diff --git a/python/samples/02-agents/harness/build_your_own_claw/claw_step03_scaling_capabilities.py b/python/samples/02-agents/harness/build_your_own_claw/claw_step03_scaling_capabilities.py
index 9c2d31254f2..dbab85a8b55 100644
--- a/python/samples/02-agents/harness/build_your_own_claw/claw_step03_scaling_capabilities.py
+++ b/python/samples/02-agents/harness/build_your_own_claw/claw_step03_scaling_capabilities.py
@@ -58,9 +58,9 @@
 
 import httpx
 from agent_framework import (
-    AggregatingSkillsSource,
     Agent,
     AgentModeProvider,
+    AggregatingSkillsSource,
     DeduplicatingSkillsSource,
     FileAccessProvider,
     FileSkillsSource,
@@ -84,7 +84,6 @@
 # subprocess script runner used to execute file-based skill scripts.
 sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
 from console import build_observers_with_planning, run_agent_async  # noqa: E402
-
 from subprocess_script_runner import subprocess_script_runner  # noqa: E402
 
 _SAMPLE_DIR = Path(__file__).resolve().parent
diff --git a/python/samples/02-agents/observability/README.md b/python/samples/02-agents/observability/README.md
index a94a199a535..4ed36c0c4b6 100644
--- a/python/samples/02-agents/observability/README.md
+++ b/python/samples/02-agents/observability/README.md
@@ -78,6 +78,16 @@ configure_otel_providers(exporters=exporters)
 
 Many third-party OTel packages ship their own setup helpers (for example, Azure Monitor's `configure_azure_monitor()`). You can use those directly — Agent Framework instrumentation is on by default, so no extra wiring is needed. To also capture sensitive data, call `enable_sensitive_telemetry()` from `agent_framework.observability`.
 
+The [Microsoft OpenTelemetry Distro](https://pypi.org/project/microsoft-opentelemetry/) bundles this pattern into a single call. Install it with `pip install microsoft-opentelemetry`, then call `use_microsoft_opentelemetry()`, which wires up the OpenTelemetry providers/exporters (optionally including Azure Monitor) and enables Agent Framework instrumentation:
+
+```python
+from microsoft.opentelemetry import use_microsoft_opentelemetry
+
+# Sets up OpenTelemetry providers/exporters and enables Agent Framework instrumentation.
+# Pass enable_azure_monitor=True to also configure the Azure Monitor exporter.
+use_microsoft_opentelemetry(enable_azure_monitor=True)
+```
+
 ```python
 from azure.monitor.opentelemetry import configure_azure_monitor
 from agent_framework.observability import create_resource, enable_sensitive_telemetry
@@ -334,6 +344,7 @@ This folder contains different samples demonstrating how to use telemetry in var
 | [configure_otel_providers_with_parameters.py](./configure_otel_providers_with_parameters.py) | Create custom exporters with specific configuration and pass them to `configure_otel_providers()`. |
 | [agent_observability.py](./agent_observability.py) | Telemetry collection for an agentic application with tool calls. |
 | [foundry_tracing.py](./foundry_tracing.py) | Azure Monitor integration with Microsoft Foundry. |
+| [microsoft_opentelemetry_distro.py](./microsoft_opentelemetry_distro.py) | One-call setup with the Microsoft OpenTelemetry Distro (`use_microsoft_opentelemetry()`), optionally enabling Azure Monitor. |
 | [workflow_observability.py](./workflow_observability.py) | Telemetry collection for a workflow with multiple executors and message passing. |
 | [advanced_manual_setup_console_output.py](./advanced_manual_setup_console_output.py) | Advanced: manual setup of exporters and providers with console output — useful for understanding how observability works under the hood. |
 | [advanced_zero_code.py](./advanced_zero_code.py) | Advanced: zero-code provider/exporter setup using the `opentelemetry-instrument` CLI wrapper. |
diff --git a/python/samples/02-agents/observability/microsoft_opentelemetry_distro.py b/python/samples/02-agents/observability/microsoft_opentelemetry_distro.py
new file mode 100644
index 00000000000..7eb3ea61d15
--- /dev/null
+++ b/python/samples/02-agents/observability/microsoft_opentelemetry_distro.py
@@ -0,0 +1,79 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = [
+#     "agent-framework-foundry",
+#     "microsoft-opentelemetry",
+# ]
+# ///
+# Run with any PEP 723 compatible runner, e.g.:
+#   uv run python/samples/02-agents/observability/microsoft_opentelemetry_distro.py
+
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+from random import randint
+from typing import Annotated
+
+from agent_framework import Agent, tool
+from agent_framework.foundry import FoundryChatClient
+from agent_framework.observability import get_tracer
+from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+from microsoft.opentelemetry import use_microsoft_opentelemetry
+from opentelemetry.trace import SpanKind
+from opentelemetry.trace.span import format_trace_id
+from pydantic import Field
+
+# Load environment variables from .env file
+load_dotenv()
+
+
+@tool(approval_mode="never_require")
+async def get_weather(
+    location: Annotated[str, Field(description="The location to get the weather for.")],
+) -> str:
+    """Get the weather for a given location."""
+    await asyncio.sleep(randint(0, 10) / 10.0)  # Simulate a network call
+    conditions = ["sunny", "cloudy", "rainy", "stormy"]
+    return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
+
+
+async def main():
+    # Set up Azure monitor exporters for telemetry
+    # This will automatically enable instrumentation for Agent Framework
+    # Install the Microsoft OpenTelemetry Distro package to enable this functionality:
+    # pip install microsoft-opentelemetry
+    # Requires the following environment variables to be set:
+    # OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4318
+    # APPLICATIONINSIGHTS_CONNECTION_STRING=InstrumentationKey...
+    use_microsoft_opentelemetry(enable_azure_monitor=True)
+
+    questions = [
+        "What's the weather in Amsterdam?",
+        "and in Paris, and which is better?",
+        "Why is the sky blue?",
+    ]
+
+    with get_tracer().start_as_current_span(
+        "Scenario: Agent Chat", kind=SpanKind.CLIENT
+    ) as current_span:
+        print(f"Trace ID: {format_trace_id(current_span.get_span_context().trace_id)}")
+
+        agent = Agent(
+            client=FoundryChatClient(credential=AzureCliCredential()),
+            tools=get_weather,
+            name="WeatherAgent",
+            instructions="You are a weather assistant.",
+            id="weather-agent",
+        )
+        session = agent.create_session()
+        for question in questions:
+            print(f"\nUser: {question}")
+            print(f"{agent.name}: ", end="")
+            async for update in agent.run(question, session=session, stream=True):
+                if update.text:
+                    print(update.text, end="")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())