diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py
index 17815976b4a..d7f6e6ab6d1 100644
--- a/litellm/completion_extras/litellm_responses_transformation/transformation.py
+++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py
@@ -922,7 +922,13 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
         if role == "user" or role == "system" or role == "tool":
             return {"type": "input_text", "text": content}
         else:
-            return {"type": "output_text", "text": content}
+            return {"type": "output_text", "text": content, "annotations": []}
+
+    @staticmethod
+    def _ensure_output_text_annotations(item: dict[str, object]) -> dict[str, object]:
+        if item.get("type") == "output_text":
+            return {"annotations": [], **item}
+        return item
 
     def _convert_content_to_responses_format_image(
         self, content: "ChatCompletionImageObject", role: str
@@ -1027,7 +1033,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
                             "summary_text",
                         ]:
                             # Already in responses API format
-                            result.append(item)
+                            result.append(self._ensure_output_text_annotations(item))
                             verbose_logger.debug("Chat provider:   passthrough -> %s", item)
                         else:
                             # Default to input_text for unknown types
diff --git a/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py b/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py
index 6ca48ce63b8..e5ac10584ca 100644
--- a/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py
+++ b/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py
@@ -21,6 +21,59 @@ if TYPE_CHECKING:
     from litellm.types.utils import ModelResponse
 
 
+@pytest.mark.parametrize(
+    ("content", "expected_content"),
+    [
+        (
+            "ok",
+            [{"type": "output_text", "text": "ok", "annotations": []}],
+        ),
+        (
+            [{"type": "text", "text": "ok"}],
+            [{"type": "output_text", "text": "ok", "annotations": []}],
+        ),
+        (
+            [{"type": "input_text", "text": "ok"}],
+            [{"type": "input_text", "text": "ok"}],
+        ),
+        (
+            [{"type": "output_text", "text": "ok"}],
+            [{"type": "output_text", "text": "ok", "annotations": []}],
+        ),
+        (
+            [
+                {
+                    "type": "output_text",
+                    "text": "ok",
+                    "annotations": [{"type": "url_citation", "url": "https://example.com"}],
+                }
+            ],
+            [
+                {
+                    "type": "output_text",
+                    "text": "ok",
+                    "annotations": [{"type": "url_citation", "url": "https://example.com"}],
+                }
+            ],
+        ),
+    ],
+)
+def test_assistant_output_text_includes_required_annotations(content, expected_content):
+    handler = LiteLLMResponsesTransformationHandler()
+
+    response, _ = handler.convert_chat_completion_messages_to_responses_api(
+        [{"role": "assistant", "content": content}]
+    )
+
+    assert response == [
+        {
+            "type": "message",
+            "role": "assistant",
+            "content": expected_content,
+        }
+    ]
+
+
 def test_convert_chat_completion_messages_to_responses_api_image_input():
     from litellm.completion_extras.litellm_responses_transformation.transformation import (
         LiteLLMResponsesTransformationHandler,