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.
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"We chose a threshold that requires a few searches within a short period of time, while still erring on the side of caution," Instagram's blog post explains. "While that means we may sometimes notify parents when there may not be real cause for concern, we feel — and experts agree — that this is the right starting point, and we’ll continue to monitor and listen to feedback to make sure we’re in the right place."