Recommendations by software repositories depend on explicit or implicit models for evaluating the quality and relevance of components for programming tasks. As a step toward creating such a model for evaluating end-user web macro scripts, we have identified script characteristics that correspond to the likelihood of script reuse. For example, the likelihood of reuse increases with the number of variables and comments in the script, the number of online forum postings by the script's author, and the presence of popular keywords in the script's source code. We discuss possible applications of our results for new recommendation features.