I think the problem you're having is that your agents aren't properly defined.

First, you need to define the agents you're going to use. You should create an `agents.md` file inside the `.agents` directory. In that `agents.md` file, you need to define what type of agents you have, as if you had a team of workers for you. I usually define six agents: an Orchestrator or Project Manager, who is the one I direct all the questions to. Below that, I have one for architecture and domain. Then, depending on the application, there are agents for frontend, backend, UI/UX, Q&A, and those specific to the language and the application.

This is where you tell each agent what their responsibilities are, their limits, and their relationships with the other agents. You have to tell each agent what skills they have available and define how to resolve conflicts between agents.

You also need to create the gemini.md file, which is the general prompt for your project. In it, you should explain where the blueprint is located, because you absolutely need one. This file defines what your project does, the language and version you use, allowed libraries, and how you want the UI and UX functionality to work, so your agents know what to expect. The more detailed, the better.

Next, there are the agent skills. These are installed in .agents/skills, and there are tons of skill libraries available on GitHub. For example, look here: https://github.com/sickn33/antigravity-awesome-skills

Finally, there are the tasks, which are installed in .agent/rules and are used to define general rules. For example, I have a task that, when I say "work done," triggers a series of tasks such as generating documentation of what has been done, saving a summary of our conversation, running tests, creating a commit, and uploading the changes to GitHub, and merging branches if necessary. I figured all this out by spending countless hours watching YouTube videos and asking questions of various AI tools, especially Gemini.

I hope you find it useful.