diff --git a/astrbot/core/agent/runners/tool_loop_agent_runner.py b/astrbot/core/agent/runners/tool_loop_agent_runner.py
index cb7e22f341..93f45475e5 100644
--- a/astrbot/core/agent/runners/tool_loop_agent_runner.py
+++ b/astrbot/core/agent/runners/tool_loop_agent_runner.py
@@ -930,6 +930,7 @@ async def _resolve_tool_exec(
                     func_tool=param_subset,
                     model=self.req.model,
                     session_id=self.req.session_id,
+                    extra_user_content_parts=self.req.extra_user_content_parts,
                     abort_signal=self._abort_signal,
                 )
                 if requery_resp:
diff --git a/tests/test_tool_loop_agent_runner.py b/tests/test_tool_loop_agent_runner.py
index f983c5b4d4..ccab267351 100644
--- a/tests/test_tool_loop_agent_runner.py
+++ b/tests/test_tool_loop_agent_runner.py
@@ -699,6 +699,87 @@ async def test_follow_up_ticket_not_consumed_when_no_next_tool_call(
     assert ticket.consumed is False
 
 
+@pytest.mark.asyncio
+async def test_skills_like_requery_passes_extra_user_content_parts():
+    """skills-like 模式 re-query 时应传递 extra_user_content_parts（如 image_caption）"""
+    from astrbot.core.agent.message import TextPart
+
+    captured_kwargs = {}
+
+    class SkillsLikeProvider(MockProvider):
+        async def text_chat(self, **kwargs) -> LLMResponse:
+            self.call_count += 1
+            if self.call_count == 1:
+                # 第一次调用：返回工具选择（light schema）
+                return LLMResponse(
+                    role="assistant",
+                    completion_text="选择工具",
+                    tools_call_name=["test_tool"],
+                    tools_call_args=[{"query": "test"}],
+                    tools_call_ids=["call_1"],
+                    usage=TokenUsage(input_other=10, output=5),
+                )
+            if self.call_count == 2:
+                # 第二次调用：re-query with param schema
+                captured_kwargs.update(kwargs)
+                return LLMResponse(
+                    role="assistant",
+                    completion_text="调用工具",
+                    tools_call_name=["test_tool"],
+                    tools_call_args=[{"query": "actual"}],
+                    tools_call_ids=["call_2"],
+                    usage=TokenUsage(input_other=10, output=5),
+                )
+            # 后续调用：正常回复
+            return LLMResponse(
+                role="assistant",
+                completion_text="最终回复",
+                usage=TokenUsage(input_other=10, output=5),
+            )
+
+    provider = SkillsLikeProvider()
+    tool = FunctionTool(
+        name="test_tool",
+        description="测试",
+        parameters={"type": "object", "properties": {"query": {"type": "string"}}},
+        handler=AsyncMock(),
+    )
+    tool_set = ToolSet(tools=[tool])
+
+    caption_part = TextPart(text="<image_caption>一张猫的照片</image_caption>")
+    req = ProviderRequest(
+        prompt="看看这张图",
+        func_tool=tool_set,
+        contexts=[],
+        extra_user_content_parts=[caption_part],
+    )
+
+    event = MockEvent(umo="test_umo", sender_id="test_sender")
+    ctx = MockAgentContext(event)
+    run_context = ContextWrapper(context=ctx)
+    runner = ToolLoopAgentRunner()
+
+    await runner.reset(
+        provider=provider,
+        request=req,
+        run_context=run_context,
+        tool_executor=MockToolExecutor(),
+        agent_hooks=MockHooks(),
+        tool_schema_mode="skills_like",
+    )
+
+    async for _ in runner.step():
+        pass
+
+    # 验证 re-query 调用包含了 extra_user_content_parts
+    assert "extra_user_content_parts" in captured_kwargs, (
+        "re-query 应该传递 extra_user_content_parts"
+    )
+    parts = captured_kwargs["extra_user_content_parts"]
+    assert len(parts) == 1
+    assert parts[0].text == "<image_caption>一张猫的照片</image_caption>"
+
+
 @pytest.mark.asyncio
 async def test_follow_up_accepted_when_active_and_not_stopping(
     runner, mock_provider, provider_request, mock_tool_executor, mock_hooks