This article examines Chile's post-disaster data collection and management, focusing on state legibility tools for identifying housing damage and victims' needs. Drawing on James Scott's theory of legibility, we explore how standardized categories are used in disaster management. Through documentary analysis and key informant interviews, we assess the strengths and limitations of the forms used for allocating aid. The 2022 Vi & ntilde;a del Mar wildland-urban interface fire serves as a case study to illustrate how classification systems determine victim status, influencing government resource allocation. We show that Chile has made significant progress in loss and needs assessment after disasters but gaps remain in data integration and intersectoral collaboration. Three main themes emerge from the analysis: actor coordination, social legitimacy, and administrative blindness. We conclude that while legibility tools facilitate state action, they also obscure the complexities of disasters. This case study provides further evidence that disparities in aid distribution hinder recovery efforts and that for many victims, disaster aid has been both insufficient and delayed. We provide recommendations to address these challenges and strengthen disaster risk management policies in Chile and other countries facing similar challenges.