fix(rectification): guarantee nonterminal turn exits

frontend/src/app/api/rectification/agent/route.ts

@@ -13,7 +13,6 @@ import { decideFromDossier, rectificationFollowupCatalog } from "@/lib/rectifica
 import {
   applyRectificationChoice,
   applyCollectFocusDenial,
-  ensureNonTerminalTurnExit,
   persistNextInterviewIfIdle,
 } from "@/lib/rectification-agentic/v9/answer-choice";
 import { mapRectificationRpcError } from "@/lib/rectification-agentic/v9/case-service";
@@ -41,6 +40,12 @@ import {
 import { persistServerOwnedFocus, openQuestionFromPersistedFocus, isCollectFocusSchema, isRenderableChoiceOpenQuestion } from "@/lib/rectification-agentic/v9/server-focus";
 import { buildMethodFollowupPlan } from "@/lib/rectification-agentic/v9/method-followup";
 import { isNonConvergingRangeOffer, nonConvergingRangeNarration } from "@/lib/rectification-agentic/core/rectification-decision";
+import {
+  awaitTurnExitBeforeResponse,
+  finalizeSuccessfulTurnExit,
+  RECTIFICATION_ACTION_EXECUTION,
+  type RectificationRouteAction,
+} from "@/lib/rectification-agentic/v9/turn-exit";
 
 export const runtime = "nodejs";
 export const maxDuration = 240;
@@ -86,6 +91,9 @@ const agentRequestSchema = z.object({
   clientActionId: z.string().uuid().optional(),
 }).strict();
 
+type ParsedRectificationAction = z.infer<typeof agentRequestSchema>["action"];
+const rectificationActionExecution: Record<ParsedRectificationAction, (typeof RECTIFICATION_ACTION_EXECUTION)[RectificationRouteAction]> = RECTIFICATION_ACTION_EXECUTION;
+
 function actionToBudget(action: "opening" | "message" | "read_only"): RectificationAgentAction {
   if (action === "opening") return "opening";
   if (action === "read_only") return "read_only";
@@ -170,7 +178,8 @@ export async function POST(request: Request) {
 
   const userId = user.id;
   const { caseId, sessionId, requestId, action } = parsed.data;
-  const isStructuredChoice = action === "answer_choice" || action === "stop_and_review";
+  const execution = rectificationActionExecution[action];
+  const isStructuredChoice = execution === "immediate";
 
   // Feature selector: the V9 runtime is DB-driven. When the flag is not
   // published/enabled, no new runs are served (legacy stays read-only).
@@ -246,8 +255,15 @@ export async function POST(request: Request) {
     );
   }
 
-  if (isStructuredChoice) {
-    const actionId = parsed.data.actionId;
+  const selectedModel = isStructuredChoice
+    ? null
+    : await resolveSessionLanguageModel(
+      chatSession.model_id,
+      chatSession.model_config_version,
+    );
+  const immediateResponse = await (async (): Promise<Response | null> => {
+    if (isStructuredChoice) {
+      const actionId = parsed.data.actionId;
     const focusId = parsed.data.focusId;
     const expectedRevision = parsed.data.expectedRevision;
     if (!actionId || !focusId || expectedRevision === undefined) {
@@ -309,11 +325,8 @@ export async function POST(request: Request) {
     }
   }
 
-  const selectedModel = await resolveSessionLanguageModel(
-    chatSession.model_id,
-    chatSession.model_config_version,
-  );
-  if (!selectedModel) {
+  const resolvedModel = selectedModel;
+  if (!resolvedModel) {
     return NextResponse.json(
       { error: "模型暂不可用", message: "请选择其他模型后重新发送，本次不会扣除点数。" },
       { status: 409 },
@@ -328,7 +341,7 @@ export async function POST(request: Request) {
       if (focus && choice) {
         let classified = null;
         try {
-          classified = await classifyRectificationTurnIntent(selectedModel, {
+          classified = await classifyRectificationTurnIntent(resolvedModel, {
             focus,
             userMessage: parsed.data.message ?? "",
             caseStatus,
@@ -537,6 +550,34 @@ export async function POST(request: Request) {
     }
   }
 
