Customize Deep Agents

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

Model

By default, deepagents uses claude-sonnet-4-5-20250929. You can customize the model used by passing any supported model identifier string or LangChain model object.

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.

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.

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

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