We describe a coherent strategy and set of tools for reconstructing the fundamental theory of the TeV scale from LHC data. We show that On-Shell Effective Theories (OSETs) effectively characterize hadron collider data in terms of masses, production cross sections, and decay modes of candidate new particles. An OSET description of the data strongly constrains the underlying new physics, and sharply motivates the construction of its Lagrangian. Simulating OSETs allows efficient analysis of new-physics signals, especially when they arise from complicated production and decay topologies. To this end, we present MARMOSET, a Monte Carlo tool for simulating the OSET version of essentially any new-physics model. MARMOSET enables rapid testing of theoretical hypotheses suggested by both data and model-building intuition, which together chart a path to the underlying theory. We illustrate this process by working through a number of data challenges, where the most important features of TeV-scale physics are reconstructed with as little as 5 inverse femtobarns of simulated LHC signals
