diff --git a/libs/core/langchain_core/tools/base.py b/libs/core/langchain_core/tools/base.py
index 9782234dfb1a0..65c707207bf69 100644
--- a/libs/core/langchain_core/tools/base.py
+++ b/libs/core/langchain_core/tools/base.py
@@ -348,7 +348,7 @@ class ChildTool(BaseTool):
 
     name: str
     """The unique name of the tool that clearly communicates its purpose."""
-    description: str
+    description: Optional[str] = None
     """Used to tell the model how/when/why to use the tool.
 
     You can provide few-shot examples as a part of the description.
diff --git a/libs/core/langchain_core/tools/structured.py b/libs/core/langchain_core/tools/structured.py
index 174e7b2f53704..35388d327f475 100644
--- a/libs/core/langchain_core/tools/structured.py
+++ b/libs/core/langchain_core/tools/structured.py
@@ -32,7 +32,7 @@
 class StructuredTool(BaseTool):
     """Tool that can operate on any number of inputs."""
 
-    description: str = ""
+    description: Optional[str] = ""
     args_schema: Annotated[TypeBaseModel, SkipValidation()] = Field(
         ..., description="The tool schema."
     )
@@ -185,16 +185,14 @@ def add(a: int, b: int) -> int:
             description_ = source_function.__doc__ or None
         if description_ is None and args_schema:
             description_ = args_schema.__doc__ or None
-        if description_ is None:
-            msg = "Function must have a docstring if description not provided."
-            raise ValueError(msg)
-        if description is None:
+        if description is None and description_ is not None:
             # Only apply if using the function's docstring
             description_ = textwrap.dedent(description_).strip()
 
         # Description example:
         # search_api(query: str) - Searches the API for the query.
-        description_ = f"{description_.strip()}"
+        if description_:
+            description_ = f"{description_.strip()}"
         return cls(
             name=name,
             func=func,
diff --git a/libs/core/langchain_core/utils/function_calling.py b/libs/core/langchain_core/utils/function_calling.py
index 1a1c26443c786..e0e5a424831ae 100644
--- a/libs/core/langchain_core/utils/function_calling.py
+++ b/libs/core/langchain_core/utils/function_calling.py
@@ -20,7 +20,7 @@
 )
 
 from pydantic import BaseModel
-from typing_extensions import TypedDict, get_args, get_origin, is_typeddict
+from typing_extensions import NotRequired, TypedDict, get_args, get_origin, is_typeddict
 
 from langchain_core._api import deprecated
 from langchain_core.messages import AIMessage, BaseMessage, HumanMessage, ToolMessage
@@ -45,10 +45,16 @@ class FunctionDescription(TypedDict):
 
     name: str
     """The name of the function."""
-    description: str
+    description: NotRequired[str]
     """A description of the function."""
-    parameters: dict
+    parameters: NotRequired[dict]
     """The parameters of the function."""
+    strict: NotRequired[Optional[bool]]
+    """Whether to enable strict schema adherence when generating the function call.
+    
+    If set to True, the model will follow the exact schema defined in the parameters
+    field. Only a subset of JSON Schema is supported when strict is True.
+    """
 
 
 class ToolDescription(TypedDict):
@@ -294,9 +300,8 @@ def format_tool_to_openai_function(tool: BaseTool) -> FunctionDescription:
             tool.tool_call_schema, name=tool.name, description=tool.description
         )
     else:
-        return {
+        oai_function = {
             "name": tool.name,
-            "description": tool.description,
             "parameters": {
                 # This is a hack to get around the fact that some tools
                 # do not expose an args_schema, and expect an argument
@@ -310,6 +315,9 @@ def format_tool_to_openai_function(tool: BaseTool) -> FunctionDescription:
                 "type": "object",
             },
         }
+        if tool.description:
+            oai_function["description"] = tool.description
+        return cast(FunctionDescription, oai_function)
 
 
 @deprecated(
diff --git a/libs/core/tests/unit_tests/runnables/test_runnable.py b/libs/core/tests/unit_tests/runnables/test_runnable.py
index d1f67a6c8d9ef..09ab6ecf4bfe1 100644
--- a/libs/core/tests/unit_tests/runnables/test_runnable.py
+++ b/libs/core/tests/unit_tests/runnables/test_runnable.py
@@ -4623,6 +4623,7 @@ async def test_tool_from_runnable() -> None:
     assert await chain_tool.arun({"question": "What up"}) == await chain.ainvoke(
         {"question": "What up"}
     )
+    assert chain_tool.description
     assert chain_tool.description.endswith(repr(chain))
     assert _schema(chain_tool.args_schema) == chain.get_input_jsonschema()
     assert _schema(chain_tool.args_schema) == {
diff --git a/libs/core/tests/unit_tests/test_tools.py b/libs/core/tests/unit_tests/test_tools.py
index ce7ea4894bb5a..45552893d392d 100644
--- a/libs/core/tests/unit_tests/test_tools.py
+++ b/libs/core/tests/unit_tests/test_tools.py
@@ -651,13 +651,21 @@ def search_api(
 
 
 def test_missing_docstring() -> None:
-    """Test error is raised when docstring is missing."""
-    # expect to throw a value error if there's no docstring
-    with pytest.raises(ValueError, match="Function must have a docstring"):
+    """Test error is not raised when docstring is missing."""
 
-        @tool
-        def search_api(query: str) -> str:
-            return "API result"
+    @tool
+    def search_api(query: str) -> str:
+        return "API result"
+
+    assert search_api.name == "search_api"
+    assert search_api.description is None
+    assert search_api.args_schema
+    assert search_api.args_schema.model_json_schema() == {
+        "properties": {"query": {"title": "Query", "type": "string"}},
+        "required": ["query"],
+        "title": "search_api",
+        "type": "object",
+    }
 
 
 def test_create_tool_positional_args() -> None: