Serendipity is important to design for, yet it remains difficult to measure and evaluate. No validated questionnaire exists, so studies either borrow ResQue's novelty scale, which does not measure serendipity, or build their own items, which makes findings hard to compare and synthesize. Building on our earlier conceptualization of experienced serendipity as a fortuitous encounter with content that is both refreshing and enriching, we developed the Serendiptionnaire, a questionnaire that operationalizes our framework. We conducted twenty-seven cognitive interviews over three iterations with respondents who varied in age, education level, country of birth, and English proficiency, while they browsed recommendations on platforms such as Instagram, TikTok, YouTube, and Spotify. After each iteration, we revised the items until respondents interpreted them as intended. The resulting instrument consists of modular scales that researchers can combine to target the specific flavor of serendipity they want to study or design for. The Serendiptionnaire offers a ground truth for validating system-centered serendipity metrics and LLM-based evaluations, and it provides a nuanced evaluation of users' experienced serendipity.

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