neb-handoff

Coordinate task handoffs between operators and AI agents in NebCore.

Updated Aug 23, 2026

Search Tags:#automation #workflow #handoff #issues #ai-agent #task-management #operator

Ready to run

npx skills add https://github.com/nebinfra/nebcore-ai-skills --skill neb-handoff

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: neb-handoff
Source: https://github.com/nebinfra/nebcore-ai-skills/tree/main/neb-handoff
Command: npx skills add https://github.com/nebinfra/nebcore-ai-skills --skill neb-handoff

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Transfers task ownership between the operator and an AI agent, preserving context and enabling reliable take-over or hand-off.

Core Features & Use Cases

Bidirectional handoffs between a human operator and an AI agent to maintain continuity.
Context preservation through issue details, descriptions, and recent activity to inform decisions.
Session-state management and auditable comments to track handoff history.

Quick Start

Describe the desired handoff scenario to begin.

Frequently Asked Questions about neb-handoff

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

FAQPage Schema

How do I automate task handoffs between operators and AI agents?▼

Preserve context during AI agent handoffs by maintaining a structured final state that includes issue id, title, status, assignee, description, and recent activity. This contextual data informs decisions and tracks handoff history through auditable comments.

What is the best way to manage session state when an AI agent takes over a task?▼

Manage session state during an AI agent take over by applying contextual prompts and tracking handoff history with auditable comments. This maintains continuity across issue tracking, commentary, and task reassignment workflows within the platform.

How does an operator hand off an issue to an AI agent without losing context?▼

An operator hands off an issue to an AI agent by transferring ownership with a structured final state including issue details and recent activity. This preserves context and enables reliable continuity through safe, auditable API interactions.

What context is needed to reassign a task from an AI agent back to an operator?▼

Reassigning a task from an AI agent back to an operator requires a structured final state including issue id, title, status, assignee, description, and recent activity. This contextual data ensures the operator can resume work without losing continuity.

Are there limitations when using automated handoffs for issue tracking workflows?▼

Automated handoffs for issue tracking require structured final state data and safe, auditable API interactions with error handling. Limitations arise if recent activity or issue descriptions are missing, which breaks context preservation and session-state management.