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Framework Selection

Select between LangChain, LangGraph, and Deep Agents for AI projects.

Updated Feb 24, 2026
Search Tags:#langchain#agent development#langgraph#architecture selection#deep agents#ai framework
One-click install
npx skills add https://github.com/Diploma-pending/test-case --skill framework-selection-diploma-pending
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Framework Selection
Source: https://github.com/Diploma-pending/test-case/tree/main/.agents/skills/framework-selection
Command: npx skills add https://github.com/Diploma-pending/test-case --skill framework-selection-diploma-pending

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps developers select the most appropriate AI framework (LangChain, LangGraph, or Deep Agents) for their project, ensuring efficient development and optimal architecture.

Core Features & Use Cases

  • Framework Guidance: Provides clear decision trees and profiles for LangChain, LangGraph, and Deep Agents.
  • Layered Architecture Explanation: Illustrates how the frameworks build upon each other.
  • Use Case: Before starting a new agent project, consult this skill to determine if a simple LangChain agent, a complex LangGraph workflow, or a feature-rich Deep Agent is the best fit for your requirements.

Quick Start

Use the framework selection skill to determine the best AI framework for a task requiring planning, memory, and on-demand skills.

Frequently Asked Questions about Framework Selection

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

FAQPage Schema
What is the difference between LangChain, LangGraph, and Deep Agents for AI development?▼

LangChain, LangGraph, and Deep Agents form a layered AI framework architecture. LangChain handles simple agents, LangGraph manages complex workflows, and Deep Agents provide feature-rich capabilities for tasks requiring planning and memory.

How do I choose the right AI framework for agent development?▼

To choose the right AI framework, evaluate your task requirements against decision trees. Select LangChain for simple agents, LangGraph for complex workflow orchestration, or Deep Agents for advanced planning and on-demand skills.

When should I use LangGraph instead of LangChain?▼

You should use LangGraph instead of LangChain when your agent project requires complex workflow orchestration. LangChain is suited for simpler agents, while LangGraph builds upon it to manage more intricate stateful operations.

Do I need Deep Agents for a project with planning and memory requirements?▼

Yes, you need Deep Agents for a project with planning and memory requirements. Deep Agents provide the feature-rich foundational architecture necessary to support on-demand skills and complex task execution.

Can I use LangChain for complex agent workflows?▼

LangChain is designed for simpler agent setups rather than complex agent workflows. For complex workflows, selecting LangGraph is recommended because it builds upon LangChain's foundational architecture to handle intricate operations.

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