fix: preserve isContextOnly context/target dividers in final prompt transcript rendering

Root cause: formatPromptMessageTranscript in prompt-builder.js ignored
isContextOnly, so context review and extraction target sections were
flattened into plain transcript even though the flag was correctly set
in intermediate layers. Additionally, userPromptSections (which
contained the dividers) was only a fallback that never reached the
final prompt when block-based profiles had user blocks.

Fix:
- getPromptMessageLikeDescriptor now preserves isContextOnly flag
- formatPromptMessageTranscript now inserts context/target section
  dividers when messages carry isContextOnly, ensuring the final
  LLM prompt always shows the distinction regardless of which
  rendering path (recentMessages, chatMessages, dialogueText) is used

Regression tests:
- prompt-builder-mixed-transcript: verify recentMessages block content
  includes context review and extraction target dividers
- extractor-phase3-layered-context: end-to-end test proving default
  extract profile + default structured mode produces final promptMessages
  with context/target section dividers

prompting/prompt-builder.js

@@ -296,6 +296,8 @@ function getPromptMessageLikeDescriptor(value) {
       role: role === "user" ? "user" : "assistant",
       seq: getOptionalFiniteNumber(value.seq),
       speaker,
+      isContextOnly:
+        typeof value.isContextOnly === "boolean" ? value.isContextOnly : null,
     };
   }
 
@@ -308,6 +310,8 @@ function getPromptMessageLikeDescriptor(value) {
       role: value.is_user === true ? "user" : "assistant",
       seq: getOptionalFiniteNumber(value.seq),
       speaker,
+      isContextOnly:
+        typeof value.isContextOnly === "boolean" ? value.isContextOnly : null,
     };
   }
 
@@ -322,23 +326,49 @@ function isPromptMessageArray(value) {
   );
 }
 
+function getPromptMessageContextGroup(value) {
+  const descriptor = getPromptMessageLikeDescriptor(value);
+  if (!descriptor || typeof descriptor.isContextOnly !== "boolean") {
+    return null;
+  }
+  return descriptor.isContextOnly ? "context" : "target";
+}
+
 function formatPromptMessageTranscript(value) {
   const entries = Array.isArray(value) ? value : [value];
-  return entries
+  const hasContextMessages = entries.some(
-    .map((entry, index) => {
+    (entry) => getPromptMessageContextGroup(entry) === "context",
-      const descriptor = getPromptMessageLikeDescriptor(entry);
+  );
-      if (!descriptor) {
+  const hasTargetMessages = entries.some(
-        return "";
+    (entry) => getPromptMessageContextGroup(entry) === "target",
-      }
+  );
-      const seqLabel =
+  const lines = [];
-        descriptor.seq != null ? `#${descriptor.seq}` : `#${index + 1}`;
+  let activeGroup = null;
-      const speakerLabel = descriptor.speaker
+
-        ? `|${descriptor.speaker}`
+  for (let index = 0; index < entries.length; index += 1) {
-        : "";
+    const entry = entries[index];
-      return `${seqLabel} [${descriptor.role}${speakerLabel}]: ${descriptor.content}`;
+    const descriptor = getPromptMessageLikeDescriptor(entry);
-    })
+    if (!descriptor) {
-    .filter(Boolean)
+      continue;
-    .join("\n\n");
+    }
+    const group = getPromptMessageContextGroup(entry);
+    if (hasContextMessages && hasTargetMessages && group && group !== activeGroup) {
+      lines.push(
+        group === "context"
+          ? "--- 以下是上下文回顾（已提取过），仅供理解剧情 ---"
+          : "--- 以下是本次需要提取记忆的新对话内容 ---",
+      );
+      activeGroup = group;
+    }
+    const seqLabel =
+      descriptor.seq != null ? `#${descriptor.seq}` : `#${index + 1}`;
+    const speakerLabel = descriptor.speaker
+      ? `|${descriptor.speaker}`
+      : "";
+    lines.push(`${seqLabel} [${descriptor.role}${speakerLabel}]: ${descriptor.content}`);
+  }
+
+  return lines.filter(Boolean).join("\n\n");
 }
 
