diff --git a/agents-api/agents_api/activities/task_steps/tool_call_step.py b/agents-api/agents_api/activities/task_steps/tool_call_step.py
index 95d89d948..a93e5bb66 100644
--- a/agents-api/agents_api/activities/task_steps/tool_call_step.py
+++ b/agents-api/agents_api/activities/task_steps/tool_call_step.py
@@ -1,22 +1,23 @@
-from agents_api.autogen.Tasks import ToolCallStep
+import base64
+import secrets
+
 from beartype import beartype
 from temporalio import activity
 
+from agents_api.activities.task_steps import base_evaluate
+from agents_api.autogen.Tasks import ToolCallStep
+
 from ...common.protocol.tasks import (
     StepContext,
     StepOutcome,
 )
 
-import secrets
-import base64
-
 
 def generate_call_id():
     # Generate 18 random bytes (which will result in 24 base64 characters)
     random_bytes = secrets.token_bytes(18)
     # Encode to base64 and remove padding
-    base64_string = base64.urlsafe_b64encode(
-        random_bytes).decode('ascii').rstrip('=')
+    base64_string = base64.urlsafe_b64encode(random_bytes).decode("ascii").rstrip("=")
     # Add the "call_" prefix
     return f"call_{base64_string}"
 
@@ -27,27 +28,23 @@ async def tool_call_step(context: StepContext) -> StepOutcome:
     assert isinstance(context.current_step, ToolCallStep)
 
     tool_type, tool_name = context.current_step.tool.split(".")
-    arguments = context.current_step.arguments
+    arguments = await base_evaluate(
+        context.current_step.arguments, context.model_dump()
+    )
 
     tools = context.execution_input.tools
 
-    assert tool_name in [
-        tool.name for tool in tools], f"Tool {tool_name} not found"
+    assert tool_name in [tool.name for tool in tools], f"Tool {tool_name} not found"
 
     call_id = generate_call_id()
 
     tool_call = {
         tool_type: {
-            'arguments': arguments,
-            'name': tool_name,
+            "arguments": arguments,
+            "name": tool_name,
         },
-        'id': call_id,
-        'type': tool_type
+        "id": call_id,
+        "type": tool_type,
     }
 
-    print("tool_call")
-    print(tool_call)
-
-    return StepOutcome(
-        output=tool_call
-    )
+    return StepOutcome(output=tool_call)
diff --git a/agents-api/agents_api/workflows/task_execution/__init__.py b/agents-api/agents_api/workflows/task_execution/__init__.py
index 17aa1035a..d1f13585f 100644
--- a/agents-api/agents_api/workflows/task_execution/__init__.py
+++ b/agents-api/agents_api/workflows/task_execution/__init__.py
@@ -212,7 +212,7 @@ async def run(
 
         # 3. Then, based on the outcome and step type, decide what to do next
         workflow.logger.info(f"Processing outcome for step {context.cursor.step}")
-        
+
         match context.current_step, outcome:
             # Handle errors (activity returns None)
             case step, StepOutcome(error=error) if error is not None:
@@ -389,9 +389,7 @@ async def run(
 
                 state = PartialTransition(type="resume", output=result)
 
-            case PromptStep(), StepOutcome(
-                output=response
-            ):  
+            case PromptStep(), StepOutcome(output=response):
                 workflow.logger.debug(f"Prompt step: Received response: {response}")
                 if response["choices"][0]["finish_reason"] != "tool_calls":
                     workflow.logger.debug("Prompt step: Received response")
@@ -420,7 +418,6 @@ async def run(
                     )
                     state = PartialTransition(output=new_response.output, type="resume")
 
-
             case SetStep(), StepOutcome(output=evaluated_output):
                 workflow.logger.info("Set step: Updating user state")
                 self.update_user_state(evaluated_output)
@@ -461,8 +458,7 @@ async def run(
                     schedule_to_close_timeout=timedelta(days=31),
                 )
 
-                state = PartialTransition(
-                    output=tool_call_response, type="resume")
+                state = PartialTransition(output=tool_call_response, type="resume")
 
             case _:
                 workflow.logger.error(