Trigger-action platforms enable end-users to program their smart homes using simple conditional rules of the form: if condition then action. Although these rules are easy to program, subtleties in their interpretation can cause users to make errors that have consequences ranging from incorrect and undesired functionality to security and privacy violations. Based on prior work, we enumerate a set of nine error classes that users can make, and we empirically study the relationship between these classes and the interface design of eight commercially available trigger-action platforms. Particularly, we examine whether each interface prevents (e.g., via good design) or allows each class of error. Based on this analysis, we develop a framework to classify errors and extract insights that lay a foundation for the design of future trigger-action programming interfaces where certain classes of errors can be mitigated by technical means or by alerting the user to the possibility of an error. For instance, we identify that an analysis of a dataset of functionally-similar trigger-action rules could be used to predict whether certain types of error patterns are about to occur. We believe that this work is a first step towards trigger-action interface designs that significantly mitigate user error.