feat(agent): align investigation reports and selected context

src/routes/chatStreamRoute.ts

@@ -90,6 +90,11 @@ const payloadSchema = z.object({
   approval_mode: z.enum(["request", "always"]).optional().default("request"),
   capabilities: z.array(z.string().max(64)).max(20).optional().default([]),
   trigger_context: agentTriggerContextSchema.optional(),
+  task_context: z.object({
+    report_revision: z.number().int().positive().optional(),
+    evidence_id: z.string().min(1).max(128).optional(),
+    gap_id: z.string().min(1).max(128).optional(),
+  }).strict().optional(),
 });
 
 const toSessionUiStateContext = (sessionRecord: SessionRecord) => ({
@@ -147,7 +152,8 @@ export const toCollaborationMessages = (messages: UIMessage[]) =>
   messages.flatMap((message) => {
     if (message.role !== "user" && message.role !== "assistant") return [];
     const content = readUiMessageText(message);
-    return content ? [{ ...message, parts: [{ type: "text" as const, text: content }] } as UIMessage] : [];
+    const reference = message.parts.filter((part) => part.type === "data-task_context");
+    return content ? [{ ...message, parts: [{ type: "text" as const, text: content }, ...reference] } as UIMessage] : [];
   });
 
 const toLegacyMessages = (messages: UIMessage[]) =>
@@ -384,11 +390,18 @@ export const registerChatStreamRoute = (
       boundOperationalSessionId = binding.sessionId;
       const resolvedTaskContext = activeSessionRecord.taskId
         && (sessionPurpose === "task_collaboration" || sessionPurpose === "task_execution")
-        ? await operationalTaskClient.getAgentContext(binding.sessionId, activeSessionRecord.taskId)
+        ? await operationalTaskClient.getAgentContext(binding.sessionId, activeSessionRecord.taskId,
+          sessionPurpose === "task_collaboration" ? parsed.data.task_context?.report_revision : undefined)
         : null;
       const taskContext = sessionPurpose === "task_collaboration"
         ? resolvedTaskContext
         : null;
+      if (taskContext) {
+        const report = taskContext.selected_report ?? taskContext.task.latest_report;
+        const reference = z.object({ revision: z.number().int().positive() }).passthrough().safeParse(report);
+        setRuntimeSessionContext({ ...getRuntimeSessionContext(binding.sessionId)!,
+          reportRevision: reference.success ? reference.data.revision : undefined });
+      }
       const hasRuntimeConversation = hadExistingRuntimeSession
         ? await runtimeHasConversation(runtime, binding.sessionId)
         : false;
@@ -882,10 +895,26 @@ export const registerChatStreamRoute = (
       taskHeartbeat?.unref();
 
       try {
+        if (taskContext) {
+          const raw = taskContext.selected_report ?? taskContext.task.latest_report;
+          const reportRef = z.object({ revision: z.number().int().positive(), execution_generation: z.number().int().positive().nullish() }).passthrough().safeParse(raw);
+          const generation = taskContext.task.execution_generation;
+          const reference = {
+            task_id: activeSessionRecord.taskId!,
+            execution_generation: reportRef.success ? reportRef.data.execution_generation ?? null
+              : typeof generation === "number" && generation > 0 ? generation : null,
+            report_revision: reportRef.success ? reportRef.data.revision : null,
+          };
+          const part = { type: "data-task_context" as const, data: reference };
+          assistantParts.push(part);
+          writeUiChunk(part);
+          syncLatestUiMessages();
+        }
         const preparedMessage = taskContext
           ? [
-              "你正在与用户协作理解一个工况任务。只根据下面由后端授权返回的任务、计划、报告和证据快照解释判断；不要展示后台执行会话、工具轨迹或内部推理。若资料不足，明确说明缺口。用户要求变更任务时使用结构化工具写回。",
+              "你正在与用户协作理解一个工况任务。只根据下面由后端授权返回的任务、报告和证据解释判断；selected_report 存在时用户正在阅读该轮次与修订号，优先据此回答并明确引用。不要展示后台执行会话、工具轨迹或内部推理。普通提问不改变任务，只有用户明确补充的事实可用结构化工具记录并重新分析；假设和查询要求不能当作现场事实。queued 表示等待领取，不能声称已经开始分析。",
               `任务快照：${JSON.stringify(taskContext)}`,
+              `当前讨论对象：${JSON.stringify(parsed.data.task_context ?? {})}`,
               `用户问题：${promptText}`,
             ].join("\n\n")
           : await buildPromptWithLearningContext(