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.
南方周末：你也说过，2015年17岁的你参加肖赛时，其实自己并没有准备好。如果现在的你可以给当时的自己一个建议，你会劝他不要参赛吗？。关于这个话题，WPS下载最新地址提供了深入分析
。业内人士推荐WPS下载最新地址作为进阶阅读
view = result.value; // Must reassign
let currentStep = workflowFn(initialInput);。搜狗输入法2026是该领域的重要参考