Multi-Platform Agent Portability

In the rapidly evolving AI landscape, being locked into a single agent ecosystem is a technical risk. This skill solves the "agent lock-in" problem by decoupling your AI tool logic from specific platform implementations. It allows developers to maintain a single, "portable core" of logic while generating thin, platform-specific adapters for every major coding agent.

What it does

The skill analyzes existing agent instructions and splits them into two distinct layers. The Portable Core houses the domain logic, operating procedures, and guardrails. The Platform Adapters handle environment-specific triggers, tool naming conventions (e.g., mapping bash to terminal tools), and metadata requirements for specific clients.

Supported Platforms

• Codex/OpenAI: Clean SKILL.md frontmatter and openai.yaml configs.
• Claude Code: Intent-rich descriptions and Claude-specific tool mappings.
• Cursor & Copilot: .cursor/rules and .github/instructions integration.
• Grok & Gemini: Optimized CLI language and long-context anchors.

Why use this instead of manual prompting?

Manually rewriting skills for different agents is error-prone. You might forget that one agent uses 'Apply Path' while another uses 'write_file'. This skill automates the translation of tool-calling conventions and ensures your prompt logic isn't degraded when moving across models with different context windows or personality biases.