Foundational assumptions under legal systems come adrift with innovation in non-law disciplines. In an effort towards improved understanding of what is going on (and what can be done) we turn to agent-based modeling as a tool. We use the KEI project for our use case, apply Holland’s ECHO framework as legal requirements engineering tool and use NetLogo as platform for implementation (resulting in an application we call Epiframer). We study parameter-change induced behavioral dynamics in the resulting artificial society. Findings are in two tiers: (i) on the role of the law in a multi-force field and (ii) on the role of institutions (also: sibling disciplines) for informing specialist legal professionals. We submit epiframer’s assumptions for diverse-disciplinary scrutiny as a closure. We have not yet reached a level that warrants the deployment of statistical learning methods onto data provided by simulation runs and are aware that such an approach has — where legal requirements engineering events tend to be sparsely punctuated — limited added value for legal requirements engineering situations anyway. With De Marchi (2005) our claim is that under such conditions computational, mathematical and, indeed, qualitative methods have complementary uses.