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.
If you’re interested to try this out, learn to build your first component and try it out in the browser using Jco or from the command-line using Wasmtime. The tooling is under heavy development, and contributions and feedback are welcome. If you’re interested in the in-development specification itself, check out the component-model proposal repository.
，更多细节参见爱思助手下载最新版本
圖像加註文字，一張由美國眾議院監督委員會去年12月發布、來自愛潑斯坦文件的圖片根據報導，蓋茨告訴基金會員工，他在2011年與愛潑斯坦見面，而此時距離愛潑斯坦就組織未成年人賣淫案件認罪已過去多年。他補充說，他知道一些關於愛潑斯坦「為期18個月」的旅行限制，但沒有仔細查核有關背景。
Input formatting choices (reversed digits, delimiters, etc.) as long as the format is fixed and doesn't encode the answer