diff --git a/astrbot/core/agent/runners/tool_loop_agent_runner.py b/astrbot/core/agent/runners/tool_loop_agent_runner.py
index 069de144f..5079d6484 100644
--- a/astrbot/core/agent/runners/tool_loop_agent_runner.py
+++ b/astrbot/core/agent/runners/tool_loop_agent_runner.py
@@ -76,12 +76,19 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
 
     async def _iter_llm_responses(self) -> T.AsyncGenerator[LLMResponse, None]:
         """Yields chunks *and* a final LLMResponse."""
+        payload = {
+            "contexts": self.run_context.messages,
+            "func_tool": self.req.func_tool,
+            "model": self.req.model,  # NOTE: in fact, this arg is None in most cases
+            "session_id": self.req.session_id,
+        }
+
         if self.streaming:
-            stream = self.provider.text_chat_stream(**self.req.__dict__)
+            stream = self.provider.text_chat_stream(**payload)
             async for resp in stream:  # type: ignore
                 yield resp
         else:
-            yield await self.provider.text_chat(**self.req.__dict__)
+            yield await self.provider.text_chat(**payload)
 
     @override
     async def step(self):
@@ -230,6 +237,25 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
             async for resp in self.step():
                 yield resp
 
+        #  如果循环结束了但是 agent 还没有完成，说明是达到了 max_step
+        if not self.done():
+            logger.warning(
+                f"Agent reached max steps ({max_step}), forcing a final response."
+            )
+            # 拔掉所有工具
+            if self.req:
+                self.req.func_tool = None
+            # 注入提示词
+            self.run_context.messages.append(
+                Message(
+                    role="user",
+                    content="工具调用次数已达到上限，请停止使用工具，并根据已经收集到的信息，对你的任务和发现进行总结，然后直接回复用户。",
+                )
+            )
+            # 再执行最后一步
+            async for resp in self.step():
+                yield resp
+
     async def _handle_function_tools(
         self,
         req: ProviderRequest,
diff --git a/astrbot/core/astr_agent_run_util.py b/astrbot/core/astr_agent_run_util.py
index 5421a14c0..d57cf5e93 100644
--- a/astrbot/core/astr_agent_run_util.py
+++ b/astrbot/core/astr_agent_run_util.py
@@ -2,6 +2,7 @@ import traceback
 from collections.abc import AsyncGenerator
 
 from astrbot.core import logger
+from astrbot.core.agent.message import Message
 from astrbot.core.agent.runners.tool_loop_agent_runner import ToolLoopAgentRunner
 from astrbot.core.astr_agent_context import AstrAgentContext
 from astrbot.core.message.components import Json
@@ -24,8 +25,25 @@ async def run_agent(
 ) -> AsyncGenerator[MessageChain | None, None]:
     step_idx = 0
     astr_event = agent_runner.run_context.context.event
-    while step_idx < max_step:
+    while step_idx < max_step + 1:
         step_idx += 1
+
+        if step_idx == max_step + 1:
+            logger.warning(
+                f"Agent reached max steps ({max_step}), forcing a final response."
+            )
+            if not agent_runner.done():
+                # 拔掉所有工具
+                if agent_runner.req:
+                    agent_runner.req.func_tool = None
+                # 注入提示词
+                agent_runner.run_context.messages.append(
+                    Message(
+                        role="user",
+                        content="工具调用次数已达到上限，请停止使用工具，并根据已经收集到的信息，对你的任务和发现进行总结，然后直接回复用户。",
+                    )
+                )
+
         try:
             async for resp in agent_runner.step():
                 if astr_event.is_stopped():
diff --git a/astrbot/core/pipeline/process_stage/method/agent_sub_stages/internal.py b/astrbot/core/pipeline/process_stage/method/agent_sub_stages/internal.py
index 7e3305f55..d147a811f 100644
--- a/astrbot/core/pipeline/process_stage/method/agent_sub_stages/internal.py
+++ b/astrbot/core/pipeline/process_stage/method/agent_sub_stages/internal.py
@@ -321,7 +321,12 @@ class InternalAgentSubStage(Stage):
             elif isinstance(req.tool_calls_result, list):
                 for tcr in req.tool_calls_result:
                     messages.extend(tcr.to_openai_messages())
-        messages.append({"role": "assistant", "content": llm_response.completion_text})
+        messages.append(
+            {
+                "role": "assistant",
+                "content": llm_response.completion_text or "*No response*",
+            }
+        )
         messages = list(filter(lambda item: "_no_save" not in item, messages))
         await self.conv_manager.update_conversation(
             event.unified_msg_origin,
