orchestrator-mode

Enforces a staged multi-agent workflow from GitHub issue plan to merge.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/AmirTlinov/magray-marketplace --skill orchestrator-mode
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: orchestrator-mode
Source: https://github.com/AmirTlinov/magray-marketplace/tree/main/flagship-team/skills/orchestrator-mode
Command: npx skills add https://github.com/AmirTlinov/magray-marketplace --skill orchestrator-mode

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a structured and controlled environment for orchestrating multiple AI agents to perform complex tasks with clear lifecycles and validation gates.

Core Features & Use Cases

  • On-demand Orchestration: Activates only when strict multi-agent coordination is explicitly requested.
  • Lifecycle Management: Enforces a strict workflow: explore → issue plan → worker → PR review → merge/close.
  • Artifact Generation: Ensures formal artifacts and status updates are maintained throughout the process.
  • Use Case: When a complex software feature requires research, planning, implementation by multiple developers (agents), and formal code review before merging, this Skill ensures each step is managed rigorously.

Quick Start

Use the orchestrator-mode skill to manage the development lifecycle for a new feature.

Frequently Asked Questions about orchestrator-mode

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

FAQPage Schema
What is strict multi-agent orchestration for software development?▼

Multi-agent orchestration coordinates multiple AI agents through a strict lifecycle to execute complex tasks. It enforces a defined workflow from exploration and planning to isolated worker implementation, PR review gates, and final merge close-loop processes.

How do I manage a GitHub Issue lifecycle with multi-agent automation?▼

Managing a GitHub Issue lifecycle with multi-agent automation follows a strict PLAN→SLICE execution flow. Agents handle context-pack updates, generate isolated worker worktrees, enforce PR review gates, and maintain formal artifacts throughout the merge close-loop process.

When do I need strict workflow orchestration for AI code generation?▼

Strict workflow orchestration is needed when a complex software feature requires rigorous research, multi-agent implementation, and formal code review gates before merging. It activates explicitly to ensure isolated worker execution and context-pack validation.

Can I use isolated worker worktrees for parallel AI agent code review?▼

Yes, isolated worker worktrees support parallel implementation by multiple agents. The orchestration lifecycle enforces PR review gates, ensuring formal code validation occurs before any merge close-loop processes finalize the task.

Does multi-agent orchestration require specific dependencies for GitHub automation?▼

Multi-agent orchestration operates without specific external dependencies, relying on built-in references. It supports various agents for exploration, implementation, review, and strategic thinking to manage context-pack single source of truth and GitHub workflows.

What are the limitations of enforcing strict multi-agent orchestration for coding tasks?▼

Strict multi-agent orchestration only activates when explicitly requested, meaning it will not intercept standard development workflows. It requires adherence to its rigid explore→issue plan→worker→PR review→merge lifecycle, which may constrain ad-hoc task execution.