diff --git a/src/google/adk/tools/set_model_response_tool.py b/src/google/adk/tools/set_model_response_tool.py
index d1dc6ed55d..90c330f23c 100644
--- a/src/google/adk/tools/set_model_response_tool.py
+++ b/src/google/adk/tools/set_model_response_tool.py
@@ -87,8 +87,22 @@ def set_model_response() -> str:
               annotation=list[inner_type],
           )
       ]
+    elif isinstance(output_schema, dict):
+      # For raw dict schemas (e.g. {"type": "object", "properties": {...}}),
+      # use the `dict` type itself as the annotation rather than the dict
+      # instance. Passing the instance would later trigger
+      # `annotation in _py_builtin_type_to_schema_type.keys()` inside
+      # `_function_parameter_parse_util`, which calls `__hash__` on the
+      # annotation and raises `TypeError: unhashable type: 'dict'`.
+      params = [
+          inspect.Parameter(
+              'response',
+              inspect.Parameter.KEYWORD_ONLY,
+              annotation=dict,
+          )
+      ]
     else:
-      # For other schema types (list[str], dict, etc.),
+      # For other schema types (list[str], dict[str, int], etc.),
       # create a single parameter with the actual schema type
       params = [
           inspect.Parameter(
diff --git a/tests/unittests/tools/test_set_model_response_tool.py b/tests/unittests/tools/test_set_model_response_tool.py
index 5d658df67a..b90b069523 100644
--- a/tests/unittests/tools/test_set_model_response_tool.py
+++ b/tests/unittests/tools/test_set_model_response_tool.py
@@ -467,3 +467,87 @@ async def test_run_async_dict_schema():
   assert result is not None
   assert isinstance(result, dict)
   assert result == {'a': 1, 'b': 2, 'c': 3}
+
+
+# Regression tests for raw dict output_schema (issue #5469)
+
+
+def test_tool_initialization_raw_dict_schema():
+  """Raw dict output_schema must not crash and must be stored as-is."""
+  raw_schema = {
+      'type': 'object',
+      'properties': {'result': {'type': 'string'}},
+  }
+
+  tool = SetModelResponseTool(raw_schema)
+
+  assert tool.output_schema == raw_schema
+  assert not tool._is_basemodel
+  assert not tool._is_list_of_basemodel
+  assert tool.name == 'set_model_response'
+  assert tool.func is not None
+
+
+def test_function_signature_generation_raw_dict_schema():
+  """Raw dict schemas should produce a single `response: dict` parameter.
+
+  The annotation must be the `dict` type (hashable), not the dict instance,
+  so downstream `_is_builtin_primitive_or_compound` does not raise
+  `TypeError: unhashable type: 'dict'`.
+  """
+  raw_schema = {
+      'type': 'object',
+      'properties': {'result': {'type': 'string'}},
+  }
+
+  tool = SetModelResponseTool(raw_schema)
+
+  sig = inspect.signature(tool.func)
+
+  assert 'response' in sig.parameters
+  assert len(sig.parameters) == 1
+  assert sig.parameters['response'].kind == inspect.Parameter.KEYWORD_ONLY
+  # The annotation is the hashable `dict` type, not the dict instance.
+  assert sig.parameters['response'].annotation is dict
+
+
+def test_get_declaration_raw_dict_schema():
+  """`_get_declaration` must not raise when given a raw dict schema.
+
+  This is the original failure mode reported in issue #5469: building the
+  function declaration triggered `TypeError: unhashable type: 'dict'`
+  because the dict instance was used as an annotation.
+  """
+  raw_schema = {
+      'type': 'object',
+      'properties': {'result': {'type': 'string'}},
+  }
+
+  tool = SetModelResponseTool(raw_schema)
+
+  declaration = tool._get_declaration()
+
+  assert declaration is not None
+  assert declaration.name == 'set_model_response'
+  assert declaration.description is not None
+
+
+@pytest.mark.asyncio
+async def test_run_async_raw_dict_schema():
+  """Tool execution with a raw dict schema returns the response unchanged."""
+  raw_schema = {
+      'type': 'object',
+      'properties': {'result': {'type': 'string'}},
+  }
+  tool = SetModelResponseTool(raw_schema)
+
+  agent = LlmAgent(name='test_agent', model='gemini-1.5-flash')
+  invocation_context = await _create_invocation_context(agent)
+  tool_context = ToolContext(invocation_context)
+
+  result = await tool.run_async(
+      args={'response': {'result': 'hello'}},
+      tool_context=tool_context,
+  )
+
+  assert result == {'result': 'hello'}