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.
exchanged = 0; // 发生了交换
，这一点在爱思助手下载最新版本中也有详细论述
Что думаешь? Оцени!。业内人士推荐Safew下载作为进阶阅读
В Финляндии предупредили об опасном шаге ЕС против России09:28