 function stringifyInterpolatedValue(value) {

tests/extractor-phase3-layered-context.mjs

@@ -165,6 +165,81 @@ function collectAllPromptContent(captured) {
   }
 }
 
+{
+  const graph = createEmptyGraph();
+  let captured = null;
+  const restore = setTestOverrides({
+    llm: {
+      async callLLMForJSON(payload) {
+        captured = payload;
+        return { operations: [], cognitionUpdates: [], regionUpdates: {} };
+      },
+    },
+  });
+
+  try {
+    const result = await extractMemories({
+      graph,
+      messages: [
+        {
+          seq: 10,
+          role: "user",
+          content: "第一轮消息",
+          name: "玩家",
+          speaker: "玩家",
+          isContextOnly: true,
+        },
+        {
+          seq: 11,
+          role: "assistant",
+          content: "第一轮回复",
+          name: "艾琳",
+          speaker: "艾琳",
+          isContextOnly: true,
+        },
+        {
+          seq: 12,
+          role: "user",
+          content: "第二轮消息",
+          name: "玩家",
+          speaker: "玩家",
+          isContextOnly: false,
+        },
+        {
+          seq: 13,
+          role: "assistant",
+          content: "第二轮回复",
+          name: "艾琳",
+          speaker: "艾琳",
+          isContextOnly: false,
+        },
+      ],
+      startSeq: 12,
+      endSeq: 13,
+      schema: DEFAULT_NODE_SCHEMA,
+      embeddingConfig: null,
+      settings: { ...defaultSettings },
+    });
+
+    assert.equal(result.success, true);
+    assert.ok(captured);
+
+    const recentBlock = (Array.isArray(captured.promptMessages) ? captured.promptMessages : []).find(
+      (m) => m.sourceKey === "recentMessages",
+    );
+    assert.ok(recentBlock, "recentMessages block should exist");
+    const recentContent = String(recentBlock?.content || "");
+    assert.match(recentContent, /以下是上下文回顾（已提取过），仅供理解剧情/);
+    assert.match(recentContent, /以下是本次需要提取记忆的新对话内容/);
+    assert.ok(
+      recentContent.indexOf("已提取过") < recentContent.indexOf("本次需要提取"),
+      "context review should appear before extraction target section",
+    );
+  } finally {
+    restore();
+  }
+}
+
 // ── Test 2: extractRecentMessageCap limits messages ──
 {
   const graph = createEmptyGraph();

tests/prompt-builder-mixed-transcript.mjs

@@ -117,6 +117,7 @@ const promptBuild = await buildTaskPrompt(settings, "extract", {
       content: "继续说明",
       name: "艾琳",
       speaker: "艾琳",
+      isContextOnly: true,
     },
     {
       seq: 42,
@@ -124,6 +125,7 @@ const promptBuild = await buildTaskPrompt(settings, "extract", {
       content: "用户输入",
       name: "玩家",
       speaker: "玩家",
+      isContextOnly: false,
     },
   ],
   graphStats: "node_count=1",
@@ -134,6 +136,14 @@ const payload = buildTaskLlmPayload(promptBuild, "fallback-user");
 const recentBlock = payload.promptMessages.find(
   (message) => message.sourceKey === "recentMessages",
 );
+assert.match(
+  String(recentBlock?.content || ""),
+  /以下是上下文回顾（已提取过），仅供理解剧情/,
+);
+assert.match(
+  String(recentBlock?.content || ""),
+  /以下是本次需要提取记忆的新对话内容/,
+);
 assert.match(String(recentBlock?.content || ""), /#41 \[assistant\|艾琳\]: 助手已净化/);
 assert.match(String(recentBlock?.content || ""), /#42 \[user\|玩家\]: 用户已净化/);
 assert.doesNotMatch(