framework-selection

Select the optimal framework layer for LangChain, LangGraph, or Deep Agents projects.

3|1|Updated Jun 4, 2025
One-click install
npx skills add https://github.com/jillesca/sp_oncall --skill framework-selection-jillesca
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: framework-selection
Source: https://github.com/jillesca/sp_oncall/tree/main/.agents/skills/framework-selection
Command: npx skills add https://github.com/jillesca/sp_oncall --skill framework-selection-jillesca

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Determines the most suitable AI framework layer (LangChain, LangGraph, or Deep Agents) at the project start to avoid misalignment and costly rework.

Core Features & Use Cases

  • Provides a concise decision guide to pick the right framework based on control flow, memory, and orchestration needs.
  • Includes framework profiles and mixing guidance to enable safe layering choices across LangChain, LangGraph, and Deep Agents.
  • Guides early architecture decisions for multi-layer AI agent projects and facilitates smooth onboarding for new teams with consistent tooling.

Quick Start

Load this skill at the start of any LangChain/LangGraph/Deep Agents project to choose the optimal framework path before coding.

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, LangGraph, and Deep Agents for my project?▼

Choosing between LangChain, LangGraph, and Deep Agents depends on your project's control flow, memory persistence, and multi-layer orchestration needs. This framework-selection process evaluates these requirements to specify the optimal architecture layer before coding begins.

What is the best way to avoid AI framework misalignment early in an architecture project?▼

The best way to avoid AI framework misalignment is applying framework-selection at the project start. It provides a concise decision guide and framework profiles to determine the suitable layer, preventing costly rework and ensuring consistent tooling for new teams.

Can I safely mix LangChain and LangGraph layers in the same multi-layer AI agent project?▼

Yes, you can safely mix LangChain and LangGraph layers. The framework-selection guidance includes specific mixing rules and profiles to enable safe layering choices across LangChain, LangGraph, and Deep Agents within multi-layer AI agent projects.

When do I need Deep Agents instead of LangChain for control flow and orchestration?▼

You need Deep Agents instead of LangChain when your project requires complex multi-layer orchestration and advanced control flow beyond basic chains. The selection process maps your specific memory and orchestration needs to the correct framework profile.

Does the framework-selection skill require any specific project dependencies to work?▼

No specific project dependencies are required. The skill functions as a decision guide loaded at the start of LangChain, LangGraph, or Deep Agents projects, requiring only a SKILL.md file with YAML frontmatter containing name and description.