+    return null;
+  })();
+  if (immediateResponse) {
+    if (immediateResponse.status !== 200) return immediateResponse;
+    const response = await awaitTurnExitBeforeResponse(
+      immediateResponse,
+      () => finalizeSuccessfulTurnExit({
+        accounting: accounting as never,
+        userId,
+        caseId,
+        action,
+      }),
+    );
+    return response;
+  }
+  if (action === "answer_choice" || action === "stop_and_review") {
+    return NextResponse.json(
+      { error: "选择题处理失败", message: "请稍后重试。" },
+      { status: 500 },
+    );
+  }
+  if (!selectedModel) {
+    return NextResponse.json(
+      { error: "模型暂不可用", message: "请选择其他模型后重新发送，本次不会扣除点数。" },
+      { status: 409 },
+    );
+  }
+
   const requestTime = new Date();
   const chinaTime = new Date(requestTime.getTime() + 8 * 60 * 60 * 1000)
     .toISOString()
@@ -673,30 +714,14 @@ export async function POST(request: Request) {
         if (!result.ok) {
           send({ type: "error", message: "生时校正暂时不可用，请稍后重试。" });
         } else {
-          if (action === "message" || action === "opening") {
-            try {
-              await persistNextInterviewIfIdle({
-                accounting: accounting as never,
-                userId,
-                caseId,
-              });
-            } catch (error) {
-              console.warn(
-                `[rectification-v9] persist next interview after turn failed case=${caseId} reason=${error instanceof Error ? error.name : "Unknown"}`,
-              );
-            }
-            try {
-              await ensureNonTerminalTurnExit({
-                accounting: accounting as never,
-                userId,
-                caseId,
-              });
-            } catch (error) {
-              console.warn(
-                `[rectification-v9] nonterminal turn exit repair failed case=${caseId} reason=${error instanceof Error ? error.name : "Unknown"}`,
-              );
-            }
-          }
+          // Shared gate owns persistNextInterviewIfIdle then ensureNonTerminalTurnExit;
+          // The shared gate replaces the old message/opening-only cleanup.
+          await finalizeSuccessfulTurnExit({
+            accounting: accounting as never,
+            userId,
+            caseId,
+            action,
+          });
           send({ type: "done", emitted: true });
         }
       } catch (error) {

frontend/src/lib/rectification-agentic/core/rectification-decision.ts

@@ -150,6 +150,7 @@ export type DecideRectificationInput = Readonly<{
   trainingGateOpen?: boolean;
   candidateScores: readonly CandidateScoreRow[];
   discriminatorProbe?: CandidateDiscriminatorProbe | null;
+  nakshatraBoundaryProbe?: CandidateDiscriminatorProbe | null;
   holdoutValidation?: HoldoutValidationStatus;
   accepted?: boolean;
   inferenceCredibleRange?: readonly [string, string] | null;
@@ -277,6 +278,23 @@ export function decideRectification(input: DecideRectificationInput): Rectificat
     if (probe) {
       return discriminateOrExhaust(input, separation, holdout, range, probe, capability, stopReason);
     }
+    if (holdout === "not_started") {
+      return holdoutValidation(separation, range, capability);
+    }
+    if (input.datedMethodCollectOpen === true) {
+      return collect(separation, holdout, range, null, capability, stopReason);
+    }
+    if (input.nakshatraBoundaryProbe) {
+      return discriminateOrExhaust(
+        input,
+        separation,
+        holdout,
+        range,
+        input.nakshatraBoundaryProbe,
+        capability,
+        stopReason,
+      );
+    }
     return stopClass?.kind === "exhausted"
       ? completeWithRange(separation, holdout, range, "exhausted", capability, stopClass.reason)
       : completeWithRange(separation, holdout, range, "offer", capability);

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

@@ -12,6 +12,7 @@ import { RECTIFICATION_TERMINATION_COPY, isNonConvergingRangeOffer, nonConvergin
 import {
   applyChoiceWithoutEvidence,
   previousInferenceFromReceipt,
+  withNakshatraBoundaryProbe,
 } from "./inference-adapter";
 import { decideAfterInferenceChange, decideFromDossier, rectificationFollowupCatalog } from "./decision-from-dossier";
 import type { InferenceState } from "../core/types.ts";
@@ -49,6 +50,7 @@ import {
   spokenFollowupForUser,
 } from "./method-followup";
 import type { SessionOutcomeKind } from "./confirmation-gate";
+import { refinementFromDecisionReceipt } from "./refinement-packet";
 import { projectCurrentQuestion } from "./turn-decision";
 
 export type ApplyChoiceCommand = Readonly<{
@@ -136,7 +138,11 @@ export async function applyRectificationChoice(
   const optionId = command.optionId;
   const questionId = focus.questionId;
   const scoring = schema.scoring !== false && !questionId.endsWith(":holdout");
-  const previous = previousInferenceFromReceipt(dossier.latestResult?.decisionReceipt ?? null);
+  const receipt = dossier.latestResult?.decisionReceipt ?? null;
+  const previous = withNakshatraBoundaryProbe(
+    previousInferenceFromReceipt(receipt),
+    refinementFromDecisionReceipt(receipt).nakshatra_boundary,
+  );
   const answerClass = optionId === "stop" ? null : outcomeIdForOption(optionId, schema);
   if (optionId !== "stop" && !answerClass) {
     throw new RectificationToolServiceError("agentic_rectification_invalid_choice_schema");
@@ -322,8 +328,8 @@ export async function persistNextInterviewAfterChoice(input: {
     followup,
   });
   const open = openQuestionFromPersistedFocus(persistedFocus);
-  if (isRenderableChoiceOpenQuestion(open)) {
-    return { hostNarration: "接下来请点选下面这一问。", choiceReady: true };
+  if (isRenderableChoiceOpenQuestion(open) && open.prompt) {
+    return { hostNarration: open.prompt, choiceReady: true };
   }
   if (followup?.choice_frame) {
     const spokenFollowup = spokenCollectFallbackFollowup(followup);
@@ -749,15 +755,12 @@ ${nonConvergingRangeNarration({
   };
 }
 
