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
-    .map((entry, index) => {
-      const descriptor = getPromptMessageLikeDescriptor(entry);
-      if (!descriptor) {
-        return "";
-      }
-      const seqLabel =
-        descriptor.seq != null ? `#${descriptor.seq}` : `#${index + 1}`;
-      const speakerLabel = descriptor.speaker
-        ? `|${descriptor.speaker}`
-        : "";
-      return `${seqLabel} [${descriptor.role}${speakerLabel}]: ${descriptor.content}`;
-    })
-    .filter(Boolean)
-    .join("\n\n");
+  const hasContextMessages = entries.some(
+    (entry) => getPromptMessageContextGroup(entry) === "context",
+  );
+  const hasTargetMessages = entries.some(
+    (entry) => getPromptMessageContextGroup(entry) === "target",
+  );
+  const lines = [];
+  let activeGroup = null;
+
+  for (let index = 0; index < entries.length; index += 1) {
+    const entry = entries[index];
+    const descriptor = getPromptMessageLikeDescriptor(entry);
+    if (!descriptor) {
+      continue;
+    }
+    const group = getPromptMessageContextGroup(entry);
+    if (hasContextMessages && hasTargetMessages && group && group !== activeGroup) {
+      lines.push(
+        group === "context"
+          ? "--- 以下是上下文回顾（已提取过），仅供理解剧情 ---"
+          : "--- 以下是本次需要提取记忆的新对话内容 ---",
+      );
+      activeGroup = group;
+    }
+    const seqLabel =
+      descriptor.seq != null ? `#${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) {