orch

Coordinate teams of AI agents for parallel codebase tasks.

134|14|Updated Mar 10, 2026

Search Tags:#parallel processing #task automation #ai agent #orchestration #codebase management

Ready to run

npx skills add https://github.com/oxgeneral/ORCH --skill orch

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: orch
Source: https://github.com/oxgeneral/ORCH/tree/main/skills/orch
Command: npx skills add https://github.com/oxgeneral/ORCH --skill orch

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @oxgeneral/orch, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill orchestrates teams of AI agents to work on codebases in parallel, solving the problem of managing multiple AI agents without the need for constant human oversight.

Core Features & Use Cases

Parallel Agent Management: Run multiple AI agents simultaneously on a single project.
Task and Goal Management: Create, assign, and track tasks and goals for AI agents.
Agent Templates: Utilize pre-built agent templates for common roles like backend, frontend, QA, and more.
Inter-Agent Communication: Enable communication and shared context between agents.
Configuration and Logs: Configure orchestrator settings and view logs for monitoring and debugging.
Use Case: For a software development project, use this Skill to automate code reviews, testing, and documentation, while coordinating multiple AI agents to work in parallel.

Quick Start

Initialize your project with orch init and deploy a team with orch org deploy startup-mvp --goal "Build feature X".

Frequently Asked Questions about orch

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

FAQPage Schema

How do I manage multiple AI agents working in parallel on a single codebase?▼

You can manage parallel AI agents by using an orchestration system that handles agent lifecycle, task assignment, and inter-agent communication. This coordinates simultaneous code execution without requiring constant human oversight.

What is AI agent orchestration for parallel task automation?▼

AI agent orchestration coordinates teams of agents to execute codebase tasks in parallel. It handles goal decomposition, task assignment, and shared context between agents to automate workflows like code reviews and testing.

How do I deploy a team of AI agents for a software development project?▼

To deploy an AI agent team, initialize your project with an orchestration command, then use a deploy command with a specific goal. The orchestrator assigns roles from pre-built templates for backend, frontend, or QA tasks.

Do I need to configure agent roles before automating codebase tasks?▼

Yes, you must configure agent roles and workflows before automating tasks. The orchestration system utilizes pre-built templates for common roles like backend and QA, which you assign to manage specific parallel code execution goals.

Can AI agents communicate and share context during parallel code execution?▼

Yes, the orchestration system enables inter-agent communication and shared context between agents working in parallel. This ensures coordinated task completion, automated code reviews, and synchronized testing across the codebase.

How do I monitor and debug parallel AI agent workflows?▼

You monitor and debug parallel AI agent workflows by viewing orchestrator configuration logs. These logs track agent lifecycle, task assignment, and goal decomposition to provide visibility into automated codebase execution.