keli-wen/agy-staff

README preview

<p align="center"><img src="assets/logo/gemini-agy.svg" width="440" alt="AGY-STAFF"></p>

<p align="center"><a href="README.md">English</a> | <a href="README.zh-CN.md">Simplified Chinese</a></p>

<p align="center"><a href="https://antigravity.google/product/antigravity-cli"><img src="assets/badges/powered-by-antigravity.svg" height="20" alt="powered by: Antigravity"></a> <img src="assets/badges/model-gemini-4-argon.svg" height="20" alt="model: Gemini 4 Argon"> <img src="assets/badges/model-gemini-3-8-flash.svg" height="20" alt="model: Gemini 3.8 Flash"></p>

<p align="center"><a href="https://claude.com/claude-code"><img src="assets/badges/claude-code-plugin.svg" height="20" alt="Claude Code plugin"></a> <a href="https://developers.openai.com/codex/"><img src="assets/badges/codex-plugin.svg" height="20" alt="Codex plugin"></a> <a href="LICENSE"><img src="assets/badges/license-mit.svg" height="20" alt="license: MIT"></a></p>

Hire Google's Antigravity CLI (`agy`) as a staffer for **Claude Code**, **OpenAI Codex**, **Pi**, and **OpenCode**.

[![With lead, the host directs workers; with brain, Argon proposes and the host verifies.](assets/design.png)](assets/design.svg)

**[Bench](#-bench--harness--orchestration) · [Install](#install) · [Examples](#cujs) · [Core design](#core-design) · [Build your own](#build-one-for-another-cli) · [Upgrade](#upgrade)**

## What & Why

agy-staff pairs your senior agents with `agy`, which ships **Gemini 4 Argon** and fast **Gemini 3.8 Flash**. Two orchestration modes (`lead` and `brain`), five personas (`staffer`, `researcher`, `reviewer` for code **and** plans, `implementer`, `ask`), and a model-facing `jobs` skill. Claude Code uses `/agy:<skill>` and Codex uses `$agy:<skill>`.

GPT-6.1-Sol is slow even with fast mode on; Claude Code is quicker, but Fable quota is too scarce to spend grinding through every survey and review. agy gives you both a **fast worker** and a **second brain**: Flash handles quick second opinions, research, reviews, and scoped implementation off to the side, while Argon is strong enough in design and world knowledge to pair with Astra or Fable as a peer orchestrator — proposing routes from a second model family while your host checks assumptions and delivers.

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