multi-ai

Coordinate multi-AI tasks across Claude Code, Codex CLI, and Gemini CLI.

Updated Apr 6, 2026
One-click install
npx skills add https://github.com/fantay0312/fantayspec --skill multi-ai-fantay0312
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: multi-ai
Source: https://github.com/fantay0312/fantayspec/tree/main/shared/skills/skills-all/multi-ai
Command: npx skills add https://github.com/fantay0312/fantayspec --skill multi-ai-fantay0312

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Multi-AI orchestration across Claude Code, Codex CLI, and Gemini CLI to coordinate tasks, share context, and synchronize results in a single workflow.

Core Features & Use Cases

  • Task delegation across engines to balance workloads and optimize outcomes.
  • Context handoff with shared session state for cross-model collaboration.
  • Phase coordination across /research, /ideate, /plan, /impl, /verify to support end-to-end workflows.

Quick Start

Configure the orchestrator.yaml to enable multi-model coordination and run the shared skill integration in your orchestration pipeline.

Frequently Asked Questions about multi-ai

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

FAQPage Schema
How do I coordinate tasks across Claude Code, Codex CLI, and Gemini CLI?

Multi-AI orchestration coordinates tasks across Claude Code, Codex CLI, and Gemini CLI to balance workloads, delegate tasks, and synchronize results within a single workflow.

What is cross-model context handoff and how does it work for AI sessions?

Cross-model context handoff works by applying shared session state to persist data and track sessions across different engines, ensuring reproducible orchestration throughout the workflow.

How do I integrate multi-AI orchestration into research and implementation phases?

You integrate multi-AI orchestration by applying it across /research, /ideate, /plan, /impl, and /verify phases to support end-to-end workflows with continuous engine selection and coordination.

Can I use a single orchestrator to balance workloads across multiple AI engines?

Yes, you can balance workloads by configuring the orchestrator.yaml to enable multi-model coordination, which delegates tasks across engines to optimize outcomes and synchronize results.

How does session persistence work when switching between Claude, Codex, and Gemini?

Session persistence works by tracking cross-engine collaboration and handing off context, ensuring that shared session state remains synchronized and reproducible when switching between models.