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.
本报布达佩斯2月27日电 （记者禹丽敏）当地时间2月27日零时许，一列货运列车从匈牙利首都布达佩斯的费伦茨城火车站驶出，标志着匈塞铁路匈牙利段正式开启货运运输。
，更多细节参见heLLoword翻译官方下载
1,000+ founders and investors come together at TechCrunch Founder Summit 2026 for a full day focused on growth, execution, and real-world scaling. Learn from founders and investors who have shaped the industry. Connect with peers navigating similar growth stages. Walk away with tactics you can apply immediately，更多细节参见safew官方版本下载
accepted an envelope (with cash or checks) and printed a transaction identifier
The bottom of confusables.txt. These pairs score negative SSIM — less similar than random noise. confusables.txt maps them as confusable because they decompose to the same abstract character, not because they look alike.