# Prebuilt Agents and Tools

> Ready-made 10xGraph graph patterns, common tools, and handoff helpers.

Source: https://10xgraph.com/docs/concepts/prebuilt-agents-and-tools
Last updated: 2026-07-21

10xGraph includes prebuilt building blocks for common agent patterns. Use them when the default shape matches your workflow, and drop down to `StateGraph`, `Agent`, and `ToolNode` when you need custom control.

## Prebuilt agents

Prebuilt agents live in `tenxgraph.prebuilt.agent`.

| Agent | Use case |
|---|---|
| `ReactAgent` | Standard model and tool loop. |
| `RAGAgent` | Retrieval-augmented generation with retriever and synthesis steps. |
| `PlanActReflectAgent` | Plan, execute, and critique across multiple passes. |
| `StructuredOutputAgent` | Constrain the final answer to a schema. |
| `SupervisorTeamAgent` | A supervisor routes work to named workers (`WorkerConfig`). |
| `SwarmAgent` | Peer agents hand control to each other (`SwarmMemberConfig`). |
| `AudioAgent` | Realtime audio-to-audio sessions over a live provider socket. |

Reranker base classes ship alongside the RAG agent:

| Class | Use case |
|---|---|
| `BaseReranker` | Interface for custom reranking of retrieved documents. |
| `CohereReranker` | Rerank with the Cohere Rerank API. |
| `CrossEncoderReranker` | Rerank with a local cross-encoder model. |

Everything above except `AudioAgent` is also re-exported from `tenxgraph.prebuilt`. `AudioAgent` must be imported from `tenxgraph.prebuilt.agent`:

```python
from tenxgraph.prebuilt.agent import AudioAgent
from tenxgraph.prebuilt import ReactAgent, SupervisorTeamAgent, SwarmAgent
```

## Prebuilt tools

Common tools are exported from `tenxgraph.prebuilt.tools`.

| Tool | Use case |
|---|---|
| `safe_calculator` | Evaluate simple math expressions safely. |
| `fetch_url` | Fetch web content from a URL. |
| `file_read`, `file_write`, `file_search` | Work with files where enabled. |
| `google_web_search`, `vertex_ai_search` | Search integrations. |
| `memory_tool`, `make_user_memory_tool`, `make_agent_memory_tool` | Store or retrieve long-term memory. |
| `create_handoff_tool`, `is_handoff_tool` | Transfer control between graph agents. |

## Handoff tools

Handoff tools let the model transfer execution to another graph node by calling a tool with the `transfer_to_<agent>` convention.

```python
from tenxgraph.prebuilt.tools import create_handoff_tool
from tenxgraph.core import ToolNode

tools = ToolNode([
    create_handoff_tool(
        agent_name="RESEARCHER",
        description="Transfer to the research agent.",
    ),
])
```

Use handoff tools for agent-to-agent delegation. Use `Command(goto=...)` when routing should be explicit code rather than an LLM tool choice.

## Rules

| Rule | Why it matters |
|---|---|
| Prefer prebuilt agents for common patterns | They encode the standard 10xGraph graph shape. |
| Keep handoff targets aligned with node names | The graph jumps to the target node. |
| Use tools for capabilities, not routing policy | Routing policy often belongs in graph edges or `Command`. |
| Check reference docs for constructor details | Prebuilt surfaces evolve as new patterns stabilize. |

## Related docs

- [Agents and tools](/docs/concepts/agents-and-tools)
- [Callbacks and Command](/docs/concepts/callbacks-and-command)
- [Command and handoff reference](/docs/reference/python/command-handoff)