diff --git a/tests/test_tool_loop_agent_runner.py b/tests/test_tool_loop_agent_runner.py
new file mode 100644
index 000000000..f0e90002d
--- /dev/null
+++ b/tests/test_tool_loop_agent_runner.py
@@ -0,0 +1,326 @@
+import os
+import sys
+from unittest.mock import AsyncMock
+
+import pytest
+
+# 将项目根目录添加到 sys.path
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
+
+from astrbot.core.agent.hooks import BaseAgentRunHooks
+from astrbot.core.agent.run_context import ContextWrapper
+from astrbot.core.agent.runners.tool_loop_agent_runner import ToolLoopAgentRunner
+from astrbot.core.agent.tool import FunctionTool, ToolSet
+from astrbot.core.provider.entities import LLMResponse, ProviderRequest, TokenUsage
+from astrbot.core.provider.provider import Provider
+
+
+class MockProvider(Provider):
+    """模拟Provider用于测试"""
+
+    def __init__(self):
+        super().__init__({}, {})
+        self.call_count = 0
+        self.should_call_tools = True
+        self.max_calls_before_normal_response = 10
+
+    def get_current_key(self) -> str:
+        return "test_key"
+
+    def set_key(self, key: str):
+        pass
+
+    async def get_models(self) -> list[str]:
+        return ["test_model"]
+
+    async def text_chat(self, **kwargs) -> LLMResponse:
+        self.call_count += 1
+
+        # 检查工具是否被禁用
+        func_tool = kwargs.get("func_tool")
+
+        # 如果工具被禁用或超过最大调用次数，返回正常响应
+        if func_tool is None or self.call_count > self.max_calls_before_normal_response:
+            return LLMResponse(
+                role="assistant",
+                completion_text="这是我的最终回答",
+                usage=TokenUsage(input_other=10, output=5),
+            )
+
+        # 模拟工具调用响应
+        if self.should_call_tools:
+            return LLMResponse(
+                role="assistant",
+                completion_text="我需要使用工具来帮助您",
+                tools_call_name=["test_tool"],
+                tools_call_args=[{"query": "test"}],
+                tools_call_ids=["call_123"],
+                usage=TokenUsage(input_other=10, output=5),
+            )
+
+        # 默认返回正常响应
+        return LLMResponse(
+            role="assistant",
+            completion_text="这是我的最终回答",
+            usage=TokenUsage(input_other=10, output=5),
+        )
+
+    async def text_chat_stream(self, **kwargs):
+        response = await self.text_chat(**kwargs)
+        response.is_chunk = True
+        yield response
+        response.is_chunk = False
+        yield response
+
+
+class MockToolExecutor:
+    """模拟工具执行器"""
+
+    @classmethod
+    def execute(cls, tool, run_context, **tool_args):
+        async def generator():
+            # 模拟工具返回结果，使用正确的类型
+            from mcp.types import CallToolResult, TextContent
+
+            result = CallToolResult(
+                content=[TextContent(type="text", text="工具执行结果")]
+            )
+            yield result
+
+        return generator()
+
+
+class MockHooks(BaseAgentRunHooks):
+    """模拟钩子函数"""
+
+    def __init__(self):
+        self.agent_begin_called = False
+        self.agent_done_called = False
+        self.tool_start_called = False
+        self.tool_end_called = False
+
+    async def on_agent_begin(self, run_context):
+        self.agent_begin_called = True
+
+    async def on_tool_start(self, run_context, tool, tool_args):
+        self.tool_start_called = True
+
+    async def on_tool_end(self, run_context, tool, tool_args, tool_result):
+        self.tool_end_called = True
+
+    async def on_agent_done(self, run_context, llm_response):
+        self.agent_done_called = True
+
+
+@pytest.fixture
+def mock_provider():
+    return MockProvider()
+
+
+@pytest.fixture
+def mock_tool_executor():
+    return MockToolExecutor()
+
+
+@pytest.fixture
+def mock_hooks():
+    return MockHooks()
+
+
+@pytest.fixture
+def tool_set():
+    """创建测试用的工具集"""
+    tool = FunctionTool(
+        name="test_tool",
+        description="测试工具",
+        parameters={"type": "object", "properties": {"query": {"type": "string"}}},
+        handler=AsyncMock(),
+    )
+    return ToolSet(tools=[tool])
+
+
+@pytest.fixture
+def provider_request(tool_set):
+    """创建测试用的ProviderRequest"""
+    return ProviderRequest(prompt="请帮我查询信息", func_tool=tool_set, contexts=[])
+
+
+@pytest.fixture
+def runner():
+    """创建ToolLoopAgentRunner实例"""
+    return ToolLoopAgentRunner()
+
+
+@pytest.mark.asyncio
+async def test_max_step_limit_functionality(
+    runner, mock_provider, provider_request, mock_tool_executor, mock_hooks
+):
+    """测试最大步数限制功能"""
+
+    # 设置模拟provider，让它总是返回工具调用
+    mock_provider.should_call_tools = True
