mpi-handoff

Generate a structured JSON handoff document from current MPI session state.

1|Updated May 13, 2026

Search Tags:#workflow #planning #resume #coordination #handoff #state-tracking #mpi

Ready to run

npx skills add https://github.com/MadPonyInteractive/mpi-kanban --skill mpi-handoff

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: mpi-handoff
Source: https://github.com/MadPonyInteractive/mpi-kanban/tree/main/skills/mpi-handoff
Command: npx skills add https://github.com/MadPonyInteractive/mpi-kanban --skill mpi-handoff

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

MPI handoffs preserve current work and provide a canonical, resumeable handoff document so a fresh session can resume with mpi-continue.

Core Features & Use Cases

Collects and anchors current plan and task state from the active MPI session.
Generates a structured JSON handoff that can be loaded by a new session to pick up where the previous one left off.
Produces lightweight pointers for task workspaces and references to relevant plan files.

Quick Start

Invoke mpi-handoff to generate a structured handoff document from the current plan and session state.

Frequently Asked Questions about mpi-handoff

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

FAQPage Schema

How do I preserve MPI session state when context gets too large?▼

To preserve MPI session state when context gets large, you generate a structured handoff document that anchors current plan and task state. This enables seamless resumption in a fresh session.

What is a structured handoff document for workflow coordination?▼

A structured handoff document for workflow coordination is a canonical JSON file containing required state fields and pointer files. It captures active plan and task context so work can be seamlessly resumed across sessions.

When do I need to generate a handoff document for MPI planning?▼

You need to generate a handoff document for MPI planning when a plan phase completes or the active session context grows too large. This triggers state collection to prepare for a fresh session.

How do I resume work in a new session after a plan phase completes?▼

To resume work in a new session after a plan phase completes, load the canonical handoff JSON generated from the previous session. This provides the exact plan and task context needed to continue.

Does the MPI handoff process require any specific dependencies or components?▼

The MPI handoff process requires no external dependencies or components. It operates independently to collect active session state and produce lightweight pointers to relevant plan files.

What is the best way to track task state across multiple MPI sessions?▼

The best way to track task state across multiple MPI sessions is generating a canonical handoff JSON with structured state tracking. This ensures lightweight pointers and plan references are preserved for resumption.