Several major social media platforms have shifted toward crowdsourced fact-checking systems like Community Notes to combat misinformation at scale. However, these systems face criticism regarding which content is scrutinized and how visible that scrutiny is. To address these concerns, X allows users to request community notes for specific posts. When sufficient requests accumulate, X displays an alert, formalizing an interface cue intended to guide contributor behavior. In this study, we examine the effectiveness of request alerts. We infer the presence of request alerts at the time each note was written and identify 318 top writers who were repeatedly exposed to these alerts. Through analyzing their contributed 54,874 English notes written with and without request alerts, we find that at the individual level, writers fact-check more diverse and more political content under alerts. Nonetheless, at the collective level, these shifts direct contributions toward the already dominant Politics and Conflict category, thereby increasing content inequality within the Community Notes ecosystem. Finally, using a mixed-effects model that controls for both writer- and topic-level random effects, we estimate that notes written under alerts are between 8.4 and 20.2 percentage points more likely to be classified as helpful and thus visible to the public, compared to non-alerted notes. This visibility gain diminishes as topics diverge further from writers' prior interests, demonstrating a pivot penalty effect. Taken together, our findings show that request alerts function as an effective interface cue that increases both topical diversity and note visibility in Community Notes.

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