agency-swarm-cn-git/docs/additional-features/custom-communication-flows/common-use-cases.mdx

---
title: "Common Use Cases"
description: "Explore common use cases for custom communication flows in Agency Swarm."
icon: "code"
---

In the following sections, we'll look at some common use cases for creating custom communication flows and how to implement them in Agency Swarm.

#### 1. Adjusting Parameters and Descriptions

Customize parameters by subclassing `SendMessage` and declaring extra fields directly on the class:

```python
from pydantic import Field
from agency_swarm import SendMessage

class SendMessageTask(SendMessage):
    """Use this tool to send tasks to other agents within your agency."""

    tool_name = "send_message_task"  # optional, defaults to "send_message"

    task: str = Field(
        description=(
            "Specify the task required for the recipient agent to complete. Focus on "
            "clarifying what the task entails rather than providing exact instructions."
        )
    )
```

#### 2. Adding Additional Fields

You can add extra fields to capture more context, like key moments and decisions:

```python
from pydantic import Field
from agency_swarm import SendMessage

class SendMessageWithContext(SendMessage):
    """SendMessage with key moments and decisions tracking."""

    tool_name = "send_message_with_context"

    key_moments: str = Field(
        description=(
            "Document critical moments and decision points from the current conversation "
            "that the recipient agent needs to understand. Include context about what "
            "has been decided or prioritized that will guide the recipient's tool selection "
            "and task execution. For example: 'User decided to prioritize performance over cost', "
            "'Analysis focus shifted to Q4 optimization', etc."
        )
    )
    decisions: str = Field(
        description=(
            "Summarize the specific decisions made that will directly impact which tools "
            "or approaches the recipient agent should use. Be explicit about choices that "
            "narrow down the scope of work. For example: 'Prioritized performance analysis "
            "over cost reduction', 'Selected React over Vue for frontend', etc. This helps "
            "the recipient agent choose the most appropriate tools and approach."
        )
    )
```

**Usage:**

```python
from agency_swarm import Agency, Agent

agent = Agent(
    name="MyAgent",
    instructions="You are a helpful assistant.",
)

other_agent = Agent(name="OtherAgent", instructions="Provide supporting context.")

agency = Agency(
    agent,
    other_agent,
    communication_flows=[(agent > other_agent, SendMessageWithContext)],
)
```

<Tip title="Contributing">
  If you have any ideas for new communication flows, please either adjust this page in docs, or add your new send
  message tool in the `agency_swarm/tools/send_message` folder and open a PR!
</Tip>