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.
// console.log(canSeePersonsCount([5,1,2,3,10])); // 输出 [4,1,1,1,0]（正确）
，更多细节参见heLLoword翻译官方下载
Медведев вышел в финал турнира в Дубае17:59，详情可参考51吃瓜
36氪获悉，寒武纪发布业绩快报，2025年实现营业收入64.97亿元，同比增长453.21%；归属于母公司所有者的净利润20.59亿元，上年同期亏损4.5亿元。，详情可参考heLLoword翻译官方下载