diff --git a/backend/src/agents/expert.py b/backend/src/agents/expert.py
index f886b91..c414e18 100644
--- a/backend/src/agents/expert.py
+++ b/backend/src/agents/expert.py
@@ -1,5 +1,6 @@
 import inference
 from agent import Agent, AgentField
+from tool import ToolSpec
 
 import asyncio
 
@@ -43,18 +44,24 @@ async def chat_completion_loop(app, run, messages, model_id=None, tools=None):
         # Avoid infinite loops from server failures
         if len(messages) == pre_len: break
 
+        cancel_tools = False
         for tc in tool_calls:
             tool = next((t for t in tools if t.name == tc.tool_name), None)
             if tool is None:
                 print(f"[agent] unknown tool name: {tc.tool_name}")
                 continue
             if execute_tools:
-                tc.result = await tool.execute_async(**tc.arguments)
+                # Only known 'non-callable' tool spec
+                if isinstance(tool, ToolSpec) and not tool.func:
+                    cancel_tools = True
+                    tc.tool = tool
+                else:
+                    tc.result = await tool.execute_async(**tc.arguments)
             else:
                 tc.tool = tool
 
-        # If not calling, respond to end the turn
-        if not (tool_calls and execute_tools) and turn_response: break
+        # If not executing tools, respond to end the turn
+        if not (tool_calls and execute_tools) and turn_response or cancel_tools: break
 
     run.close()
 
@@ -87,8 +94,6 @@ class ExpertAgent(Agent):
         if run.input.get('tool_policy') != 'caller':
             tools += self.get_tools(run)
 
-        print("Final tool object: " + repr(run.input.get('tools', [])))
-
         # Build the initial message list
         messages = inference.build_messages(
             system_prompt=self.config.get("system_prompt", ""),
diff --git a/backend/src/app_mixins/agent.py b/backend/src/app_mixins/agent.py
index 84bde1d..7cd6806 100644
--- a/backend/src/app_mixins/agent.py
+++ b/backend/src/app_mixins/agent.py
@@ -186,6 +186,38 @@ class AgentMixin:
         # inference.Message objects. get_agent_control is awaited lazily on first
         # iteration, keeping the control object alive for the generator's
         # lifetime.
+
+        def normalize_tool(t):
+            # this function makes a lot of sense in ToolSpec itself...
+            from tool import ToolSpec, ToolParameter
+            if isinstance(t, dict):
+                params = []
+
+                d = t.get('parameters', {})
+                required = d.get('required', [])
+                props = d.get('properties', {})
+
+                for key, p in props.items():
+                    params.append(ToolParameter(
+                        name=key,
+                        type=p.get('type'),
+                        description=p.get('description'),
+                        required=key in required,
+                    ))
+                return ToolSpec(
+                    name=t['name'],
+                    description=t['description'],
+                    parameters=params,
+                )
+            else:
+                return t
+
+        if 'tools' in options:
+            options = {**options}
+            options['tools'] = [
+                normalize_tool(t) for t in options['tools']
+            ]
+
         control = await self.get_agent_control(agent_id)
         async for msg in control.prompt(instruction, input, **options):
             yield msg