-export async function ensureNonTerminalTurnExit(input: {
+async function inspectNonTerminalTurnExit(input: {
   accounting: AccountingClient;
   userId: string;
   caseId: string;
-}): Promise<{ persisted: boolean; choiceReady: boolean; hostNarration: string | null }> {
+}) {
   const dossier = await loadV9CaseDossier(input.accounting, input.userId, input.caseId);
-  if (projectCurrentQuestion(dossier.conversationSummary.activeFocus)) {
-    return { persisted: false, choiceReady: false, hostNarration: null };
-  }
   let birthDate: string | null = null;
   try {
     const compute = await loadV9CaseCompute(input.accounting, input.userId, input.caseId);
@@ -766,12 +769,23 @@ export async function ensureNonTerminalTurnExit(input: {
     birthDate = null;
   }
   const decision = decideFromDossier(dossier, { birthDate });
-  if (
-    dossier.case.acceptedTime
+  const satisfied = Boolean(
+    projectCurrentQuestion(dossier.conversationSummary.activeFocus)
+    || dossier.case.acceptedTime
     || dossier.case.confirmedTime
     || decision.completionStatus === "provisional_range_user_stopped"
     || decision.canAdopt
-  ) {
+  );
+  return { dossier, decision, satisfied };
+}
+
+export async function ensureNonTerminalTurnExit(input: {
+  accounting: AccountingClient;
+  userId: string;
+  caseId: string;
+}): Promise<{ persisted: boolean; choiceReady: boolean; hostNarration: string | null }> {
+  const before = await inspectNonTerminalTurnExit(input);
+  if (before.satisfied) {
     return { persisted: false, choiceReady: false, hostNarration: null };
   }
   console.warn(JSON.stringify({
@@ -779,14 +793,19 @@ export async function ensureNonTerminalTurnExit(input: {
     case_id: input.caseId,
     reason: "missing_question_and_adopt_carrier",
   }));
-  return persistExhaustionCollect({
+  const repaired = await persistExhaustionCollect({
     accounting: input.accounting,
     userId: input.userId,
     caseId: input.caseId,
-    dossier,
-    decision,
-    decisionReceipt: dossier.latestResult?.decisionReceipt,
+    dossier: before.dossier,
+    decision: before.decision,
+    decisionReceipt: before.dossier.latestResult?.decisionReceipt,
   });
+  const after = await inspectNonTerminalTurnExit(input);
+  if (!after.satisfied) {
+    throw new RectificationToolServiceError("agentic_rectification_nonterminal_exit_missing");
+  }
+  return repaired;
 }
 
 function optionQuoteFromSchema(schema: Readonly<Record<string, unknown>>, optionId: ChoiceKey): string | null {

frontend/src/lib/rectification-agentic/v9/decision-from-dossier.ts

@@ -23,7 +23,7 @@ import {
   type HoldoutValidationStatus,
   type RectificationDecision,
 } from "../core/rectification-decision.ts";
-import type { InferenceState } from "../core/types.ts";
+import type { ConflictProbe, InferenceState } from "../core/types.ts";
 import {
   askedDiscriminatorKeys,
   authoritativeCandidateProjection,
@@ -185,6 +185,7 @@ export function contrastPacketFromLatestResult(
   const fromInference: EngineContrastProbe[] = (inference?.probes ?? []).flatMap((probe) => {
     if (answered.has(probe.id) || probe.information_gain <= 0) return [];
     if (probe.source === "known_event_quality") return [];
+    if (probe.source === "nakshatra_boundary") return [];
     return [{
       semantic_key: probe.semantic_key,
       candidate_split_hash: probe.candidate_split_hash,
@@ -193,7 +194,6 @@ export function contrastPacketFromLatestResult(
       user_meaning: probe.question,
       information_gain: probe.information_gain,
       expected_outcomes: probe.expected_outcomes,
-      candidate_ids: probe.candidate_ids,
       ...(probe.choice_kind === "varga_style"
         || probe.choice_kind === "event_quality"
         || probe.choice_kind === "existence"
@@ -212,7 +212,6 @@ export function contrastPacketFromLatestResult(
       user_meaning: probe.user_meaning,
       information_gain: probe.information_gain,
       expected_outcomes: probe.expected_outcomes,
-      candidate_ids: probe.candidate_ids,
       choice_kind: probe.choice_kind,
       style_options: probe.style_options,
     })),
@@ -273,7 +272,7 @@ export function rectificationFollowupCatalog(
     eventClarificationProbes: refinement.event_clarification_probes,
     evidenceCollectionProbes: refinement.evidence_collection_probes,
     precisionStage: refinement.precision_stage?.current ?? null,
-    nakshatraBoundary: refinement.nakshatra_boundary,
+    nakshatraProbe: inference?.probes.find((probe) => probe.source === "nakshatra_boundary") ?? null,
     oosBlindPrompts: refinement.oos_blind_prompts,
     holdoutEvents: (inference?.events ?? [])
       .filter((item) => item.usage === "holdout")
@@ -287,7 +286,7 @@ function contrastPacketFromState(state: InferenceState): CandidateContrastPacket
     candidateSetVersion: state.candidate_set_id,
     calculationResultId: null,
     engineProbes: state.probes
-      .filter((item) => !answered.has(item.id))
+      .filter((item) => !answered.has(item.id) && item.source !== "nakshatra_boundary")
       .map((item) => ({
         semantic_key: item.semantic_key,
         candidate_split_hash: item.candidate_split_hash,
@@ -442,6 +441,74 @@ function discriminatorProbeIfFollowupCanAsk(input: {
   return { probe: matched ?? input.inspected.selected, dropped };
 }
 
