rune-orchestration

Coordinate distributed multi-agent workflows using file-based handoffs and inscription-driven protocols.

6|3|Updated Feb 11, 2026
One-click install
npx skills add https://github.com/vinhnxv/rune-plugin --skill rune-orchestration
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: rune-orchestration
Source: https://github.com/vinhnxv/rune-plugin/tree/main/plugins/rune/skills/rune-orchestration
Command: npx skills add https://github.com/vinhnxv/rune-plugin --skill rune-orchestration

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Distributed multi-agent orchestration unblocks complex tasks by partitioning work across specialized AI teammates, enabling scalable collaboration beyond a single context window.

Core Features & Use Cases

  • File-based handoff: agents write to and read from shared tmp/reviews/tmp directories to exchange findings and assemble a Tome.
  • Architectural patterns: supervisor/orchestrator, peer-to-peer swarm, and hierarchical coordination for flexible workflow shapes.
  • Inscription-driven workflow: defines teammate roles, outputs, and validation pipelines, with optional references/scripts/assets to guide execution.

Quick Start

Summon a small Rune orchestration with three Ash agents to see file-based handoff in action and generate a TOME.md summary.

Frequently Asked Questions about rune-orchestration

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

FAQPage Schema
How do I coordinate multi-agent workflows when a single context window is too small?

You can coordinate multi-agent workflows by partitioning tasks across language-model instances. This approach uses file-based handoffs and inscription-driven protocols to orchestrate, collect, and validate distributed outputs.

What is file-based handoff for orchestrating agent teams?

File-based handoff is a coordination pattern where agents write to and read from shared tmp directories to exchange findings. This enables asynchronous collaboration and output assembly across distributed language-model instances.

How do I set up a hierarchical coordination pattern for complex code review?

You can set up hierarchical coordination by defining teammate roles and validation pipelines through an inscription-driven workflow. This orchestrates specialized agents to concurrently review and audit complex codebases.

What's the best way to structure peer-to-peer swarm coordination for distributed tasks?

Peer-to-peer swarm coordination is structured using an inscription-driven protocol that defines roles and outputs. Agents operate autonomously and exchange findings via shared file directories to assemble a validated summary.

Do I need external dependencies to run multi-agent orchestration with safe handoffs?

No, you do not need external dependencies to run multi-agent orchestration. The workflow relies entirely on partitioning tasks across language-model instances and using shared directories for file-based handoffs.

When should I not use a distributed multi-agent orchestration approach?

You should avoid distributed multi-agent orchestration for simple tasks that fit within a single context window. The overhead of managing file-based handoffs and inscription protocols is designed for complex code review and auditing workflows.