> ## Documentation Index
> Fetch the complete documentation index at: https://traceroot.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Microsoft Agent Framework

> Auto-instrument Microsoft Agent Framework agent runs, model calls, and tool executions

Automatically capture agent runs, model calls, and tool executions from [Microsoft Agent Framework](https://github.com/microsoft/agent-framework) through its built-in OpenTelemetry emission — no manual instrumentation of the framework required.

## Setup

```python theme={null}
import traceroot
from traceroot import Integration

traceroot.initialize(integrations=[Integration.AGENT_FRAMEWORK])
```

Initialize TraceRoot **before** importing `agent_framework`, so the OpenTelemetry instrumentation is wired up before the framework emits its first span.

## Usage

Once initialized, every agent invocation, model call, and tool execution is captured automatically:

```python theme={null}
import asyncio

import traceroot
from traceroot import Integration

traceroot.initialize(integrations=[Integration.AGENT_FRAMEWORK])

# Import after initialize() so tracing is already active.
from agent_framework import Agent
from agent_framework.openai import OpenAIChatClient


def get_weather(city: str) -> str:
    """Return a short weather forecast for a city."""
    return f"{city}: 18°C, partly cloudy."


agent = Agent(
    OpenAIChatClient(model="gpt-4o-mini"),
    "You are a helpful travel concierge. Use the weather tool when relevant.",
    name="Concierge",
    tools=[get_weather],
)


async def main():
    # The agent run, the model call, and the get_weather tool call are all traced.
    response = await agent.run("What's the weather in Tokyo?")
    print(response.text)


asyncio.run(main())
```

Tools are plain functions — Agent Framework already emits an `execute_tool` span for each call, so they don't need manual decoration.

## What Gets Captured

| Attribute  | Description                                                   |
| ---------- | ------------------------------------------------------------- |
| Agent run  | Each agent invocation as a span (nested for delegated agents) |
| Model      | The chat model used for each call                             |
| Tool calls | An `execute_tool` span per tool execution, with arguments     |
| Response   | Generated text and tool outputs                               |
| Tokens     | Input and output token counts                                 |
| Cost       | Calculated from token usage and model pricing                 |
| Latency    | Request duration                                              |

## Run the example

Clone the repo and run a complete multi-agent example end-to-end.

<Card title="Python" icon="python" href="https://github.com/traceroot-ai/traceroot/tree/main/examples/python/microsoft-agent-framework">
  Run the Python example
</Card>