Humans categorize the experience they encounter in various ways, which is mirrored, for instance, in grammatical gender systems of languages. In such systems, nouns are grouped based on whether they refer to masculine/feminine beings, (non-)humans, (in)animate entities, or objects with specific shapes. Languages differ greatly in how many gender assignment rules are incorporated in gender systems and how many word classes carry gender marking (gender agreement patterns). It has been suggested that these two dimensions are positively associated as numerous assignment rules are better sustained by numerous agreement patterns. We test this claim by analyzing the correlated evolution (Continuous method in BayesTraits) and making the causal inferences about the relationships (phylogenetic path analysis) between these 2 dimensions in 482 languages from the global Grambank database. By applying these methods to linguistic data matched to phylogenetic trees (a world tree and individual families), we evaluate whether various types of gender assignment rules (semantic, phonological, and unpredictable) are causally linked to more gender agreement patterns on the global level and in individual language families. Our results on the world language tree suggest that semantic rules are weakly positively correlated with gender agreement and that the development of agreement patterns is facilitated by different rules in individual families. For example, in Indo-European languages, more agreement patterns are caused by the presence of phonological and unpredictable rules, while in Bantu languages, the driving force of agreement patterns is the variety of semantic rules. Our study shows that the relationships between agreement and rules are family-specific and yields support to the idea that more distinct rules and/or rule types might be more robust in languages with more pervasive gender agreement.