Нина Ташевская (Редактор отдела «Среда обитания»)
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:,这一点在夫子中也有详细论述
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2021—2025 年度,中国企业研发投入的区间分布保持稳定,延续了以亿元和千万元级企业为“腰部力量”、百亿元以上和千万元及以下企业作为“首”“尾”两端的基本态势。腰部区间覆盖了最大比例的企业数量,构成了研发梯队的中坚部分。
SSIM was chosen over CNN-based approaches for a deliberate reason: reproducibility without infrastructure. SSIM is a deterministic mathematical function. No training data, no model weights, no GPU, no framework dependencies. Anyone with fontconfig and node-canvas can reproduce these exact numbers on the same platform.