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framework-selection

Select LangChain, LangGraph, or Deep Agents for AI project kickoff.

Updated May 29, 2026
Search Tags:#architecture#langchain#langgraph#startup#decision-making#framework-selection#deep-agents
One-click install
npx skills add https://github.com/patorn/langgraph-template --skill framework-selection-patorn
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: framework-selection
Source: https://github.com/patorn/langgraph-template/tree/main/.agents/skills/framework-selection
Command: npx skills add https://github.com/patorn/langgraph-template --skill framework-selection-patorn

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Helps teams decide which framework layer to use at the start of a LangGraph/AI project (LangChain, LangGraph, or Deep Agents), ensuring the right foundation before coding.

Core Features & Use Cases

  • Structured decision guidance to evaluate task needs and point to the most suitable framework.
  • Comprehensive framework profiles that clarify when to use LangChain, LangGraph, or Deep Agents, and how they can be combined.
  • Mixing guidance for multi-layer projects, including how to integrate LangGraph graphs within Deep Agents workflows.

Quick Start

Run this at the start of a project to select the most suitable framework layer based on task characteristics.

Frequently Asked Questions about framework-selection

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

FAQPage Schema
How do I choose between LangChain and LangGraph for a new AI project?▼

Framework selection depends on task complexity: LangChain suits simple chains, while LangGraph handles complex, stateful workflows. This skill provides a decision table to evaluate your project needs and map them to the correct LangChain, LangGraph, or Deep Agents layer before coding.

When should I use Deep Agents instead of LangGraph for workflow architecture?▼

Use Deep Agents instead of LangGraph when your architecture requires autonomous orchestration rather than granular graph control. This skill provides framework profiles to help determine if Deep Agents fits your specific task scenarios better than lower-level LangGraph workflows.

Can I mix LangGraph workflows within a Deep Agents project?▼

Yes, you can mix frameworks in multi-layer projects. This skill provides mix-and-match guidance explaining how to integrate LangGraph graphs directly within Deep Agents workflows to build a combined, cohesive architecture.

What is the best way to bootstrap an AI startup architecture decision?▼

Run this skill at project kickoff to bootstrap your AI startup architecture decision. It provides a concise quick-start instruction and decision table to evaluate task characteristics, ensuring you select the optimal LangChain, LangGraph, or Deep Agents foundation.

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