+function nakshatraContrastPacket(
+  probe: ConflictProbe,
+  candidateSetVersion: string,
+): CandidateContrastPacket {
+  return buildCandidateContrastPacket({
+    candidateSetVersion,
+    engineProbes: [{
+      semantic_key: probe.semantic_key,
+      candidate_split_hash: probe.candidate_split_hash,
+      domain: probe.domain,
+      year: probe.year > 0 ? probe.year : undefined,
+      user_meaning: probe.question,
+      information_gain: probe.information_gain,
+      expected_outcomes: probe.expected_outcomes,
+      choice_kind: probe.choice_kind,
+      style_options: probe.style_options,
+    }],
+  });
+}
+
+function nakshatraProbeIfFollowupCanAsk(input: {
+  dossier: DecisionDossier;
+  probe: ConflictProbe | null;
+  candidateSetVersion: string;
+  askedKeys: readonly string[];
+  topCandidateTimes: readonly string[];
+  holdoutValidation: HoldoutValidationStatus;
+  birthDate?: string | null;
+}): { probe: CandidateDiscriminatorProbe | null; dropped: DroppedProbe[] } {
+  if (!input.probe) return { probe: null, dropped: [] };
+  const packet = nakshatraContrastPacket(input.probe, input.candidateSetVersion);
+  const inspected = inspectDiscriminatorProbes(packet, {
+    askedKeys: input.askedKeys,
+    mentionedKeys: mentionedVargaKeysFromLedgerEvidence(input.dossier.evidence),
+    topCandidateTimes: input.topCandidateTimes,
+  });
+  if (!inspected.selected) return { probe: null, dropped: inspected.dropped };
+  const catalog = rectificationFollowupCatalog(input.dossier.latestResult, input.dossier.evidence);
+  const plan = buildMethodFollowupPlan({
+    evidence: input.dossier.evidence,
+    declinedTopics: input.dossier.conversationSummary.declinedSkippedTopics,
+    closedCollectFocuses: input.dossier.conversationSummary.declinedSkippedTopics,
+    sessionOutcome: "discriminate_candidates",
+    contrastPacket: { ...packet, probes: [] },
+    topCandidateTimes: input.topCandidateTimes,
+    askedProbeKeys: input.askedKeys,
+    eventProbes: [],
+    eventClarificationProbes: [],
+    evidenceCollectionProbes: [],
+    precisionStage: null,
+    nakshatraProbe: input.probe,
+    holdoutValidation: input.holdoutValidation,
+    oosBlindPrompts: catalog.oosBlindPrompts,
+    holdoutEvents: catalog.holdoutEvents,
+    ...(input.birthDate ? { birthDate: input.birthDate } : {}),
+    candidatesSeparated: false,
+  });
+  if (!followupAsksRenderableDiscriminator(plan.next_followup)) {
+    return { probe: null, dropped: mergeDroppedProbes(inspected.dropped, plan.dropped_probes) };
+  }
+  const key = plan.next_followup?.semantic_key;
+  const matched = key ? completedProbeForSemanticKey(key, packet, []) : null;
+  return {
+    probe: matched ?? inspected.selected,
+    dropped: mergeDroppedProbes(inspected.dropped, plan.dropped_probes),
+  };
+}
+
 function evidenceStopInputs(evidence: DecisionDossier["evidence"]): {
   datedEventCount: number;
   datedDomainCount: number;
@@ -511,6 +578,16 @@ export function decideFromDossier(
     askedKeys,
     birthDate: options?.birthDate,
   });
+  const holdoutValidation = holdoutStatusFromInference(inference, oosBlindPrompts);
+  const nakshatra = nakshatraProbeIfFollowupCanAsk({
+    dossier,
+    probe: inference?.probes.find((probe) => probe.source === "nakshatra_boundary") ?? null,
+    candidateSetVersion: inference?.candidate_set_id ?? "",
+    askedKeys,
+    topCandidateTimes,
+    holdoutValidation,
+    birthDate: options?.birthDate,
+  });
   return {
     ...decideRectification({
       methodCoverageAll: blockingMethodsCovered(collecting.methods),
@@ -520,7 +597,8 @@ export function decideFromDossier(
       snapshotCurrent,
       candidateScores: candidateScoresFromDossier(dossier.latestResult),
       discriminatorProbe: gated.probe,
-      holdoutValidation: holdoutStatusFromInference(inference, oosBlindPrompts),
+      nakshatraBoundaryProbe: nakshatra.probe,
+      holdoutValidation,
       accepted: Boolean(dossier.case.acceptedTime),
       inferenceCredibleRange: inference?.credible_range ?? null,
       engineCeiling: engineCapabilityCeilingFromReceipt(latest?.decisionReceipt ?? null),
@@ -529,7 +607,7 @@ export function decideFromDossier(
       ...evidenceStops,
       userUncertaintyHigh,
     }),
-    droppedProbes: gated.dropped,
+    droppedProbes: mergeDroppedProbes(gated.dropped, nakshatra.dropped),
   };
 }
 
