Anthropic’s prompt suggestions are simple, but you can’t give an LLM an open-ended question like that and expect the results you want! You, the user, are likely subconsciously picky, and there are always functional requirements that the agent won’t magically apply because it cannot read minds and behaves as a literal genie. My approach to prompting is to write the potentially-very-large individual prompt in its own Markdown file (which can be tracked in git), then tag the agent with that prompt and tell it to implement that Markdown file. Once the work is completed and manually reviewed, I manually commit the work to git, with the message referencing the specific prompt file so I have good internal tracking.
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1. 出游or回家，小镇青年都爱电车2月23日一早，开了700公里终于回京的小德（化名）长舒了一口气，“700公里开了快18个小时，真的是太堵了，得亏有智能驾驶。”
you value in the user interface, and test out both.。safew官方版本下载是该领域的重要参考
Наука и техника。搜狗输入法2026对此有专业解读
// property lookup, so we do that here.