+    mock_provider.max_calls_before_normal_response = (
+        100  # 设置一个很大的值，确保不会自然结束
+    )
+
+    # 初始化runner
+    await runner.reset(
+        provider=mock_provider,
+        request=provider_request,
+        run_context=ContextWrapper(context=None),
+        tool_executor=mock_tool_executor,
+        agent_hooks=mock_hooks,
+        streaming=False,
+    )
+
+    # 设置较小的最大步数来测试限制功能
+    max_steps = 3
+
+    # 收集所有响应
+    responses = []
+    async for response in runner.step_until_done(max_steps):
+        responses.append(response)
+
+    # 验证结果
+    assert runner.done(), "代理应该在达到最大步数后完成"
+
+    # 验证工具被禁用（这是最重要的验证点）
+    assert runner.req.func_tool is None, "达到最大步数后工具应该被禁用"
+
+    # 验证有最终响应
+    final_responses = [r for r in responses if r.type == "llm_result"]
+    assert len(final_responses) > 0, "应该有最终的LLM响应"
+
+    # 验证最后一条消息是assistant的最终回答
+    last_message = runner.run_context.messages[-1]
+    assert last_message.role == "assistant", "最后一条消息应该是assistant的最终回答"
+
+
+@pytest.mark.asyncio
+async def test_normal_completion_without_max_step(
+    runner, mock_provider, provider_request, mock_tool_executor, mock_hooks
+):
+    """测试正常完成（不触发最大步数限制）"""
+
+    # 设置模拟provider，让它在第2次调用时返回正常响应
+    mock_provider.should_call_tools = True
+    mock_provider.max_calls_before_normal_response = 2
+
+    # 初始化runner
+    await runner.reset(
+        provider=mock_provider,
+        request=provider_request,
+        run_context=ContextWrapper(context=None),
+        tool_executor=mock_tool_executor,
+        agent_hooks=mock_hooks,
+        streaming=False,
+    )
+
+    # 设置足够大的最大步数
+    max_steps = 10
+
+    # 收集所有响应
+    responses = []
+    async for response in runner.step_until_done(max_steps):
+        responses.append(response)
+
+    # 验证结果
+    assert runner.done(), "代理应该正常完成"
+
+    # 验证没有触发最大步数限制 - 通过检查provider调用次数
+    # mock_provider在第2次调用后返回正常响应，所以不应该达到max_steps(10)
+    assert mock_provider.call_count < max_steps, (
+        f"正常完成时调用次数({mock_provider.call_count})应该小于最大步数({max_steps})"
+    )
+
+    # 验证没有最大步数警告消息（注意：实际注入的是user角色的消息）
+    user_messages = [m for m in runner.run_context.messages if m.role == "user"]
+    max_step_messages = [
+        m for m in user_messages if "工具调用次数已达到上限" in m.content
+    ]
+    assert len(max_step_messages) == 0, "正常完成时不应该有步数限制消息"
+
+    # 验证工具仍然可用（没有被禁用）
+    assert runner.req.func_tool is not None, "正常完成时工具不应该被禁用"
+
+
+@pytest.mark.asyncio
+async def test_max_step_with_streaming(
+    runner, mock_provider, provider_request, mock_tool_executor, mock_hooks
+):
+    """测试流式响应下的最大步数限制"""
+
+    # 设置模拟provider
+    mock_provider.should_call_tools = True
+    mock_provider.max_calls_before_normal_response = 100
+
+    # 初始化runner，启用流式响应
+    await runner.reset(
+        provider=mock_provider,
+        request=provider_request,
+        run_context=ContextWrapper(context=None),
+        tool_executor=mock_tool_executor,
+        agent_hooks=mock_hooks,
+        streaming=True,
+    )
+
+    # 设置较小的最大步数
+    max_steps = 2
+
+    # 收集所有响应
+    responses = []
+    async for response in runner.step_until_done(max_steps):
+        responses.append(response)
+
+    # 验证结果
+    assert runner.done(), "代理应该在达到最大步数后完成"
+
+    # 验证有流式响应
+    streaming_responses = [r for r in responses if r.type == "streaming_delta"]
+    assert len(streaming_responses) > 0, "应该有流式响应"
+
+    # 验证工具被禁用
+    assert runner.req.func_tool is None, "达到最大步数后工具应该被禁用"
+
+    # 验证最后一条消息是assistant的最终回答
+    last_message = runner.run_context.messages[-1]
+    assert last_message.role == "assistant", "最后一条消息应该是assistant的最终回答"
+
+
+@pytest.mark.asyncio
+async def test_hooks_called_with_max_step(
+    runner, mock_provider, provider_request, mock_tool_executor, mock_hooks
+):
+    """测试达到最大步数时钩子函数是否被正确调用"""
+
+    # 设置模拟provider
+    mock_provider.should_call_tools = True
+    mock_provider.max_calls_before_normal_response = 100
+
+    # 初始化runner
+    await runner.reset(
+        provider=mock_provider,
+        request=provider_request,
+        run_context=ContextWrapper(context=None),
+        tool_executor=mock_tool_executor,
+        agent_hooks=mock_hooks,
+        streaming=False,
+    )
+
+    # 设置较小的最大步数
+    max_steps = 2
+
+    # 执行步骤
+    async for response in runner.step_until_done(max_steps):
+        pass
+
+    # 验证钩子函数被调用
+    assert mock_hooks.agent_begin_called, "on_agent_begin应该被调用"
+    assert mock_hooks.agent_done_called, "on_agent_done应该被调用"
+    assert mock_hooks.tool_start_called, "on_tool_start应该被调用"
+    assert mock_hooks.tool_end_called, "on_tool_end应该被调用"
+
+
+if __name__ == "__main__":
+    # 运行测试
+    pytest.main([__file__, "-v"])