DynSem is a domain-specific language for concise specification of the dynamic semantics of programming languages, aimed at rapid experimentation and evolution of language designs. To maintain a short definition-to-execution cycle, DynSem specifications are meta-interpreted. Meta-interpretation introduces runtime overhead that is difficult to remove by using interpreter optimization frameworks such as the Truffle/Graal Java tools; previous work has shown order-of-magnitude improvements from applying Truffle/Graal to a meta-interpreter, but this is still far slower than what can be achieved with a language-specific interpreter. In this paper, we show how specifying the meta-interpreter using scope graphs, which encapsulate static name binding and resolution information, produces much better optimization results from Truffle/Graal. Furthermore, we identify that JIT compilation is hindered by large numbers of calls between small polymorphic rules and we introduce rule cloning to derive larger monomorphic rules at run time as a countermeasure. Our contributions improve the performance of DynSem-derived interpreters to within a factor of 1.5-4.5 (in most cases) of a handwritten language-specific interpreter, and to within an order of magnitude of native code.