refactor: tighten master-agent memory ingestion

src/lib/boss-data.ts

@@ -3942,6 +3942,23 @@ function normalizeAutoMemoryText(value: string | undefined) {
     .trim();
 }
 
+function isLowValueAutoMemoryText(text: string) {
+  const normalized = normalizeAutoMemoryText(text);
+  if (!normalized) {
+    return true;
+  }
+  if (normalized.length < 10) {
+    return true;
+  }
+  if (/^(好的|收到|明白|继续|先这样|可以|行|没问题|辛苦了|谢谢|了解|嗯嗯)$/i.test(normalized)) {
+    return true;
+  }
+  if (/(马上|稍后|回头|等下|一会|临时|先看下|先试试|先这样)/i.test(normalized)) {
+    return true;
+  }
+  return false;
+}
+
 function inferAutoMemoryType(text: string): MasterMemoryType | null {
   if (!text.trim()) return null;
   if (/(微信|wechat|中文回复|中文沟通|UI风格|交互风格|偏好|习惯|默认)/i.test(text)) {
@@ -4120,15 +4137,20 @@ function autoCaptureMasterAgentMemoriesInState(
 
   const createdOrUpdated: MasterAgentMemory[] = [];
   const combined = [requestText, replyText].filter(Boolean).join(" ");
-  const preferenceType = inferAutoMemoryType(requestText);
+  const preferenceCandidate = isLowValueAutoMemoryText(requestText) ? "" : requestText;
+  const projectCandidate = isLowValueAutoMemoryText(replyText) ? combined : replyText || combined;
+  const preferenceType = inferAutoMemoryType(preferenceCandidate);
 
-  if (preferenceType === "user_preference" || preferenceType === "workflow_rule") {
+  if (
+    preferenceCandidate &&
+    (preferenceType === "user_preference" || preferenceType === "workflow_rule")
+  ) {
     createdOrUpdated.push(
       upsertAutoMasterMemoryInState(state, {
         account: input.account,
         scope: "global",
         title: buildAutoMemoryTitle(preferenceType),
-        content: requestText,
+        content: preferenceCandidate,
         memoryType: preferenceType,
         tags: preferenceType === "user_preference" ? ["用户偏好"] : ["工作方式"],
         sourceMessageId: input.sourceMessageId,
@@ -4137,15 +4159,15 @@ function autoCaptureMasterAgentMemoriesInState(
   }
 
   const referencedProject = detectReferencedProjectForMemory(state, combined);
-  const projectType = inferProjectAutoMemoryType(replyText) ?? inferProjectAutoMemoryType(combined);
-  if (referencedProject && projectType) {
+  const projectType = inferProjectAutoMemoryType(projectCandidate) ?? inferProjectAutoMemoryType(combined);
+  if (referencedProject && projectType && !isLowValueAutoMemoryText(projectCandidate)) {
     createdOrUpdated.push(
       upsertAutoMasterMemoryInState(state, {
         account: input.account,
         scope: "project",
         projectId: referencedProject.projectId,
         title: buildAutoMemoryTitle(projectType, referencedProject.projectName),
-        content: replyText || requestText,
+        content: projectCandidate,
         memoryType: projectType,
         tags: [referencedProject.projectName, referencedProject.alias],
         sourceMessageId: input.sourceMessageId,

tests/master-agent-memory-ingestion.test.ts

@@ -57,3 +57,31 @@ test("主 Agent 完成对话后会自动沉淀用户偏好和项目记忆", asyn
   assert.match(globalMemory?.content ?? "", /微信式交互|中文回复/);
   assert.match(projectMemory?.content ?? "", /boss 项目当前进度已更新/);
 });
+
+test("主 Agent 不会把低价值短句和瞬时安排自动写入记忆", async () => {
+  await setup();
+
+  const task = await queueMasterAgentTask({
+    projectId: "master-agent",
+    requestMessageId: "msg-user-2",
+    requestText: "好的，先这样，稍后我再看。",
+    executionPrompt: "prompt",
+    requestedBy: "17600003315",
+    requestedByAccount: "17600003315",
+    deviceId: "master-agent-openai",
+  });
+
+  await completeMasterAgentTask({
+    taskId: task.taskId,
+    deviceId: "master-agent-openai",
+    status: "completed",
+    replyBody: "好的，稍后继续。",
+  });
+
+  const memories = await listUserMasterMemories("17600003315", { includeArchived: false });
+  const noisyMemory = memories.find(
+    (memory) => (memory.content ?? "").includes("先这样") || (memory.content ?? "").includes("稍后继续"),
+  );
+
+  assert.equal(noisyMemory, undefined);
+});