Norms are rules that help control how independent agents behave. This paper looks at how general these rules should be to work effectively. Very specific rules are not used often, while very general rules can restrict agents too much. The researchers studied different ways to organize these rules based on their structure. They found that having a balanced level of generality in rules is important for efficiency. This can help in creating better rules for systems with multiple agents.