handover

Generate structured handover prompts for multi-phase project state between chat sessions.

Updated Apr 17, 2026
One-click install
npx skills add https://github.com/xinye1/xl-skills --skill handover-xinye1
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: handover
Source: https://github.com/xinye1/xl-skills/tree/main/skills/handover
Command: npx skills add https://github.com/xinye1/xl-skills --skill handover-xinye1

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill solves the issue of context degradation in long-running AI-assisted projects by providing a structured, self-contained bridge that allows you to move from a full, cluttered chat to a fresh, clean one without losing progress or momentum.

Core Features & Use Cases

  • Context Preservation: Generates a comprehensive handover prompt that captures plan status, verification evidence, and pending tasks.
  • Orchestration Alignment: Automatically selects the optimal model tier (Sonnet, Opus, or Fable) based on the phase's complexity and requirements.
  • Use Case: When you are mid-way through a complex multi-phase refactor and the current chat context is becoming sluggish or hitting token limits, use this skill to generate a handover prompt that ensures the next chat starts with perfect clarity on what has been achieved and what remains.

Quick Start

Run the handover skill to generate a prompt for continuing your current multi-phase project in a new chat session.

Frequently Asked Questions about handover

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

FAQPage Schema
How do I preserve project context when moving a multi-phase workflow to a new chat session?

To preserve project context across chat sessions, you can generate a structured handover prompt that captures plan status, verification evidence, and pending tasks before transitioning to a fresh chat.

What is the best way to manage context degradation in long-running AI-assisted projects?

Managing context degradation requires a structured bridge between sessions, allowing you to move from a cluttered chat to a clean one by transferring persistent project memory and verified exit criteria.

How does model-specific orchestration work for multi-phase software development?

Model-specific orchestration automatically selects the optimal model tier, such as Sonnet, Opus, or Fable, based on the phase's complexity and requirements to ensure consistent task delegation.

Can I use handover prompts for long-horizon refactoring tasks hitting token limits?

Yes, when a complex multi-phase refactor becomes sluggish or hits token limits, generating a handover prompt ensures the next chat starts with perfect clarity on achieved milestones and remaining work.

What information is included in a structured handover prompt for project transitions?

A structured handover prompt includes comprehensive details on plan status, verification evidence, and pending tasks to satisfy requirements for persistent project memory and consistent task delegation.

When should I transition my project state between independent chat sessions?

You should transition project state between chat sessions when context degradation occurs, requiring context hygiene and verified exit criteria to maintain momentum in long-horizon workflows.