@@ -570,11 +648,29 @@ export function decideAfterInferenceChange(input: {
     askedKeys: input.state.answered_probes.map((item) => item.semantic_key),
     topCandidateTimes,
   });
+  const askedKeys = input.state.answered_probes.flatMap((item) => [
+    item.probe_id,
+    item.semantic_key,
+    item.candidate_split_hash,
+  ]);
   const gated = discriminatorProbeIfFollowupCanAsk({
     dossier: input.dossier,
     inspected,
     contrastPacket,
-    askedKeys: input.state.answered_probes.map((item) => item.semantic_key),
+    askedKeys,
+    birthDate: input.birthDate,
+  });
+  const oosBlindPrompts = refinementFromDecisionReceipt(
+    input.dossier.latestResult?.decisionReceipt ?? null,
+  ).oos_blind_prompts;
+  const holdoutValidation = holdoutStatusFromState(input.state, oosBlindPrompts);
+  const nakshatra = nakshatraProbeIfFollowupCanAsk({
+    dossier: input.dossier,
+    probe: input.state.probes.find((probe) => probe.source === "nakshatra_boundary") ?? null,
+    candidateSetVersion: input.state.candidate_set_id,
+    askedKeys,
+    topCandidateTimes,
+    holdoutValidation,
     birthDate: input.birthDate,
   });
   return {
@@ -586,10 +682,8 @@ export function decideAfterInferenceChange(input: {
         .filter((item) => item.status !== "eliminated")
         .map((item) => ({ time: item.time, score: item.posterior_score })),
       discriminatorProbe: gated.probe,
-      holdoutValidation: holdoutStatusFromState(
-        input.state,
-        refinementFromDecisionReceipt(input.dossier.latestResult?.decisionReceipt ?? null).oos_blind_prompts,
-      ),
+      nakshatraBoundaryProbe: nakshatra.probe,
+      holdoutValidation,
       inferenceCredibleRange: input.state.credible_range,
       userStopped: input.userStopped,
       accepted: Boolean(input.dossier.case.acceptedTime),
@@ -599,7 +693,7 @@ export function decideAfterInferenceChange(input: {
       ...evidenceStops,
       userUncertaintyHigh,
     }),
-    droppedProbes: gated.dropped,
+    droppedProbes: mergeDroppedProbes(gated.dropped, nakshatra.dropped),
   };
 }
 

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

@@ -13,14 +13,20 @@ import { selectHighestGainProbe } from "../core/select-probe.ts";
 import { askedEventProbeKeysFromLedgerEvidence } from "../core/candidate-contrast-packet.ts";
 import { rankActive } from "../core/convergence-evaluator.ts";
 import { rangeFromTimes, unionStillValidRange } from "../core/credible-range.ts";
-import { previousInferenceFromReceipt } from "../core/compose-receipt.ts";
+import {
+  previousInferenceFromReceipt as parsePreviousInferenceFromReceipt,
+} from "../core/compose-receipt.ts";
 import type { AnswerClass, ConflictProbe, InferenceState, ProbeAnswer } from "../core/types.ts";
 import { datedPrecision } from "./evidence-model.ts";
 import {
   isHoldoutVerificationQuote,
   type ChoiceKey,
 } from "./choice-card.ts";
-import type { DiscriminatingEventProbe } from "./refinement-packet.ts";
+import {
+  parseNakshatraBoundary,
+  type DiscriminatingEventProbe,
+  type NakshatraBoundary,
+} from "./refinement-packet.ts";
 
 function yearFrom(value: string | null | undefined): number | null {
   if (!value || value.length < 4 || !/^\d{4}/.test(value)) return null;
@@ -68,7 +74,122 @@ export function askedDiscriminatorKeys(
   ];
 }
 
