skills.rest
listentomi
listentomiCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

langgraph

Builds stateful multi-agent AI applications using LangGraph graphs, reducers, and checkpointers.

Updated Aug 28, 2026
Search Tags:#state management#llm#agent#multi-agent#langgraph#stategraph#react agent
One-click install
npx skills add https://github.com/listentomi/Orcajack --skill langgraph-listentomi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langgraph
Source: https://github.com/listentomi/Orcajack/tree/main/skills/science/langgraph
Command: npx skills add https://github.com/listentomi/Orcajack --skill langgraph-listentomi

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires langgraph, langchain-openai, langchain-core.

What problem does it solve? Building production AI agents requires explicit control over state, routing, and persistence, which ad-hoc prompt chains cannot provide. This Skill guides the design of LangGraph-based agents with visible, debuggable graph structures. ## Core Features & Use Cases - Graph Construction: Define StateGraph workflows with nodes, edges, and conditional routing for ReAct-style agents with tool calling. - State Management: Use reducers to append messages, merge findings, and accumulate sources across multiple agents sharing state. - Production Patterns: Apply checkpointers for persistence, human-in-the-loop interrupts, and exit conditions that prevent infinite loops. - Use Case: Build a research assistant where a researcher node accumulates findings and sources in shared state, then a writer node consumes the accumulated state to produce a cited report. ## Quick Start Ask the AI to build a LangGraph ReAct agent with a search tool and a calculator tool that loops until the task is complete.

Frequently Asked Questions about langgraph

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

FAQPage Schema
How do I build a ReAct agent with LangGraph?▼

Define a TypedDict state with an add_messages reducer, bind tools to an LLM, create an agent node and a ToolNode, then add conditional edges that route to tools when tool calls exist and to END otherwise. Compile the StateGraph and invoke it with user messages.

How do reducers work in LangGraph state management?▼

Reducers control how node outputs merge into shared state. Annotated fields like Annotated[list, add_messages] append rather than overwrite, while custom functions can merge dictionaries or sum counters. Nodes return partial updates and LangGraph applies the reducers.

Does LangGraph support persistence and conversation resumption?▼

Yes, LangGraph supports checkpointers that save graph state between steps, enabling conversation resumption and human-in-the-loop interrupts. Without a checkpointer, state exists only for a single invocation.

How do I prevent infinite loops in a LangGraph agent?▼

Add explicit exit conditions in your routing function, such as an iteration counter in state that returns END after a maximum number of steps, or a task_complete flag. Application-level timeouts provide an additional safeguard.

What are the limitations of LangGraph?▼

LangGraph is primarily Python-only, with TypeScript support in early stages. It has a learning curve for graph concepts, state management adds complexity, and debugging cyclic graphs can be challenging.

Related Skills

Explore More Software Engineering Skills→
IbIFACE-TechIbIFACE-Tech

provider-integration

Configure and switch between multiple LLM providers like OpenAI, Anthropic, Azure, and Ollama.

Official
Intermediate
aurumorincaurumorinc

langfuse

Configure Langfuse trace trees, score metrics, and prompt versioning for AI agent workflows.

Official
Advanced
krzysztofsurdykrzysztofsurdy
20

langchain-components

Reference LangChain components for building agents, RAG pipelines, and LangGraph workflows.

Community
Advanced
LKB-99LKB-99

ai-agents-builder

Automate creation and orchestration of AI agents with LangChain, AutoGPT, and CrewAI.

Community
Advanced