Can I implement human-in-the-loop workflows?

Absolutely. The skill includes patterns for implementing interrupts, state editing, and manual approval steps within your agentic graphs.

Does this skill support both Python and TypeScript?

Yes, it provides comprehensive implementation patterns and quick-start examples for both the Python (langgraph) and TypeScript (@langchain/langgraph) ecosystems.

What kind of persistence options are covered?

It covers a range of persistence options from in-memory MemorySaver for development to production-ready SQLite and PostgreSQL checkpointers.

Does it help with multi-agent orchestration?

Yes, it provides specific guidance on supervisor patterns, hierarchical agent teams, and conditional routing between different specialized nodes.

Is this compatible with the LangGraph Platform?

Yes, it includes instructions for LangGraph CLI commands and environment configuration for deploying to the LangGraph Platform.

LangGraph Agent Builder

Name: LangGraph Agent Builder
Author: FortiumPartners

byFortiumPartners

Data Science & ML

Builds sophisticated, stateful multi-agent workflows and cyclic AI graphs using LangGraph for complex orchestration.

About

This skill empowers developers to architect and implement production-grade agentic systems using LangGraph's stateful graph framework. It provides expert guidance on creating cyclic workflows, managing persistent state with checkpointers, and implementing complex routing logic for both Python and TypeScript environments. Whether you are building a simple ReAct agent or a hierarchical multi-agent system with human-in-the-loop capabilities, this skill streamlines the development process with standardized patterns, best practices, and multi-actor orchestration techniques.

Key Features

Cross-platform support for Python and TypeScript ecosystems
Complex multi-agent coordination and conditional routing patterns
0 GitHub stars
Stateful graph orchestration using StateGraph and MessageGraph
Human-in-the-loop workflow implementation with interrupts
Persistent state management with SQLite and PostgreSQL checkpointers

Use Cases

Building enterprise chatbots with long-term memory and persistent conversation threads
Creating research agents that require cyclic reasoning and iterative tool usage
Developing multi-agent systems where a supervisor orchestrates specialized worker nodes

About

Key Features

Cross-platform support for Python and TypeScript ecosystems
Complex multi-agent coordination and conditional routing patterns
0 GitHub stars
Stateful graph orchestration using StateGraph and MessageGraph
Human-in-the-loop workflow implementation with interrupts
Persistent state management with SQLite and PostgreSQL checkpointers

Use Cases

Building enterprise chatbots with long-term memory and persistent conversation threads
Creating research agents that require cyclic reasoning and iterative tool usage
Developing multi-agent systems where a supervisor orchestrates specialized worker nodes