deepagent

Create configurable DeepAgents with tools for LangChain and LangGraph workflows.

Updated Dec 22, 2025

Search Tags:#integration #langchain #tooling #agent #LLM #tools #deepagent

Ready to run

npx skills add https://github.com/htooayelwinict/claude-config --skill deepagent-htooayelwinict

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: deepagent
Source: https://github.com/htooayelwinict/claude-config/tree/main/skills/deepagent
Command: npx skills add https://github.com/htooayelwinict/claude-config --skill deepagent-htooayelwinict

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill offers expert guidance for using the DeepAgents framework to create capable AI agents with tool integration and cross-framework compatibility.

Core Features & Use Cases

Creating DeepAgents with customizable models and system prompts.
Defining and binding tools to agents for extended capabilities.
Demonstrating integration with LangChain and LangGraph workflows.

Quick Start

Create a basic DeepAgent with a few tools and invoke it with a simple user message.

Frequently Asked Questions about deepagent

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I build an AI agent with tool integration in LangChain?▼

DeepAgents let you build configurable AI agents with integrated tools within LangChain workflows. You instantiate a DeepAgent with a model, attach tool functions via decorators or modules, and invoke it with user messages. This enables agents to call tools dynamically and return results directly in your LangChain pipelines.

Can I use DeepAgents with LangGraph for complex agent workflows?▼

Yes. DeepAgents integrate with LangGraph for building sophisticated multi-step agent workflows. You define tools and attach them to your agent, then compose the agent into LangGraph state machines. This supports streaming, async invocation, and orchestration across code, research, and admin tasks.

What's the best way to attach tools to an LLM agent?▼

DeepAgents support two patterns: decorated functions and module-based tools. Define tool functions with decorators that describe their purpose and parameters, or import tool modules and bind them to your agent instance. Both methods register tools for the agent to discover and invoke automatically.

How do I invoke a DeepAgent and stream responses?▼

DeepAgents expose multiple invocation patterns: invoke for synchronous calls, stream for iterative response output, and astream for async streaming. Pass a user message to any method and the agent executes tools as needed, returning results incrementally or as a complete response.

Do DeepAgents work with custom language models?▼

DeepAgents accept customizable models and system prompts, so you can swap in your preferred LLM provider or fine-tuned model. Instantiate the agent with your model instance and configure the system prompt to shape the agent's behavior and reasoning style.

What safety and testing patterns should I follow with tool-augmented agents?▼

DeepAgents documentation covers best practices for logging tool invocations, validating tool outputs, and testing agent behavior. Implement input validation on tools, monitor execution logs, and use unit tests to verify tool registration and agent responses under known inputs.