-export { previousInferenceFromReceipt };
+const NAKSHATRA_BOUNDARY_SOURCE = "nakshatra_boundary";
+
+export function nakshatraBoundaryProbe(
+  state: InferenceState | null | undefined,
+  boundary: NakshatraBoundary | null | undefined,
+): ConflictProbe | null {
+  if (!state || !boundary?.near_boundary) return null;
+  const optionA = boundary.options.find((item) => item.key === "A") ?? null;
+  const optionB = boundary.options.find((item) => item.key === "B") ?? null;
+  if (
+    !optionA?.traits.length
+    || !optionB?.traits.length
+    || optionA.time_bias === optionB.time_bias
+  ) return null;
+
+  const active = rankActive(state.candidates)
+    .slice()
+    .sort((left, right) => left.time.localeCompare(right.time));
+  if (active.length < 2) return null;
+  const pivot = Math.ceil(active.length / 2);
+  const earlier = active.slice(0, pivot).map((item) => item.id);
+  const later = active.slice(pivot).map((item) => item.id);
+  if (earlier.length === 0 || later.length === 0) return null;
+
+  const semanticKey = `nakshatra-boundary:${state.candidate_set_id}`;
+  const candidateSplitHash = `${semanticKey}:${earlier.join(",")}|${later.join(",")}`;
+  const candidatesFor = (bias: "earlier" | "later") => bias === "earlier" ? earlier : later;
+  const conflictsFor = (bias: "earlier" | "later") => bias === "earlier" ? later : earlier;
+  const optionLabel = (key: "A" | "B", traits: readonly string[]) => `${key} 组：${traits.join("、")}`;
+
+  return {
+    id: `probe:${semanticKey}`,
+    semantic_key: semanticKey,
+    candidate_split_hash: candidateSplitHash,
+    domain: "appearance",
+    year: 0,
+    question: boundary.user_meaning
+      ?? "升点靠近两段日常节奏的交界。平时做事时，哪一组更像你？这只用来偏置时间窗，不能确认唯一分钟。",
+    candidate_ids: active.map((item) => item.id),
+    expected_outcomes: [
+      {
+        answer_class: "yes",
+        supports: candidatesFor(optionA.time_bias),
+        conflicts: conflictsFor(optionA.time_bias),
+      },
+      {
+        answer_class: "weak_yes",
+        supports: candidatesFor(optionB.time_bias),
+        conflicts: conflictsFor(optionB.time_bias),
+      },
+      { answer_class: "no", supports: [], conflicts: [] },
+      { answer_class: "unsure", supports: [], conflicts: [] },
+    ],
+    information_gain: 0.01,
+    source: NAKSHATRA_BOUNDARY_SOURCE,
+    choice_kind: "varga_style",
+    style_options: [
+      {
+        label: optionLabel("A", optionA.traits),
+        answer_class: "yes",
+        sign: optionA.time_bias === "earlier" ? "较早时间窗" : "较晚时间窗",
+      },
+      {
+        label: optionLabel("B", optionB.traits),
+        answer_class: "weak_yes",
+        sign: optionB.time_bias === "earlier" ? "较早时间窗" : "较晚时间窗",
+      },
+      { label: "两组都不太像我", answer_class: "no" },
+      { label: "一时说不好", answer_class: "unsure" },
+    ],
+  };
+}
+
+export function withNakshatraBoundaryProbe(
+  state: InferenceState | null,
+  boundary: NakshatraBoundary | null | undefined,
+): InferenceState | null {
+  if (!state) return null;
+  const probe = nakshatraBoundaryProbe(state, boundary);
+  const existingIndexes = state.probes.flatMap((item, index) => (
+    item.source === NAKSHATRA_BOUNDARY_SOURCE ? [index] : []
+  ));
+  if (!probe || isDuplicateProbe(probe, state.answered_probes)) {
+    if (existingIndexes.length === 0) return state;
+    return {
+      ...state,
+      probes: state.probes.filter((item) => item.source !== NAKSHATRA_BOUNDARY_SOURCE),
+    };
+  }
+  const existing = existingIndexes.length > 0 ? state.probes[existingIndexes[0]!] : null;
+  if (
+    existingIndexes.length === 1
+    && existing?.id === probe.id
+    && existing.semantic_key === probe.semantic_key
+    && existing.candidate_split_hash === probe.candidate_split_hash
+  ) return state;
+  const probes = state.probes.filter((item) => item.source !== NAKSHATRA_BOUNDARY_SOURCE);
+  const insertAt = existingIndexes[0] ?? probes.length;
+  return {
+    ...state,
+    probes: [
+      ...probes.slice(0, insertAt),
+      probe,
+      ...probes.slice(insertAt),
+    ],
+  };
+}
+
+export function previousInferenceFromReceipt(
+  receipt: Readonly<Record<string, unknown>> | null | undefined,
+): InferenceState | null {
+  return withNakshatraBoundaryProbe(
+    parsePreviousInferenceFromReceipt(receipt),
+    parseNakshatraBoundary(receipt?.nakshatra_boundary),
+  );
+}
 
 type CandidateSnapshotRow = Readonly<{
   candidateId?: string;

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

@@ -68,6 +68,7 @@ import {
   parseAgentChoiceCopy,
   preferConcreteChoicePrompt,
   mergeChoiceCard,
+  serverOwnedChoiceCopy,
   type RectificationChoiceCard,
   type RectificationChoiceFrame,
 } from "./choice-card.ts";
@@ -77,6 +78,7 @@ import {
   decideRectification,
   type HoldoutValidationStatus,
 } from "../core/rectification-decision.ts";
+import type { ConflictProbe } from "../core/types.ts";
 import {
   datedDomainsFromEvidence,
   isStructuredDiscriminator,
@@ -104,7 +106,6 @@ import type {
   DiscriminatingEventProbe,
   EventProbeDomain,
   EventProbeStyleOption,
-  NakshatraBoundary,
   OosBlindPrompt,
   PrecisionStageId,
 } from "./refinement-packet";
@@ -947,7 +948,7 @@ export const GENERIC_COLLECT_QUESTION = "请先说一件你记得大概时间的
 
