Imagine a vast shopping mall parking lot with thousands of individual parking spots and internal lanes (representing road segments within a cluster). No matter how complex it is inside, there are usually only a few key exits to the main roads. Our goal was to identify these natural "exits" for each map cluster. For instance, the complex road network around Amsterdam Airport Schiphol (see on OpenStreetMap) has many internal roads but limited primary access points.
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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Белорусская теннисистка ранее стала амбассадором модного дома, а сегодня посетила шоу в качестве гостьи. Помимо спортсменки, на мероприятии заметили Ренату Литвинову и Деми Мур, певца Шона Мендеса, а также Николь Кидман, Анну Винтур и Пэрис Хилтон.，更多细节参见WPS官方版本下载
→ 0x000 (continue) + limit check flag
（二）从海关取得的海关进口增值税专用缴款书上列明的增值税税额；