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session-handover

Generate a structured handoff document capturing session state, blockers, and decisions.

Updated Jan 10, 2026
Search Tags:#documentation#context#memory#handoff#traceability#session#ai-workflow
One-click install
npx skills add https://github.com/serguei9090/Agentic-Governance-Framework --skill session-handover-serguei9090
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: session-handover
Source: https://github.com/serguei9090/Agentic-Governance-Framework/tree/main/MasterPrompts/.agents/skills/session-handover
Command: npx skills add https://github.com/serguei9090/Agentic-Governance-Framework --skill session-handover-serguei9090

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill ensures continuity by capturing the exact execution state, blockers, and decisions before a session ends, enabling a clean handoff to the next assistant.

Core Features & Use Cases

  • Analyze the current state and recent activity to produce a reliable handoff.
  • Verify task parity by validating completed tasks in docs/track/TODO.md and updating as needed.
  • Generate or update docs/track/handoff.md with a structured summary including Last Action, Current Blockers, Contextual Memory, and Next Atomic Step.
  • Provide a final, concise summary indicating the project state is saved and ready for the next session.

Quick Start

End a session and run the handover to create a new session handoff document for the next AI assistant.

Frequently Asked Questions about session-handover

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

FAQPage Schema
How do I preserve AI session context for a task handoff?▼

To preserve AI session context for a task handoff, you need to generate a structured handoff document capturing execution state, blockers, and decisions before the session ends. This ensures continuity and a clean transition for the next assistant.

What is the best way to manage task traceability across multiple AI assistants?▼

Task traceability across AI assistants is managed by validating completed tasks in TODO.md and updating a structured handoff.md file. This tracks recent activity and provides a deterministic workflow with a concise next-step summary.

How do I document current blockers and memory of decisions before ending an AI workflow?▼

To document blockers and memory of decisions before ending an AI workflow, analyze the current state and generate a handoff document. This file records Last Action, Current Blockers, Contextual Memory, and the Next Atomic Step for future reference.

Do I need specific dependencies to create a session handoff document for my AI workflow?▼

No specific dependencies are required to create a session handoff document for your AI workflow. The process works by analyzing current session activity and writing structured context directly to standard markdown tracking files.

Can I use automated handoffs to maintain a deterministic workflow for ongoing project development?▼

Yes, you can use automated handoffs to maintain a deterministic workflow for project development. Applying a handover at session end verifies task parity and saves the project state, ensuring the next AI assistant resumes work seamlessly.

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