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.
{ 34, 46, 48, 36, 25, 11, 13, 27 },
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В Следственном комитете России рассказали, что ранее судимому 43-летнему мужчине и его 51-летней сожительнице, в квартире которых нашли девочку, предъявили обвинение в похищении ребенка.
That's it. Any other response is either a variation of these (like "resize the buffer," which is really just deferring the choice) or domain-specific logic that doesn't belong in a general streaming primitive. Web streams currently always choose Wait by default.