Running behavioral experiments is expensive, slow, and prone to design flaws, often detectable after collecting data. We introduce UnexpectedParrots to iteratively refine behavioral study designs before a researcher recruits costly human participants. UnexpectedParrots relies on reasoning traces in addition to responses from LLM participants to uncover diagnostic critiques of structural errors and missed opportunities in existing study designs. When evaluated against a human-pilot or a no-simulation design-only baseline, UnexpectedParrots adds most value, producing unique, high-quality critiques. In a moderated user study with 12 proficient researchers, we find UnexpectedParrots useful, time-saving, and thought-provoking. Critiques provided by UnexpectedParrots often converge on issues researchers identify only during independent human pilots or additional formative interviews, even when the fidelity of the simulated populations remains questionable. Our users deem UnexpectedParrots useful not only as a tool to conduct early pilot studies and identify errors but also as an ideation tool to expand one's research horizon.

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