orchestrate

Orchestrate multiple AI agents across parallel multi-model workflows.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/zhsks311/cc-orchestrator --skill orchestrate-zhsks311
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: orchestrate
Source: https://github.com/zhsks311/cc-orchestrator/tree/main/skills/orchestrate
Command: npx skills add https://github.com/zhsks311/cc-orchestrator --skill orchestrate-zhsks311

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a structured approach to coordinating multiple AI agents to handle complex, multi-phase tasks. It enables parallel exploration, design decisions, and implementation across frontend, backend, data, and infrastructure by delegating work to native and external agents while ensuring governance and safety checks.

Core Features & Use Cases

  • Hybrid Swarm orchestration: parallel routing of tasks between native coding agents and MCPs to optimize quality and speed.
  • -Phase-based execution: Phase 0-3 workflow from intent gating to execution and verification.
  • Pattern-driven delegation: reusable templates for exploration, implementation, and review.
  • Use Case: A multi-file UI and API feature is implemented by parallel teams, then integrated with automated checks.

Quick Start

Run orchestrate on a project with an initial user request such as: "Implement a responsive login page with API integration." The system will classify the task, allocate agents, and start parallel exploration and development while monitoring quality gates.

Frequently Asked Questions about orchestrate

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

FAQPage Schema
How do I coordinate multiple AI agents for parallel software development?

To coordinate multiple AI agents for parallel software development, you can use a hybrid swarm orchestration approach that routes tasks between native coding agents and external services across frontend, backend, and infrastructure contexts.

What is multi-model workflow orchestration for complex software projects?

Multi-model workflow orchestration is a structured approach that delegates complex, multi-phase tasks across various AI agents to enable parallel exploration, architecture decisions, and implementation while enforcing interface contracts and governance checks.

How to start a parallel multi-agent workflow for a UI and API feature?

To start a parallel multi-agent workflow for a UI and API feature, submit an initial request like implementing a responsive login page with API integration; the system classifies the task, allocates agents, and begins parallel exploration and development.

Does multi-agent orchestration support phase-based execution and quality gates?

Yes, multi-agent orchestration supports phase-based execution through a Phase 0-3 workflow that progresses from intent gating to execution and verification, actively monitoring quality gates to ensure reliable and auditable results.

What is the best way to manage interface contracts across parallel AI agents?

The best way to manage interface contracts across parallel AI agents is by applying pattern-driven delegation templates that enforce explicit routing and governance checks during exploration, implementation, and review phases.

When should I not use parallel multi-agent orchestration for software architecture decisions?

You should avoid parallel multi-agent orchestration for software architecture decisions when a project lacks clearly defined interface contracts or cannot support phase-based intent gating, as reliable results depend on strict governance checks.