<p>Shock-fitting methods provide highly accurate solutions for compressible flows by explicitly tracking discontinuities, yet their broader adoption has been constrained by implementation complexity, extensive manual preprocessing, and sensitivity near geometric singularities. This work presents modular and robust algorithms for two-dimensional shock-fitting simulations, addressing both software-level automation and solver-level improvements. A new Python-based preprocessing toolkit automates key setup stages–such as shock point extraction from shock-capturing solutions, curve fitting of initial shock lines, mesh generation in Triangle format, and configuration management, thereby enabling reproducible workflows and improving the usability of the base solver. At the algorithmic level, new treatments for shock–geometry interaction are introduced to enhance stability and accuracy. Two additional classes of special points (WDGX and WDGY) are defined to correctly represent shock initiation and reflection from geometric corners, while the formulation of the regular reflection (RR) point is revised to ensure consistent curvature evolution. These refinements eliminate numerical inconsistencies previously observed near corners and yield more physically faithful shock structures. The enhanced framework is validated on multiple benchmark configurations, including transonic airfoil flows, supersonic wedges, and steady reflection problems, demonstrating stable and accurate performance across diverse flow regimes. The implementation and associated scripts are released under an open-source license to promote reproducibility and future methodological development in computational fluid dynamics.</p>