Chain-of-Thought Prompt Wrapper
Describe the task, pick a reasoning structure, and this wraps it into a prompt that asks the model to reason through the problem before answering.
About this tool
Chain-of-thought prompting asks a model to work through its reasoning in steps before committing to a final answer, instead of jumping straight to a conclusion. On multi-step or judgment-heavy tasks, that extra reasoning tends to catch mistakes a straight-to-the-answer response would have missed, the model has room to notice when an early step doesn't hold up.
Three ways to structure the reasoning
"Think step by step" is the loosest version, free-form reasoning followed by a clearly marked final answer. Numbered reasoning steps forces a more explicit, checkable structure. "Consider alternatives, then decide" is best when there's genuinely more than one reasonable answer, it makes the model weigh options instead of anchoring on the first one it considers.
This adds length, and therefore cost
Reasoning steps mean more output tokens, which means more cost and more latency. It's worth it for genuinely hard tasks, ambiguous judgment calls, multi-step calculations, anything where getting it wrong is costly, but it's overkill for simple lookups or single-fact questions where the model wasn't going to make a reasoning error in the first place.