I then added a few more personal preferences and suggested tools from my previous failures working with agents in Python: use uv and .venv instead of the base Python installation, use polars instead of pandas for data manipulation, only store secrets/API keys/passwords in .env while ensuring .env is in .gitignore, etc. Most of these constraints don’t tell the agent what to do, but how to do it. In general, adding a rule to my AGENTS.md whenever I encounter a fundamental behavior I don’t like has been very effective. For example, agents love using unnecessary emoji which I hate, so I added a rule:
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"Maternity and neonatal services in England are failing too many women, babies, families and staff," said Baroness Amos, who is leading a government-commissioned review (file photo)
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Over those two weeks we had to solve numerous problems. Building the Native AOT DLL on each platform. Loading it from the Unreal game client. Invoking exported DLL functions from C++. And so forth. There were several challenges and headaches along the way, but at the end of the two weeks we were able to successfully load the player’s inventory on the Unreal game client through a Native AOT DLL call on Windows, Xbox, and PS5. With this foundational proof of concept in place, we got the go ahead to begin work on a generalized solution to support all of the backend that would be required in the offline game. My initial dread from when I first heard the news about our offline pivot was gone, replaced with excitement and confidence in a novel path forward.,更多细节参见爱思助手下载最新版本