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🤖 How to Build Your Agent Skills Once, Run It Almost Everywhere: Claude Code, Codex, Cursor

Every AI platform has its own way of handling workflows today. Agent Plugins 1.0 could change that by creating a shared layer where agents follow you wherever you work.

Author

Neil Phan
August 21, 2026

TL;DR

Agent Plugins are an open format for packaging reusable agent workflows so they can work across compatible platforms. They combine Agent Skills, MCP configuration, and other shared components inside one portable package.

This helps reduce the work of rebuilding the same workflow for Codex, Cursor, ChatGPT, and other supported clients. Claude Code can also use Agent Plugins through a translation layer, although it doesn’t currently support the format natively.

The bigger shift is toward reusable agent components that are less tied to one model or platform. OpenAI, Google, and other companies are already building around Agent Skills and MCP.

Key points

  • Agent Plugins 1.0 launched with support across six major clients.

  • Avoid assuming one plugin will behave exactly the same everywhere.

  • Keep reusable workflow logic separate from platform-specific settings.

Introduction

I bet you’ve faced this: You build a workflow that works perfectly in Cursor. Then you move to Codex, and it breaks. So you rebuild the same workflow again.

I hate this.

Akshay recently shared the exact same problem after recreating his workflow for Cursor, Copilot, and Codex. Each version slowly became different.

That’s why Agent Plugins caught my attention. OpenAI and partners like AWS, Cursor, GitHub, VS Code, and Vercel are building an open standard around:

  • Agent Skills → Reusable instructions and workflows

  • MCP → Tools and external data

  • Config files → Everything needed to run the plugin

Build once. Take it anywhere. In this guide, I’ll show you how Agent Plugins work and how to master everything, apply it in the right way.

And I think this is much bigger than cleaner configs.

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