Secure Multi-Party Computation (MPC) enables private computation, but has significantly higher overhead than plaintext execution. Hybrid MPC compilers improve concrete efficiency by mapping distinct computation parts to contextually optimal MPC protocols. However, state-of-the-art systems like Silph (Chen et al., S&P’23) depend on deployment-specific cost models that are cumbersome to retune, and compute mappings via brittle heuristics or costly Integer Linear Programming (ILP), limiting sca