 export function spokenFollowupForUser(followup: MethodFollowup | null): string | null {
   if (!followup) return null;
-  if (followup.choice_frame) return "接下来请点选下面这一问。";
+  if (followup.choice_frame) return serverOwnedChoiceCopy(followup.choice_frame)?.prompt ?? null;
   if (followup.intent !== "collect_method_evidence") return null;
   const base = USER_COLLECT_QUESTION[followup.domain ?? ""]
     ?? GENERIC_COLLECT_QUESTION;
@@ -1307,7 +1308,7 @@ export function buildMethodFollowupPlan(input: {
   observations?: readonly InternalVargaObservation[];
   sessionOutcome?: SessionOutcomeKind;
   precisionStage?: PrecisionStageId | null;
-  nakshatraBoundary?: NakshatraBoundary | null;
+  nakshatraProbe?: ConflictProbe | null;
   oosBlindPrompts?: readonly OosBlindPrompt[];
   eventProbes?: readonly DiscriminatingEventProbe[];
   eventClarificationProbes?: readonly DiscriminatingEventProbe[];
@@ -1614,7 +1615,25 @@ export function buildMethodFollowupPlan(input: {
       probe_id: contrast.probeId,
     }, true, true);
   };
-  if (!dashaCovered) {
+  if (dashaCovered) {
+    const allowLowGainDiscriminator = !coverageComplete || !candidatesSeparated;
+    for (const ranked of rankedDiscriminators) {
+      if (!allowLowGainDiscriminator && ranked.score < 0.08) continue;
+      const candidate = followupFromRanked(ranked);
+      if (candidate.choice_frame) {
+        next = candidate;
+        break;
+      }
+    }
+  }
+  if (!next && input.holdoutValidation === "not_started") {
+    const fields = holdoutAskFields(
+      input.oosBlindPrompts?.[0],
+      (input.holdoutEvents ?? []).find((item) => item.year !== null) ?? null,
+    );
+    if (fields) next = makeFollowup(fields, false);
+  }
+  if (!next && !dashaCovered) {
     next = makeFollowup({
       method_id: "dasha_events",
       intent: "collect_method_evidence",
@@ -1628,37 +1647,54 @@ export function buildMethodFollowupPlan(input: {
       ),
       source: "method_coverage",
     });
-  } else {
+  }
+  if (!next && dashaCovered && coverageComplete) {
     const allowLowGainDiscriminator = !coverageComplete || !candidatesSeparated;
-    for (const ranked of rankedDiscriminators) {
-      if (!allowLowGainDiscriminator && ranked.score < 0.08) continue;
-      const candidate = followupFromRanked(ranked);
-      if (candidate.choice_frame) {
-        next = candidate;
-        break;
-      }
-    }
-    if (!next && coverageComplete) {
-      const yearless = yearlessDiscriminators[0];
-      if (yearless && (allowLowGainDiscriminator || yearless.score >= 0.08)) {
-        const domain = contrastFollowupDomain(
-          yearless.eventProbe?.domain ?? yearless.contrastProbe?.domain ?? null,
-        );
-        const lead = YEARLESS_COLLECT_LEAD[domain];
-        if (lead && !declined.has(domain)) {
-          next = makeFollowup({
-            method_id: PROBE_METHOD_ID[domain],
-            intent: "collect_method_evidence",
-            ask_theme: REVERSE_VERIFY_THEME[domain],
-            domain,
-            kind_hint: REVERSE_VERIFY_KIND[domain],
-            user_prompt_hint: collect(lead, REVERSE_VERIFY_VARGA[domain]),
-            source: "method_coverage",
-          });
-        }
+    const yearless = yearlessDiscriminators[0];
+    if (yearless && (allowLowGainDiscriminator || yearless.score >= 0.08)) {
+      const domain = contrastFollowupDomain(
+        yearless.eventProbe?.domain ?? yearless.contrastProbe?.domain ?? null,
+      );
+      const lead = YEARLESS_COLLECT_LEAD[domain];
+      if (lead && !declined.has(domain)) {
+        next = makeFollowup({
+          method_id: PROBE_METHOD_ID[domain],
+          intent: "collect_method_evidence",
+          ask_theme: REVERSE_VERIFY_THEME[domain],
+          domain,
+          kind_hint: REVERSE_VERIFY_KIND[domain],
+          user_prompt_hint: collect(lead, REVERSE_VERIFY_VARGA[domain]),
+          source: "method_coverage",
+        });
       }
     }
   }
+  if (
+    !next
+    && input.holdoutValidation !== "not_started"
+    && !datedMethodCollectOpen(methods)
+    && input.nakshatraProbe
+  ) {
+    const probe = input.nakshatraProbe;
+    next = makeFollowup({
+      method_id: "nakshatra_boundary",
+      intent: "distinguish_candidates",
+      ask_theme: "nakshatra_trait",
+      domain: probe.domain,
+      kind_hint: null,
+      user_prompt_hint: probe.question,
+      source: "nakshatra_boundary",
+      information_gain: probe.information_gain,
+      semantic_key: probe.semantic_key,
+      candidate_split_hash: probe.candidate_split_hash,
+      probe_year: probe.year,
+      choice_kind: probe.choice_kind ?? "varga_style",
+      candidate_ids: probe.candidate_ids,
+      expected_outcomes: probe.expected_outcomes,
+      style_options: probe.style_options,
+      probe_id: probe.id,
+    }, true, true);
+  }
   const sameDomainYearlessCard = (domain: string): MethodFollowup | null => {
     const ranked = yearlessDiscriminators.find((row) => (
       (row.eventProbe?.domain ?? row.contrastProbe?.domain ?? null) === domain
@@ -1934,23 +1970,6 @@ export function buildMethodFollowupPlan(input: {
         ),
         source: "varga_observation",
       });
-    } else if (input.nakshatraBoundary?.near_boundary) {
-      next = makeFollowup({
-        method_id: "nakshatra_boundary",
-        intent: "distinguish_candidates",
-        ask_theme: "nakshatra_trait",
-        domain: null,
-        kind_hint: null,
-        user_prompt_hint: input.nakshatraBoundary.user_meaning
-          ?? "升点靠近两段日常节奏的交界。哪一组更像你近年的处事方式？这只用来偏置时间窗，不能确认唯一分钟。",
-        source: "nakshatra_boundary",
-      });
-    } else if (input.holdoutValidation === "not_started") {
-      const fields = holdoutAskFields(
-        input.oosBlindPrompts?.[0],
-        (input.holdoutEvents ?? []).find((item) => item.year !== null) ?? null,
-      );
-      if (fields) next = makeFollowup(fields, false);
     } else if (horaryStatus === "uncovered") {
       next = sameDomainYearlessCard("horary") ?? makeFollowup({
         method_id: "horary",

