deep-agents-core

To build an AI agent with multi-step task capabilities, use the Deep Agents framework to configure custom tools, middleware, and context management. This Skill provides Python and TypeScript code examples for creating agents that can plan, delegate, and execute complex workflows.

Middleware in an AI agent framework provides built-in modules for planning, file management, and task delegation. It allows you to intercept and modify agent behavior between steps, enabling complex context management and multi-step task execution without writing custom logic.

Yes, Deep Agents supports tool integration within your AI agent setup. The framework provides configuration options to attach custom tools to your agents, allowing you to extend their capabilities for specific use cases like research, summarization, and drafting.

Task delegation in a deep agent is configured using the framework's built-in middleware. By integrating the delegation middleware, your agent can assign subtasks to other agents or tools, manage the context, and compile the results into a final output.

Yes, the Deep Agents framework supports both Python and TypeScript. The Skill provides code examples and configuration guidance for both languages, allowing you to create and invoke agents with custom tools in your preferred development environment.

The best way to set up an AI agent for research and drafting is to use the Deep Agents framework with planning and file management middleware. This configuration allows the agent to research a topic, summarize findings, and draft an email through multi-step task execution.