Anyway, the reason I got back to Antigravity was that I found an interesting repo I wanted to test: Agency Agents

I checked the Antigravity docs and didn't find anything about agent setup. I just dropped them into a project like with Claude Code and asked the LLM to check it and fix the setup. It reassured me that everything was correct and that it supports agent teams.

However, with all models, Antigravity fails to follow through the whole workflow. I have to pinpoint missed steps for every single task.

Heavily inspired by the original repo, I prepared a team specialized in game development with Unity: https://github.com/AlexMerzlikin/unity-agent-team

I also added custom tools to the Coplay Unity MCP to take screenshots and interact with the in-game logic. This way, the LLM can write manual test cases, run the game, take screenshots, and query the scene hierarchy to verify these "manual" tests.

First impressions of these agents:
• As said above Antigravity doesn't support it at all.
• Codex and Claude Code integration is great. You can check what each agent does, and they run in parallel, making the whole flow a lot faster.
• This team produces a lot of documentation. Compared to the default old Sonnet, which created multiple docs per prompt, this team does it better though. Everything is structured according to Nexus Sprint rules, and I feel like it helps to understand how your requirements transform throughout the dev pipeline. Also, each agent is super focused. Subjectively, there is less fluff in each document, and I get the exact info I need from a particular output. It's great for when I work on a big project, but it's too much overhead for prototypes. I prefer to skip it completely when just testing ideas.
• Token drain. Each agent has its own context, so token spend multiplies. Keep that in mind when testing these agents, or tailor it to reduce the number of agents.

If anyone tries out the Unity agent team repo, drop a comment. I am curious to see how it handles your specific setups and workflows.

#ai #agent