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

@@ -8,8 +8,10 @@ import {
   askedProbeKeysFromReceipt,
   stampChoiceSchemaWithProbe,
   previousInferenceFromReceipt,
+  withNakshatraBoundaryProbe,
 } from "./inference-adapter";
 import { spokenFollowupForUser, type MethodFollowup } from "./method-followup";
+import { refinementFromDecisionReceipt } from "./refinement-packet";
 import {
   setV10ConversationFocus,
   RectificationToolServiceError,
@@ -90,7 +92,11 @@ function expectedAnswerSchemaFor(
     candidate_split_hash: followup.candidate_split_hash ?? null,
     choice_kind: frame.choice_kind ?? followup.choice_kind ?? "existence",
   };
-  const state = previousInferenceFromReceipt(decisionReceipt ?? null);
+  const receipt = decisionReceipt ?? null;
+  const state = withNakshatraBoundaryProbe(
+    previousInferenceFromReceipt(receipt),
+    refinementFromDecisionReceipt(receipt).nakshatra_boundary,
+  );
   if (decisionReceipt?.inference_state !== undefined && !state) return null;
   const stamped = stampChoiceSchemaWithProbe(
     schema,

frontend/src/lib/rectification-agentic/v9/turn-exit.ts

@@ -0,0 +1,79 @@
+import {
+  ensureNonTerminalTurnExit,
+  persistNextInterviewIfIdle,
+} from "./answer-choice.ts";
+import { projectCurrentQuestion } from "./turn-decision.ts";
+import {
+  loadV9CaseDossier,
+  persistV9DeterministicTurn,
+  type RectificationRpcClient,
+} from "./tool-service.ts";
+
+export type RectificationRouteAction =
+  | "opening"
+  | "message"
+  | "read_only"
+  | "answer_choice"
+  | "stop_and_review";
+
+export const RECTIFICATION_ACTION_EXECUTION = {
+  opening: "stream",
+  message: "hybrid",
+  read_only: "read_only",
+  answer_choice: "immediate",
+  stop_and_review: "immediate",
+} as const satisfies Record<RectificationRouteAction, "stream" | "hybrid" | "read_only" | "immediate">;
+
+export async function finalizeSuccessfulTurnExit(input: {
+  accounting: RectificationRpcClient;
+  userId: string;
+  caseId: string;
+  action: RectificationRouteAction;
+}): Promise<void> {
+  if (input.action === "read_only") {
+    // Read-only requests must never mutate the interview or create a focus.
+    return;
+  }
+  let focusCreated = false;
+  try {
+    const next = await persistNextInterviewIfIdle(input);
+    focusCreated = next.persisted;
+  } catch (error) {
+    console.warn(
+      `[rectification-v9] persist next interview after turn failed case=${input.caseId} reason=${error instanceof Error ? error.name : "Unknown"}`,
+    );
+  }
+  try {
+    const repaired = await ensureNonTerminalTurnExit(input);
+    focusCreated ||= repaired.persisted;
+  } catch (error) {
+    console.warn(
+      `[rectification-v9] nonterminal turn exit repair failed case=${input.caseId} reason=${error instanceof Error ? error.name : "Unknown"}`,
+    );
+    throw error;
+  }
+  if (!focusCreated) return;
+  try {
+    const dossier = await loadV9CaseDossier(input.accounting, input.userId, input.caseId);
+    const question = projectCurrentQuestion(dossier.conversationSummary.activeFocus);
+    if (question?.focus_id && question.prompt) {
+      await persistV9DeterministicTurn(input.accounting, input.userId, input.caseId, {
+        requestId: question.focus_id,
+        userMessage: null,
+        assistantMessage: question.prompt,
+      });
+    }
+  } catch (error) {
+    console.warn(
+      `[rectification-v9] persist server question turn failed case=${input.caseId} reason=${error instanceof Error ? error.name : "Unknown"}`,
+    );
+  }
+}
+
+export async function awaitTurnExitBeforeResponse<T>(
+  response: T,
+  finalize: () => Promise<void>,
+): Promise<T> {
+  await finalize();
+  return response;
+}