Few-Shot Prompting Tool
Add a few input/output example pairs and pick a format, this builds the consistently-formatted few-shot block to paste into your prompt.
About this tool
Few-shot prompting means showing a model a handful of example input/output pairs instead of, or alongside, describing the task in words. The model infers the pattern from the examples themselves, which often gets you closer to the output shape you actually want than a description alone.
Why consistent formatting matters more than it seems like it should
If your examples are formatted inconsistently, extra whitespace in one, a different label style in another, that inconsistency itself becomes part of the pattern the model learns, and it can show up in the output in ways that are hard to trace back to the cause. Picking one format and sticking to it across every example removes that variable entirely.
A rule of thumb on how many examples to use
Three to five varied examples usually outperforms a long list of similar ones. Similar examples mostly repeat the same signal, while a few genuinely different cases (different lengths, different edge cases, different phrasing) teach the model more about where the boundaries of the pattern actually are.