> ## Documentation Index
> Fetch the complete documentation index at: https://langchain-5e9cc07a-preview-devupd-1765394015-eccef47.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Customize Deep Agents

> Learn how to customize deep agents with system prompts, tools, subagents, and more

```mermaid theme={null}
graph LR
    Create[create_deep_agent] --> Core[Core Config]
    Create --> Features[Features]

    Core --> Model[Model]
    Core --> Prompt[System Prompt]
    Core --> Tools[Tools]

    Features --> Backend[Backend]
    Features --> Sub[Subagents]
    Features --> Interrupt[Interrupts]

    Model --> Agent[Customized Agent]
    Prompt --> Agent
    Tools --> Agent
    Backend --> Agent
    Sub --> Agent
    Interrupt --> Agent
```

## Model

By default, `deepagents` uses [`claude-sonnet-4-5-20250929`](https://platform.claude.com/docs/en/about-claude/models/overview). You can customize the model used by passing any supported <Tooltip tip="A string that follows the format `provider:model` (e.g. openai:gpt-5)" cta="See mappings" href="https://reference.langchain.com/python/langchain/models/#langchain.chat_models.init_chat_model(model)">model identifier string</Tooltip> or [LangChain model object](/oss/javascript/integrations/chat).

```typescript theme={null}
import { ChatAnthropic } from "@langchain/anthropic";
import { ChatOpenAI } from "@langchain/openai";
import { createDeepAgent } from "deepagents";

// Using Anthropic
const agent = createDeepAgent({
  model: new ChatAnthropic({
    model: "claude-sonnet-4-20250514",
    temperature: 0,
  }),
});

// Using OpenAI
const agent2 = createDeepAgent({
  model: new ChatOpenAI({
    model: "gpt-5",
    temperature: 0,
  }),
});
```

## System prompt

Deep agents come with a built-in system prompt inspired by Claude Code's system prompt. The default system prompt contains detailed instructions for using the built-in planning tool, file system tools, and subagents.

Each deep agent tailored to a use case should include a custom system prompt specific to that use case.

```typescript theme={null}
import { createDeepAgent } from "deepagents";

const researchInstructions = `You are an expert researcher. Your job is to conduct thorough research, and then write a polished report.`;

const agent = createDeepAgent({
  systemPrompt: researchInstructions,
});
```

## Tools

Just like tool-calling agents, a deep agent gets a set of top level tools that it has access to.

```typescript theme={null}
import { tool } from "langchain";
import { TavilySearch } from "@langchain/tavily";
import { createDeepAgent } from "deepagents";
import { z } from "zod";

const internetSearch = tool(
  async ({
    query,
    maxResults = 5,
    topic = "general",
    includeRawContent = false,
  }: {
    query: string;
    maxResults?: number;
    topic?: "general" | "news" | "finance";
    includeRawContent?: boolean;
  }) => {
    const tavilySearch = new TavilySearch({
      maxResults,
      tavilyApiKey: process.env.TAVILY_API_KEY,
      includeRawContent,
      topic,
    });
    return await tavilySearch._call({ query });
  },
  {
    name: "internet_search",
    description: "Run a web search",
    schema: z.object({
      query: z.string().describe("The search query"),
      maxResults: z.number().optional().default(5),
      topic: z
        .enum(["general", "news", "finance"])
        .optional()
        .default("general"),
      includeRawContent: z.boolean().optional().default(false),
    }),
  },
);

const agent = createDeepAgent({
  tools: [internetSearch],
});
```

In addition to any tools that you provide, deep agents also get access to a number of default tools:

* `write_todos` – Update the agent's to-do list
* `ls` – List all files in the agent's filesystem
* `read_file` – Read a file from the agent's filesystem
* `write_file` – Write a new file in the agent's filesystem
* `edit_file` – Edit an existing file in the agent's filesystem
* `task` – Spawn a subagent to handle a specific task

***

<Callout icon="pen-to-square" iconType="regular">
  [Edit the source of this page on GitHub.](https://github.com/langchain-ai/docs/edit/main/src/oss/deepagents/customization.mdx)
</Callout>

<Tip icon="terminal" iconType="regular">
  [Connect these docs programmatically](/use-these-docs) to Claude, VSCode, and more via MCP for real-time answers.
</Tip>