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:
The TLB is flushed entirely on any write to CR3 (the page directory base register). There is no per-entry invalidation on the 386 -- that arrived with the 486's INVLPG instruction.
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其次，我们希望智能体能“动手”做事：执行和交互能力。这就意味着它能够使用工具、执行操作，并能与外部环境发生直接交互。在数字世界中，智能体可以模拟人类操作，通过键盘输入、点击屏幕的方式来完成任务；也可以通过其他程序或系统接口来调用工具；还可以发挥模型特长，通过编写和执行代码来达成目的。在物理世界中，智能体则需要与各类控制系统和设备相连接，通过下达指令来操控物理对象，将智能决策转化为现实行动。
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Отмечается, что аэропорты Казани и Нижнекамска временно не принимают и не отправляют рейсы. Детей в школах и садиках Казани временно эвакуировали в специальные укрытия.