diff --git a/examples/agents/simple_chat.py b/examples/agents/simple_chat.py
index a76a4357..70570695 100644
--- a/examples/agents/simple_chat.py
+++ b/examples/agents/simple_chat.py
@@ -9,7 +9,7 @@
 from llama_stack_client import LlamaStackClient, Agent, AgentEventLogger
 from termcolor import colored
 
-from .utils import check_model_is_available, get_any_available_model
+from .utils import check_model_is_available, get_any_available_chat_model
 
 
 def main(host: str, port: int, model_id: str | None = None):
@@ -27,14 +27,8 @@ def main(host: str, port: int, model_id: str | None = None):
         provider_data={"tavily_search_api_key": os.getenv("TAVILY_SEARCH_API_KEY")},
     )
 
-    available_shields = [shield.identifier for shield in client.shields.list()]
-    if not available_shields:
-        print(colored("No available shields. Disabling safety.", "yellow"))
-    else:
-        print(f"Available shields found: {available_shields}")
-
     if model_id is None:
-        model_id = get_any_available_model(client)
+        model_id = get_any_available_chat_model(client)
         if model_id is None:
             return
     else:
@@ -47,10 +41,8 @@ def main(host: str, port: int, model_id: str | None = None):
         client,
         model=model_id,
         instructions="",
-        tools=["builtin::websearch"],
-        input_shields=available_shields,
-        output_shields=available_shields,
-        enable_session_persistence=False,
+        # OpenAI Responses tool schema requires a type discriminator.
+        tools=[{"type": "web_search"}],
     )
     user_prompts = [
         "Hello",
@@ -65,8 +57,8 @@ def main(host: str, port: int, model_id: str | None = None):
             session_id=session_id,
         )
 
-        for log in AgentEventLogger().log(response):
-            log.print()
+        for printable in AgentEventLogger().log(response):
+            print(printable, end="", flush=True)
 
 
 if __name__ == "__main__":
diff --git a/examples/agents/utils.py b/examples/agents/utils.py
index 298be9a0..8878d81e 100644
--- a/examples/agents/utils.py
+++ b/examples/agents/utils.py
@@ -2,11 +2,36 @@
 from termcolor import colored
 
 
+def _get_model_type(model) -> str | None:
+    for metadata_attr in ("custom_metadata", "metadata"):
+        metadata = getattr(model, metadata_attr, None)
+        if isinstance(metadata, dict):
+            value = metadata.get("model_type") or metadata.get("type")
+            if isinstance(value, str):
+                return value
+    return None
+
+
+def _is_llm_model(model) -> bool:
+    model_type = _get_model_type(model)
+    # If the client schema doesn't expose type fields, assume LLM.
+    return model_type is None or model_type == "llm"
+
+
+def _get_model_id(model) -> str | None:
+    for attr in ("identifier", "model_id", "id", "name"):
+        value = getattr(model, attr, None)
+        if isinstance(value, str):
+            return value
+    return None
+
+
 def check_model_is_available(client: LlamaStackClient, model: str):
     available_models = [
-        model.identifier
+        model_id
         for model in client.models.list()
-        if model.model_type == "llm" and "guard" not in model.identifier
+        for model_id in [_get_model_id(model)]
+        if model_id and _is_llm_model(model) and "guard" not in model_id
     ]
 
     if model not in available_models:
@@ -23,12 +48,44 @@ def check_model_is_available(client: LlamaStackClient, model: str):
 
 def get_any_available_model(client: LlamaStackClient):
     available_models = [
-        model.identifier
+        model_id
         for model in client.models.list()
-        if model.model_type == "llm" and "guard" not in model.identifier
+        for model_id in [_get_model_id(model)]
+        if model_id and _is_llm_model(model) and "guard" not in model_id
     ]
     if not available_models:
         print(colored("No available models.", "red"))
         return None
 
     return available_models[0]
+
+
+def can_model_chat(client: LlamaStackClient, model_id: str) -> bool:
+    # Lightweight probe to ensure the model supports chat completions.
+    try:
+        client.chat.completions.create(
+            model=model_id,
+            messages=[{"role": "user", "content": "ping"}],
+            max_tokens=1,
+        )
+    except Exception:
+        return False
+    return True
+
+def get_any_available_chat_model(client: LlamaStackClient):
+    available_models = [
+        model_id
+        for model in client.models.list()
+        for model_id in [_get_model_id(model)]
+        if model_id and _is_llm_model(model) and "guard" not in model_id
+    ]
+    if not available_models:
+        print(colored("No available models.", "red"))
+        return None
+
+    for model_id in available_models:
+        if can_model_chat(client, model_id):
+            return model_id
+
+    print(colored("No available chat-capable models.", "red"))
+    return None