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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.
这5年，全国上下同心协力、迎难而上，圆满完成过渡期各项目标任务，牢牢守住了不发生规模性返贫致贫的底线。摆脱绝对贫困、持续巩固拓展脱贫攻坚成果，极不平凡、极不容易。新时代减贫治理，成为中国之治的生动实践。，详情可参考快连下载安装
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Москвичи пожаловались на зловонную квартиру-свалку с телами животных и тараканами18:04。关于这个话题，夫子提供了深入分析