What problem does it solve?
This skill eliminates the complexity of developing AI CLI components for diverse platforms. Instead of learning each platform's unique architecture, conventions, and resource models, you can describe your needs once and get tailored, production-ready components for any supported AI CLI. This saves immense time and reduces the learning curve for multi-platform AI development.
Core Features & Use Cases
- Automatic Platform Detection: Intelligently identifies the current AI CLI environment (Claude Code, Gemini CLI, KiloCode, Goose, OpenAI CLI, etc.) to ensure generated components are perfectly adapted.
- Multi-Platform Component Generation: Creates platform-appropriate file structures, configuration schemas, and component types (Skills, Workflows, Agents, Tasks, Commands) that adhere to each platform's specific conventions and resource models.
- Cross-Platform Integration & Migration: Designs components that work seamlessly across multiple platforms, provides migration guides, and establishes interoperability patterns, making it ideal for cross-platform projects or migrating existing setups.
- Use Case: "Create a testing workflow that works in Claude Code and Goose." The skill will generate a
testing-automation skill for Claude Code and a testing-agent module for Goose, complete with integration guides.
Quick Start
Use the multi-platform-architect skill to create a deployment automation tool with Docker integration.
