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Convert a zero-shot prompt into a well-chosen few-shot version
I have a zero-shot prompt that's inconsistent in output format/quality. Help me convert it to a few-shot prompt with well-chosen examples, not just any examples. Given the prompt and a handful of real inputs/outputs (including some bad ones that show the current failure mode): prompt / sample_io
1. Select 2-4 examples for the few-shot prompt that specifically cover the range of failure modes you see in the bad outputs, not just easy/typical cases - a few-shot example set that's all easy cases won't fix inconsistency on hard ones.
2. For each chosen example, state which specific failure mode it's meant to correct, so the example set is deliberate, not just 'here are some examples'.
3. Format the examples consistently with the exact structure you want output to follow (this consistency is itself doing work, not just the content of the examples).
4. Warn me if any of my candidate examples are actually ambiguous or borderline themselves, since a flawed few-shot example teaches the model the flaw, don't include one without flagging it first.
5. Note the token cost tradeoff: few-shot prompts are longer and cost more per call, is this justified given how much the zero-shot version is actually failing, or would a more precise instruction achieve the same consistency more cheaply.
Zero-shot prompt: prompt
Sample inputs/outputs, including failures: sample_io