langgraph-human-in-the-loop

Pauses and resumes LangGraph execution for user approval and validation.

2|Updated Mar 7, 2026
One-click install
npx skills add https://github.com/Lincyaw/AgentM --skill langgraph-human-in-the-loop-lincyaw
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: langgraph-human-in-the-loop
Source: https://github.com/Lincyaw/AgentM/tree/main/.claude/skills/langgraph-human-in-the-loop
Command: npx skills add https://github.com/Lincyaw/AgentM --skill langgraph-human-in-the-loop-lincyaw

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill enables seamless integration of human decision-making and feedback into automated AI workflows, allowing for approvals, validation, and error correction at critical junctures.

Core Features & Use Cases

  • Pause and Resume Execution: Halt graph execution to surface information or requests to a human and resume based on their input.
  • Approval Workflows: Implement systems where human approval is required before proceeding with an action (e.g., sending an email, making a financial transaction).
  • Data Validation Loops: Continuously prompt a user for input until valid data is provided.
  • Error Handling: Use interrupts as a mechanism for user-driven error resolution.
  • Use Case: An AI agent drafting an important email can pause execution, present the draft to a manager for review and edits, and then resume to send the finalized email only after approval.

Quick Start

Use the langgraph-human-in-the-loop skill to pause execution and ask for user approval on a draft response.

Frequently Asked Questions about langgraph-human-in-the-loop

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

FAQPage Schema
How do I pause LangGraph execution to ask for user approval before proceeding?

You can pause LangGraph execution for user approval by using the interrupt() function to halt the graph, then resuming it with Command(resume=...) once the user provides their validated input.

What is the best way to handle user-fixable errors in an AI workflow?

The best way to handle user-fixable errors in an AI workflow is using interrupts to pause graph execution, allowing human users to resolve the error and resume the process with corrected inputs.

How does LangGraph manage paused states during a human-in-the-loop process?

LangGraph manages paused states during a human-in-the-loop process by utilizing checkpointers and thread IDs to track execution state, ensuring JSON-serializable payloads for interrupt values.

Can I continuously prompt a user for input until valid data is provided in LangGraph?

Yes, you can implement data validation loops in LangGraph by pausing execution with interrupt() and repeatedly prompting the user until valid, JSON-serializable data is provided to resume the graph.

Do I need to ensure idempotent operations before using interrupts in LangGraph?

Yes, you need to ensure idempotent operations before triggering interrupts in LangGraph, as this prevents duplicate side effects when graph execution pauses for human feedback and resumes later.