handoff-skill

Name: handoff-skill
Availability: InStock
Author: eric

Transfer tasks between AI agents using an email-inspired protocol.

Updated Jan 20, 2026

Search Tags:#workflow #context management #agent communication #handoff #inter-agent #task transfer

Ready to run

npx skills add https://github.com/maxoreric/sop-engine --skill handoff-skill

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: handoff-skill
Source: https://github.com/maxoreric/sop-engine/tree/main/%24workflow.input.user_intent/skills/handoff-skill
Command: npx skills add https://github.com/maxoreric/sop-engine --skill handoff-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenge of transferring tasks and context between different AI agents, ensuring a smooth and structured workflow.

Core Features & Use Cases

Structured Task Transfer: Implements an email-protocol-like system for passing tasks.
Context Preservation: Ensures all necessary information (inputs, task description, history) is passed along.
Status Tracking: Manages task states (pending, in_progress, completed, failed) for visibility.
Use Case: A 'research-agent' completes its data gathering and needs to hand off the findings to a 'writer-agent' to generate a report. The handoff-skill facilitates this transfer with all relevant research data attached.

Quick Start

Use the handoff skill to transfer the current task to the writer-agent with the subject 'Draft initial report'.

Frequently Asked Questions about handoff-skill

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

FAQPage Schema

How do I transfer tasks and context between AI agents without losing data?▼

Inter-agent task handover solves this by using a structured, email-inspired protocol to manage task context, inputs, outputs, and status tracking across agent boundaries. This ensures all necessary information is passed along seamlessly during the transfer.

What is the best way to track task status when chaining multiple AI agents together?▼

Task status tracking across agent boundaries is managed by assigning states like pending, in_progress, completed, or failed. The handoff protocol supports task chaining through reference IDs, providing full traceability and visibility for chained agent workflows.

How does the email-inspired protocol work for agent communication?▼

The email-inspired protocol facilitates agent communication by structuring task transfers like an email. It packages the task description, historical context, and inputs into a managed format, passing the complete workload to the next agent in the workflow chain.

Can I use this structured task transfer approach for a research-to-writing agent workflow?▼

Yes, structured task transfer is designed for workflows like a research-agent handing off findings to a writer-agent. The protocol attaches all relevant research data, task inputs, and history, allowing the writer-agent to generate a report with full context.

Do I need any specific frameworks to implement inter-agent task handover?▼

No specific frameworks are required as dependencies for implementing inter-agent task handover. The protocol operates independently to structure context management and task transfer, relying on reference IDs for traceability rather than external platform constraints.