fix: Unable to create scheduled tasks

backend/services/agent_automation/intent_analyzer.py

@@ -273,6 +273,7 @@ async def analyze(self, context: AutomationIntentContext) -> Dict[str, Any]:
 
     def _generate_sync(self, context: AutomationIntentContext) -> str:
         from nexent.core.models import OpenAIModel
+        from nexent.core.utils.observer import MessageObserver
         from utils.config_utils import get_model_name_from_config
 
         language = detect_instruction_language(context.message)
@@ -289,6 +290,7 @@ def _generate_sync(self, context: AutomationIntentContext) -> str:
             undefined=StrictUndefined,
         ).render(**values).strip()
         llm = OpenAIModel(
+            observer=MessageObserver(),
             model_id=get_model_name_from_config(self._model_config),
             api_base=self._model_config.get("base_url", ""),
             api_key=self._model_config.get("api_key", ""),

backend/services/agent_automation/prompt_generator.py

@@ -227,12 +227,14 @@ def _generate_sync(
         user_key: str,
     ) -> str:
         from nexent.core.models import OpenAIModel
+        from nexent.core.utils.observer import MessageObserver
         from utils.config_utils import get_model_name_from_config
 
         prompt_template = get_prompt_template("agent_automation", context.language)
         values = {"instruction": context.instruction.strip()}
         user_prompt = Template(prompt_template[user_key], undefined=StrictUndefined).render(**values).strip()
         llm = OpenAIModel(
+            observer=MessageObserver(),
             model_id=get_model_name_from_config(self._model_config) if self._model_config.get("model_name") else "",
             api_base=self._model_config.get("base_url", ""),
             api_key=self._model_config.get("api_key", ""),

backend/services/agent_automation/tool_adapter.py

@@ -34,6 +34,16 @@
 DEFAULT_AUTOMATION_TIMEZONE = "Asia/Shanghai"
 
 
+def _strip_runtime_time_prefix(message: str) -> str:
+    """Remove the runtime-only current-time header from the user request."""
+    normalized = str(message or "")
+    if normalized.startswith("[Current time:"):
+        close_index = normalized.find("]", len("[Current time:"))
+        if close_index >= 0:
+            return normalized[close_index + 1:].lstrip("\n").strip()
+    return normalized
+
+
 def _run_coroutine(coro):
     try:
         asyncio.get_running_loop()
@@ -130,7 +140,8 @@ async def create_proposal(
         # The model argument is intentionally not forwarded to extraction. The
         # persisted current user message is the authoritative business input.
         del request_text
-        language = detect_instruction_language(context.user_message)
+        user_message = _strip_runtime_time_prefix(context.user_message)
+        language = detect_instruction_language(user_message)
         if context.source_message_id is None:
             message = (
                 "本轮消息尚未完成持久化，无法安全创建定时任务提案。请稍后重试。"
@@ -160,7 +171,7 @@ async def create_proposal(
         request = AutomationProposalCreateRequest(
             conversation_id=context.conversation_id,
             agent_id=context.agent_id,
-            message=context.user_message,
+            message=user_message,
             timezone=context.timezone or DEFAULT_AUTOMATION_TIMEZONE,
             agent_version_no=context.agent_version_no,
             model_id=context.model_id,

sdk/nexent/core/agents/core_agent.py

@@ -215,6 +215,9 @@ class InvalidActionFormatError(AgentExecutionError):
     r"|(?:我(?:将|需要|先)|接下来|下一步|i\s+(?:will|need\s+to|should)\b|next\b).{0,240})"
     r"(?:调用|使用|检索|搜索|call|use|search|invoke)"
 )
+_EXPLICIT_FINAL_ANSWER_RE = re.compile(
+    r"(?is)(?:^|\n)\s*(?:最终回答|final\s+answer)\s*[:：]\s*\S"
+)
 
 
 def _looks_like_invalid_action_output(text: Any) -> bool:
@@ -263,6 +266,8 @@ def _looks_like_incomplete_action_output(
         return True
     if _looks_like_invalid_action_output(text):
         return True
+    if _EXPLICIT_FINAL_ANSWER_RE.search(text):
+        return False
 
     normalized = text.casefold()
     mentioned_tool = any(

test/backend/services/test_agent_automation_intent_analyzer.py

@@ -220,6 +220,8 @@ def test_llm_analyzer_generate_sync_invokes_model_as_callable(monkeypatch):
         "schedule_error": None,
     }, ensure_ascii=False)
 
