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hive

Orchestrate multi-provider AI teams through a 7-stage quality pipeline.

Updated Mar 4, 2026
Search Tags:#quality assurance#code generation#task decomposition#multi-agent systems#team collaboration#ai orchestration
One-click install
npx skills add https://github.com/inhyoe/hive-plugin --skill hive-inhyoe
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hive
Source: https://github.com/inhyoe/hive-plugin/tree/main/skills/hive
Command: npx skills add https://github.com/inhyoe/hive-plugin --skill hive-inhyoe

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the complex process of decomposing large tasks and orchestrating multiple AI agents (like Claude, Codex, and Gemini) to collaborate and execute them efficiently, ensuring quality through a structured pipeline.

Core Features & Use Cases

  • Multi-Agent Orchestration: Manages teams of AI agents for complex project execution.
  • Structured Quality Gates: Enforces a 7-stage quality pipeline with hard gate enforcement to ensure consistent, high-quality output.
  • Agent Isolation: Implements patterns like CodeDelegator to ensure agents focus on their specific tasks without interference.
  • Use Case: When you have a large software development task that requires design, implementation, testing, and cross-verification, this Skill can decompose it, assign modules to different AI agents, and manage their collaboration through a rigorous quality process.

Quick Start

Use the hive skill to decompose the task of building a new user authentication module.

Frequently Asked Questions about hive

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

FAQPage Schema
How do I orchestrate multiple AI agents like Claude and Gemini for complex software development?▼

Multi-agent orchestration coordinates AI teams through a structured 7-stage quality pipeline. It decomposes large tasks, assigns modules to specific agents, and manages collaboration via consensus building and TDD-driven execution.

What is task decomposition in multi-agent AI systems and when is it needed?▼

Task decomposition breaks large projects into isolated modules for different AI agents. It is needed for complex software execution requiring design, implementation, testing, and cross-verification to ensure agents focus without interference.

How do I enforce quality assurance gates across multiple AI coding agents?▼

Quality assurance gates are enforced through a structured 7-stage pipeline. This process manages agent coordination and applies hard gate enforcement to ensure consistent, high-quality output during complex project execution.

Does multi-agent AI orchestration work with Codex and Claude simultaneously?▼

Multi-agent orchestration supports simultaneous coordination of multiple providers including Codex and Claude. It uses patterns like CodeDelegator to isolate agent tasks and facilitate structured collaboration without interference.

What are the limitations of using a structured 7-stage pipeline for AI team collaboration?▼

The 7-stage pipeline requires rigorous consensus building and TDD-driven execution, which may introduce overhead for smaller tasks. It is designed for complex projects needing cross-verification rather than simple, isolated code generation.

How to start building a new user authentication module using multi-agent AI orchestration?▼

Start by prompting the orchestration skill to decompose the authentication module task. The system assigns design, implementation, and testing components to different AI agents, managing their collaboration through the quality pipeline.

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