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:
A recent study by Fortune magazine stated that AI search engines are confidently wrong over 60% of the time, with various widely-used AI tools exhibiting significantly high error rates. This trend often extends to AI-generated captions, as run-on sentences, misheard phrases, and dialogues compressed into an incomprehensible stream of text may be familiar features across […]
，更多细节参见WPS下载最新地址
[&:first-child]:overflow-hidden [&:first-child]:max-h-full"。关于这个话题，雷电模拟器官方版本下载提供了深入分析
上海医疗资源集中、医疗活动密集，走在中国对外开放和国际合作的前沿。然而，上合组织成员国、伙伴众多，民众的文化习俗、饮食结构、经济水平和疾病易感性各异，防控治理难度颇大。如何在多元中寻求共识，构建一套真正普惠、包容、有效的代谢性疾病防控治理体系？这是摆在中国工程院院士、上海交通大学医学院附属瑞金医院院长宁光面前的一道难题。
The V86 return path is one of the longest microcode sequences in the 386. It pops nine DWORDs from the stack -- EIP, CS, EFLAGS, ESP, SS, ES, DS, FS, GS -- compared to three for a normal IRET. The microcode then sets up fixed access rights for every segment register: