,

frontend/src/lib/rectification-agentic/v9/skill-verification-report.ts

@@ -9,42 +9,7 @@
 import type { EventDashaLedgerRow } from "./refinement-packet";
 import type { WindowScan } from "./varga-observations";
 import type { CandidateSeparation } from "../core/candidate-separation";
-
-const D9_TYPE_TABLE: Readonly<Record<string, { trait: string; spouse: string; marriage: string }>> = {
-  白羊座: { trait: "主动、热情、冲动", spouse: "独立、有活力", marriage: "早期婚姻、激情型" },
-  金牛座: { trait: "稳定、务实、占有欲强", spouse: "稳重、有经济基础", marriage: "晚婚、稳定型" },
-  双子座: { trait: "沟通、多变、好奇心强", spouse: "聪明、善交流", marriage: "多次恋爱、友谊型" },
-  巨蟹座: { trait: "情感丰富、家庭导向", spouse: "温柔、顾家", marriage: "家庭型" },
-  狮子座: { trait: "骄傲、戏剧性、领导欲", spouse: "有魅力、有地位", marriage: "戏剧性" },
-  处女座: { trait: "完美主义、挑剔、服务型", spouse: "细致、有技能", marriage: "晚婚、服务型" },
-  天秤座: { trait: "和谐、美感、合作", spouse: "优雅、有艺术气质", marriage: "美满、合作型" },
-  天蝎座: { trait: "深刻、占有欲、转化", spouse: "神秘、有深度", marriage: "深刻、转化型" },
-  射手座: { trait: "自由、哲学、冒险", spouse: "开放、有学识", marriage: "自由型、精神伴侣" },
-  摩羯座: { trait: "务实、责任、延迟", spouse: "成熟、有事业", marriage: "晚婚、责任型" },
-  水瓶座: { trait: "独立、非传统、友谊", spouse: "独特、有理想", marriage: "非传统、友谊型" },
-  双鱼座: { trait: "浪漫、牺牲、灵性", spouse: "灵性、有艺术天赋", marriage: "灵性、牺牲型" },
-};
-
-const D10_TYPE_TABLE: Readonly<Record<string, { trait: string; occupation: string; style: string }>> = {
-  白羊座: { trait: "领导、创业、竞争", occupation: "创业者、运动员、军人", style: "主动、竞争" },
-  金牛座: { trait: "稳定、财富、艺术", occupation: "金融、艺术、农业", style: "稳定、务实" },
-  双子座: { trait: "沟通、写作、教育", occupation: "教师、作家、销售", style: "多变、沟通" },
-  巨蟹座: { trait: "照顾、家庭、情感", occupation: "护理、餐饮、房地产", style: "照顾、情感" },
-  狮子座: { trait: "领导、表演、创意", occupation: "管理、娱乐、政治", style: "领导、表演" },
-  处女座: { trait: "服务、分析、健康", occupation: "医疗、分析、服务", style: "细致、服务" },
-  天秤座: { trait: "合作、美学、法律", occupation: "法律、艺术、咨询", style: "合作、和谐" },
-  天蝎座: { trait: "研究、转化、危机", occupation: "研究、心理学、危机管理", style: "深度、转化" },
-  射手座: { trait: "教育、哲学、国际", occupation: "教育、出版、国际事务", style: "自由、哲学" },
-  摩羯座: { trait: "管理、责任、延迟", occupation: "管理、政府、建筑", style: "务实、责任" },
-  水瓶座: { trait: "创新、科技、人道", occupation: "科技、人道主义、创新", style: "创新、独立" },
-  双鱼座: { trait: "灵性、艺术、服务", occupation: "艺术、灵性、医疗", style: "灵性、服务" },
-};
-
-function signKey(value: string): string {
-  const trimmed = value.trim();
-  if (trimmed.endsWith("座")) return trimmed;
-  return `${trimmed}座`;
-}
+import { D9_TYPE_TABLE, D10_TYPE_TABLE, signKey } from "./varga-type-tables";
 
 function typeRow(sign: string, table: "d9" | "d10"): string {
   const key = signKey(sign);

