multi-ai-orchestration

Route tasks to cost-effective AI models like Gemini, Codex, Copilot, and Claude.

3|3|Updated Dec 16, 2025
One-click install
npx skills add https://github.com/shakestzd/htmlgraph --skill multi-ai-orchestration-shakestzd
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: multi-ai-orchestration
Source: https://github.com/shakestzd/htmlgraph/tree/main/packages/claude-plugin/skills/multi-ai-orchestration-skill
Command: npx skills add https://github.com/shakestzd/htmlgraph --skill multi-ai-orchestration-shakestzd

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the challenge of selecting the most cost-effective and appropriate AI model (Spawner) for various tasks, optimizing resource usage and budget.

Core Features & Use Cases

  • Cost-First Routing: Guides the selection of AI models based on task type and cost hierarchy (Gemini, Codex, Copilot, Claude).
  • Spawner Patterns: Demonstrates how to use spawn_* functions for specific tasks like code generation, research, and Git operations.
  • Use Case: When needing to implement a new feature, this Skill ensures you use spawn_codex for writing code, spawn_gemini for initial research, and spawn_copilot for committing changes, rather than over-relying on expensive models.

Quick Start

Use the multi-ai-orchestration skill to research existing authentication patterns.

Frequently Asked Questions about multi-ai-orchestration

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

FAQPage Schema
How do I optimize AI model costs when orchestrating multiple AI models?▼

AI model cost optimization uses a hierarchical routing system to prioritize free and low-cost models like Gemini and Codex over expensive ones, ensuring efficient resource allocation across various tasks.

When should I use Gemini versus Codex or Claude for AI task routing?▼

Use Gemini for initial research, Codex for code generation, Copilot for Git operations, and Claude for strategic planning, routing tasks based on a cost hierarchy to avoid over-relying on expensive models.

What is the best way to orchestrate code generation and Git operations using different AI spawners?▼

Orchestrate code generation and Git operations by using specific spawn functions: spawn_codex for writing code, spawn_gemini for research, and spawn_copilot for committing changes to maintain cost efficiency.

Can I use multi-ai orchestration to manage research and strategic planning tasks?▼

Multi-ai orchestration supports research and strategic planning by routing research to Gemini and strategic planning to Claude, utilizing a headless spawner selection system to match tasks with appropriate AI models.

Does cost-first AI model routing require specific dependencies or environments?▼

Cost-first AI model routing operates without external dependencies, using internal scripts and references to guide the selection of AI spawners like Gemini, Codex, Copilot, and Claude for task-specific orchestration.

Why does my AI task orchestration over-rely on expensive models?▼

AI task orchestration over-relies on expensive models when lacking a cost hierarchy, which this Skill solves by prioritizing free and low-cost spawners like Gemini and Codex for appropriate task types.