Agent Handoff
Agent handoff is the controlled transfer of a task — with its context — from one agent to another agent or to a human.
/ quick answer
A handoff passes control plus a context package (goal, work done, open questions, constraints) to the next actor. Good handoffs are explicit contracts: the receiving agent gets a structured payload, not a raw transcript. Handoff failures are the single most common cause of quality loss in multi-agent systems.
/ frequently asked
What is Agent Handoff?
A handoff passes control plus a context package (goal, work done, open questions, constraints) to the next actor. Good handoffs are explicit contracts: the receiving agent gets a structured payload, not a raw transcript. Handoff failures are the single most common cause of quality loss in multi-agent systems.
What is an example of Agent Handoff?
A triage agent classifies a ticket as 'billing', writes a 5-field summary, and hands off to the billing agent, which never sees the full chat history.
Why does Agent Handoff matter?
Agent handoff is the controlled transfer of a task — with its context — from one agent to another agent or to a human.
What should I learn after Agent Handoff?
Open the related workflows and prompts further down this page: they show how this idea is applied in a real task, step by step.
/ continue exploring
Related concepts
The vocabulary this page depends on.
- →Multi-Agent System
A multi-agent system splits a job across several specialised AI agents that coordinate through a shared plan, message bus or orchestrator.
- →Agent-to-Agent Protocol (A2A)
An Agent-to-Agent (A2A) protocol defines the communication standards and rules that enable autonomous AI agents to interact and exchange information or services directly with each other without human intervention. This foundational concept is crucial for building complex, collaborative multi-agent systems.
- →AI Orchestration
Coordinating multiple AI models, tools and steps into a single reliable workflow.
- →Agent Architecture
Agent architecture is the structural blueprint of an AI agent: the model, the planning loop, the tools, the memory layer and the guardrails that decide how it acts.
Related workflows
Turn this into a repeatable process.
- →Build a Multi-Agent Content Team
Researcher, writer and editor agents under a supervisor, producing publishable drafts.
- →Design Agent-to-Human Escalation
A handoff contract that gives humans everything they need in one screen.
- →Automate Agent Task Delegation
This workflow automates the process of an initiating AI agent delegating a complex task to a specialized recipient AI agent using a standardized Agent-to-Agent (A2A) protocol, ensuring efficient task handoff and execution. It streamlines multi-agent collaboration for defined objectives.
- →Ship an Autonomous Workflow Safely
Move an automation from human-triggered to autonomous without losing control.
Related tool stacks
The tools that run it in production.
- →Multi-Agent Orchestration Stack
Tooling for coordinating several specialised agents with reliable handoffs.
- →Agent Architecture Stack
The minimum tooling to design, run and observe a production agent.
- →AI Agent + Web3 Stack
Agent framework, MCP/API tools, blockchain data access and a limited signing layer — with policy enforced in code.
- →A2A Orchestration Stack
This stack comprises the essential tools and frameworks for designing, deploying, and managing Agent-to-Agent (A2A) communication protocols and multi-agent system orchestration. It provides the infrastructure for complex AI agent collaboration.
Related prompts
Reusable prompts for this job.
- →Multi-Agent Role Definition Prompt
Generates crisp role prompts and handoff contracts for a team of agents.
- →Agent Architecture Spec Prompt
Turns a fuzzy agent idea into a reviewable five-layer architecture spec.
- →Crypto Agent Design Prompt
Specifies an AI crypto agent's tools, permissions, guardrails and evaluation before a single line is written.
- →Wallet Monitoring Agent Prompt
System prompt for a read-only agent that watches addresses, filters noise and reports only decision-relevant activity.
Related use cases
How people apply it, and what came out.
- →SaaS Cuts First-Response Time from 6h to 4min with an Agent
A 12-person SaaS shipped a tier-1 support agent and kept humans on exceptions only.
- →Ecommerce Team Runs a Multi-Agent Catalog Pipeline
Three agents enrich, write and QA 12,000 product listings.
- →Build An AI Crypto Research Agent
A read-only research agent produced daily briefings on a 30-token watchlist, cutting a 90-minute manual routine to a 10-minute review.
Comparisons & alternatives
Pick between the options.
- →Single Agent vs Multi-Agent System
One well-equipped agent beats a crowd for most jobs; multi-agent wins on genuinely separable, parallel work.
- →AI Agent vs Trading Bot
A trading bot executes fixed rules deterministically; an AI agent interprets context and decides which steps to take — powerful for research, risky for execution.