frontend/src/lib/rectification-agentic/v9/varga-type-tables.ts

@@ -0,0 +1,52 @@
+/**
+ * D9/D10 type tables for rectification contrast, not fate promises.
+ */
+
+export type D9TypeRow = Readonly<{ trait: string; spouse: string; marriage: string }>;
+export type D10TypeRow = Readonly<{ trait: string; occupation: string; style: string }>;
+
+export const D9_TYPE_TABLE: Readonly<Record<string, D9TypeRow>> = {
+  白羊座: { trait: "主动、热情、冲动", spouse: "独立、有活力", marriage: "早期婚姻、激情型" },
+  金牛座: { trait: "稳定、务实、占有欲强", spouse: "稳重、有经济基础", marriage: "晚婚、稳定型" },
+  双子座: { trait: "沟通、多变、好奇心强", spouse: "聪明、善交流", marriage: "多次恋爱、友谊型" },
+  巨蟹座: { trait: "情感丰富、家庭导向", spouse: "温柔、顾家", marriage: "家庭型" },
+  狮子座: { trait: "骄傲、戏剧性、领导欲", spouse: "有魅力、有地位", marriage: "戏剧性" },
+  处女座: { trait: "完美主义、挑剔、服务型", spouse: "细致、有技能", marriage: "晚婚、服务型" },
+  天秤座: { trait: "和谐、美感、合作", spouse: "优雅、有艺术气质", marriage: "美满、合作型" },
+  天蝎座: { trait: "深刻、占有欲、转化", spouse: "神秘、有深度", marriage: "深刻、转化型" },
+  射手座: { trait: "自由、哲学、冒险", spouse: "开放、有学识", marriage: "自由型、精神伴侣" },
+  摩羯座: { trait: "务实、责任、延迟", spouse: "成熟、有事业", marriage: "晚婚、责任型" },
+  水瓶座: { trait: "独立、非传统、友谊", spouse: "独特、有理想", marriage: "非传统、友谊型" },
+  双鱼座: { trait: "浪漫、牺牲、灵性", spouse: "灵性、有艺术天赋", marriage: "灵性、牺牲型" },
+};
+
+export const D10_TYPE_TABLE: Readonly<Record<string, D10TypeRow>> = {
+  白羊座: { trait: "领导、创业、竞争", occupation: "创业者、运动员、军人", style: "主动、竞争" },
+  金牛座: { trait: "稳定、财富、艺术", occupation: "金融、艺术、农业", style: "稳定、务实" },
+  双子座: { trait: "沟通、写作、教育", occupation: "教师、作家、销售", style: "多变、沟通" },
+  巨蟹座: { trait: "照顾、家庭、情感", occupation: "护理、餐饮、房地产", style: "照顾、情感" },
+  狮子座: { trait: "领导、表演、创意", occupation: "管理、娱乐、政治", style: "领导、表演" },
+  处女座: { trait: "服务、分析、健康", occupation: "医疗、分析、服务", style: "细致、服务" },
+  天秤座: { trait: "合作、美学、法律", occupation: "法律、艺术、咨询", style: "合作、和谐" },
+  天蝎座: { trait: "研究、转化、危机", occupation: "研究、心理学、危机管理", style: "深度、转化" },
+  射手座: { trait: "教育、哲学、国际", occupation: "教育、出版、国际事务", style: "自由、哲学" },
+  摩羯座: { trait: "管理、责任、延迟", occupation: "管理、政府、建筑", style: "务实、责任" },
+  水瓶座: { trait: "创新、科技、人道", occupation: "科技、人道主义、创新", style: "创新、独立" },
+  双鱼座: { trait: "灵性、艺术、服务", occupation: "艺术、灵性、医疗", style: "灵性、服务" },
+};
+
+export function signKey(value: string): string {
+  const trimmed = value.trim();
+  if (!trimmed) return trimmed;
+  return trimmed.endsWith("座") ? trimmed : `${trimmed}座`;
+}
+
+export function d9StyleLabel(sign: string): string {
+  const row = D9_TYPE_TABLE[signKey(sign)];
+  return row?.trait ?? `${signKey(sign)}相处`;
+}
+
+export function d10StyleLabel(sign: string): string {
+  const row = D10_TYPE_TABLE[signKey(sign)];
+  return row?.style ?? `${signKey(sign)}职责`;
+}

frontend/src/mastra/rectification-v9-tools.ts

@@ -85,6 +85,7 @@ import {
   buildCandidateContrastPacket,
   conflictProbesFromContrast,
   selectDiscriminatorProbe,
+  volunteeredDomainsFromEvidence,
 } from "@/lib/rectification-agentic/core/candidate-contrast-packet";
 import { evaluateCandidateSeparation } from "@/lib/rectification-agentic/core/candidate-separation";
 import { offerSessionKinds } from "@/lib/rectification-agentic/core/decide-next-action";
@@ -205,6 +206,7 @@ function contrastPacketFromLatest(
     candidateTimes,
     transitions: windowScan?.transitions ?? [],
     askedKeys: askedDiscriminatorKeys(latest?.decisionReceipt, evidence),
+    volunteeredDomains: volunteeredDomainsFromEvidence(evidence),
   });
 }
 
@@ -879,6 +881,7 @@ export function createRectificationV9Tools(ctx: RectificationV9Context) {
       candidateTimes: score.candidates.map((item) => item.time),
       transitions: windowScan?.transitions ?? [],
       askedKeys: askedDiscriminatorKeys(dossier.latestResult?.decisionReceipt, parsed.evidence),
+      volunteeredDomains: volunteeredDomainsFromEvidence(parsed.evidence),
     });
     const inference = buildCaseInferenceState({
       range: parsed.case.candidateRange,