Kind of ugly, but it would work. When the guess is small, you use a
Раскрыты подробности похищения ребенка в Смоленске09:27
美光科技公司表示，内存芯片短缺在过去一个季度愈演愈烈，供应紧张状况将持续到2026年之后。，这一点在91视频中也有详细论述
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В Финляндии предупредили об опасном шаге ЕС против России09:28。heLLoword翻译官方下载对此有专业解读
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.