+    captured = {}
+
     class FakeModel:
         def __init__(self):
             self.calls = None
@@ -229,7 +231,12 @@ def __call__(self, messages):
             return SimpleNamespace(content=fake_payload)
 
     fake_model = FakeModel()
-    monkeypatch.setattr("nexent.core.models.OpenAIModel", lambda **kwargs: fake_model)
+
+    def build_fake_model(**kwargs):
+        captured["config"] = kwargs
+        return fake_model
+
+    monkeypatch.setattr("nexent.core.models.OpenAIModel", build_fake_model)
     monkeypatch.setattr(
         "services.agent_automation.intent_analyzer.get_prompt_template",
         lambda *a, **k: {
@@ -251,6 +258,9 @@ def __call__(self, messages):
     assert result["analysis_source"] == "llm"
     assert result["is_automation_intent"] is True
     assert result["schedule_trigger"].cron_expr == "0 8 * * *"
+    from nexent.core.utils.observer import MessageObserver
+
+    assert isinstance(captured["config"]["observer"], MessageObserver)
     assert fake_model.calls[0] == {"role": "system", "content": "sys"}
     assert fake_model.calls[1]["content"].startswith("msg: ")
 

test/backend/services/test_agent_automation_prompt_generator.py

@@ -305,6 +305,9 @@ def __call__(self, messages):
     assert result == '{"title":"A","instruction":"B"}'
     assert captured["config"]["model_id"] == "resolved-model"
     assert captured["config"]["ssl_verify"] is False
+    from nexent.core.utils.observer import MessageObserver
+
+    assert isinstance(captured["config"]["observer"], MessageObserver)
     assert captured["messages"][1]["content"] == "Instruction: do work"
 
 

test/backend/services/test_agent_automation_tool_adapter.py

@@ -6,6 +6,7 @@
 from services.agent_automation.tool_adapter import (
     AgentLoopAutomationToolAdapter,
     AutomationToolRuntimeContext,
+    _strip_runtime_time_prefix,
     link_persisted_proposal_card,
 )
 
@@ -36,6 +37,24 @@ def test_build_tool_config_registers_scheduled_task_as_builtin(monkeypatch):
     assert callable(tool_config.metadata["create_proposal"])
 
 
+@pytest.mark.parametrize(
+    ("message", "expected"),
+    [
+        (
+            "[Current time: 2026-08-26 09:20:28]\n\n每天早上9点查一下八字信息",
+            "每天早上9点查一下八字信息",
+        ),
+        (
+            "[Current time: 2026-08-26 09:20:28]\n\nEvery day at 9 AM, check the report",
+            "Every day at 9 AM, check the report",
+        ),
+        ("每天九点生成日报", "每天九点生成日报"),
+    ],
+)
+def test_strip_runtime_time_prefix_keeps_only_the_original_request(message, expected):
+    assert _strip_runtime_time_prefix(message) == expected
+
+
 def test_build_callback_runs_coroutine_without_an_event_loop(monkeypatch):
     async def fake_create_proposal(context, request_text):
         return {"request_text": request_text, "conversation_id": context.conversation_id}
@@ -101,7 +120,7 @@ async def fake_create_proposal(request, tenant_id, user_id, **kwargs):
         user_id="user-1",
         conversation_id=20,
         agent_id=7,
-        user_message="每天九点生成日报",
+        user_message="[Current time: 2026-08-26 09:20:28]\n\n每天九点生成日报",
         source_message_id=101,
         model_id=3,
     )

test/sdk/core/agents/test_core_agent.py

@@ -375,12 +375,33 @@ def test_complete_answer_that_names_tool_is_not_misclassified():
     ) is False
 
 
+@pytest.mark.parametrize(
+    "output",
+    [
+        (
+            "思考：工具调用成功。根据策略，我需要用 `final_answer` 返回工具结果。\n\n"
+            "最终回答：\n定时任务提案已生成，请核对任务内容和执行时间后确认创建。"
+        ),
+        (
+            "Analysis: The tool call succeeded, so I will use `final_answer` to return the result.\n\n"
+            "Final answer:\nThe scheduled-task proposal is ready for confirmation."
+        ),
+    ],
+)
+def test_complete_explicit_final_answer_is_not_misclassified(output):
+    assert core_agent_module._looks_like_incomplete_action_output(
+        output,
+        available_tool_names={"final_answer", "create_scheduled_task_proposal"},
+    ) is False
+
+
 def test_length_truncated_non_code_output_is_not_a_final_answer():
     assert core_agent_module._looks_like_incomplete_action_output(
         "这是一个尚未完成的回答",
         finish_reason="length",
     ) is True
 
+
 def test_parse_code_blobs_run_format():
     """Test parse_code_blobs with <code>...</code> pattern (new format)."""
     text = """Here is some code: