Abstract: Quantum hardware, if successfully deployed in the future, would provide computational and communication resources unavailable in classical settings. Nonetheless, we still need as-efficient-as-possible classical simulators for quantum dynamics: both in the experimental design process for quantum hardware and in the theoretical study of potential quantum algorithms. A vast array of techniques have been developed in the last 20 years, from expensive but faithful to (too) approximate but fast.Thus, a lot of questions arise for the scientist designing such machines: which simulation method would permit the study of the particular dynamic of interest, how most efficiently to model the environmental noise, and crucially, how to couple an efficient simulation of one type of quantum dynamics with a completely different methodology that has to be used for a different part of the hardware. Our answer to these issues is the QuantumSavory.jl family of packages, now an integral part of the NSF Center for Quantum Networks virtual testbed. QuantumSavory provides for a formalism-agnostic way to describe the quantum hardware you want to study. Then it dispatches to the appropriate backend simulator: QuantumClifford.jl for Clifford circuits and error correction; BPGates.jl for even faster simulations of entanglement purification; QuantumOptics.jl for general purpose wavefunction simulations; and other special-purpose packages that can be easily plugged into the interface provided by QuantumSavory. QuantumSymbolics.jl is another crucial tool enabling the formalism-agnostic simulator: a symbolic quantum-focused computer algebra system. In QuantumSymbolics one can operate on the "Platonic" representation of various quantum states and processes before converting them to a special-purpose numerical object to be used by the backend simulator (e.g. a density matrix for QuantumOptics or a tableau for QuantumClifford). Of course, these tools would not be complete without support for discrete event simulations (e.g. in quantum networks) and a rich library of plotting recipes for visualization and debugging, of which we provide a brief overview at the end.