auto-continuation

Spawn context-preserving agents to continue tasks exceeding a single context window.

Updated Mar 15, 2026

Search Tags:#workflow #orchestration #multi-step #continuation #ai-agents #state-preservation

Ready to run

npx skills add https://github.com/JNZader/javi-ai --skill auto-continuation

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: auto-continuation
Source: https://github.com/JNZader/javi-ai/tree/main/own/skills/auto-continuation
Command: npx skills add https://github.com/JNZader/javi-ai --skill auto-continuation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Enables AI to spawn continuation agents with preserved state to handle tasks that exceed a single context window.

Core Features & Use Cases

Continuation orchestration: spawn subsequent agents with preserved task context and progress tracking.
Handoff and state preservation: capture essential decisions, inputs, and outputs to resume work seamlessly.
Use Case: Automate multi-phase research tasks or large codebase refactors that exceed a single context window.

Quick Start

Provide a task description and initiate the continuation workflow to begin processing.

Frequently Asked Questions about auto-continuation

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

FAQPage Schema

How do I coordinate multi-agent continuations for tasks that exceed a single context window?▼

Multi-agent continuations are coordinated by spawning context-preserving agents to tackle tasks exceeding a single context window. The system captures essential decisions, inputs, and outputs to resume work seamlessly.

What is context preservation in AI workflow orchestration?▼

Context preservation in AI workflow orchestration is the process of capturing essential decisions, inputs, and outputs during task handoffs. This state preservation allows subsequent agents to resume work seamlessly without losing prior progress.

How do I automate large codebase refactors that exceed a single context window?▼

Automating large codebase refactors requires initiating a continuation workflow with a task description. This spawns subsequent agents with preserved task context and progress tracking to handle the multi-file development process.

Can I use continuation orchestration for multi-phase research tasks?▼

Continuation orchestration supports multi-phase research tasks by enabling deterministic task handoffs and phase tracking. You provide a task description and initiate the workflow to begin processing the research phases.

Do I need external dependencies to enable structured handoff state between agents?▼

No external dependencies are required to enable structured handoff state between agents. The workflow independently handles deterministic task handoffs and state preservation to facilitate multi-step operations.

What is the best way to track progress in multi-step AI agent workflows?▼

The best way to track progress in multi-step AI agent workflows is using continuation orchestration with built-in phase tracking. It captures essential decisions and outputs to maintain structured handoff state between agents.