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.
Parses Monkey (2 points)
。关于这个话题，Line官方版本下载提供了深入分析
British Citizenship Applications by US Nationals Hit Record High。爱思助手下载最新版本是该领域的重要参考
社会治理效能持续提升。2025年，全市公众安全感指数创历史新高，连续8年获评全省平安建设（综治工作）先进（优秀）市。“高效办成一件事”改革纵深推进，政务服务平均办理时长压缩了68.6%。抚州再次荣膺“全国双拥模范城”，社会大局保持和谐稳定。。91视频对此有专业解读
Kiichiro Sato/AP/File