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LangGraph Execution Control

Manage LangGraph execution flows with Send API parallel tasks, interrupts, and streaming.

1.1k|86|Updated Jan 22, 2026
Search Tags:#workflow#parallel execution#agent#streaming#orchestration#langgraph#interrupt
One-click install
npx skills add https://github.com/langchain-ai/langchain-skills --skill langgraph-execution-control
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: LangGraph Execution Control
Source: https://github.com/langchain-ai/langchain-skills/tree/main/config/skills/langgraph-execution
Command: npx skills add https://github.com/langchain-ai/langchain-skills --skill langgraph-execution-control

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides advanced control over LangGraph workflows, enabling parallel execution, human-in-the-loop interruptions, and real-time data streaming for complex agent orchestration.

Core Features & Use Cases

  • Workflow vs. Agent: Differentiate between predetermined paths and dynamic, model-driven decision-making.
  • Send API: Facilitate fan-out to parallel workers for map-reduce operations.
  • Interrupts: Implement human-in-the-loop pauses for review and decision-making, resuming execution with Command.
  • Streaming: Configure real-time output of state, tokens, or custom data for dynamic UIs and monitoring.

Quick Start

Use the LangGraph Execution Control skill to fan out tasks to parallel workers and aggregate their results.

Frequently Asked Questions about LangGraph Execution Control

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

FAQPage Schema
How do I execute parallel tasks in a LangGraph workflow?▼

Implement human-in-the-loop interruptions in LangGraph by pausing execution for human review, then resuming the workflow dynamically using the Command function to proceed with interactive agent behavior.

Can I stream real-time state and token updates from LangGraph agents?▼

Configure streaming modes in LangGraph to output custom data alongside state and tokens, enabling real-time feedback for dynamic user interfaces and continuous workflow monitoring.

What is the difference between a workflow and an agent in LangGraph?▼

LangGraph differentiates workflows with predetermined paths from agents using dynamic, model-driven decision-making, providing specialized control for complex orchestration scenarios.

How do I implement human-in-the-loop interruptions for agent review?▼

You can execute parallel tasks in a LangGraph workflow by using the Send API to fan out operations to multiple workers, enabling efficient map-reduce orchestration and dynamic task distribution.

How do I handle fault tolerance during complex agent orchestration?▼

Ensure fault tolerance in agent orchestration by utilizing LangGraph execution controls to manage parallel task distribution and human-in-the-loop interruptions, preventing workflow failures.

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