Steel frames are gaining prominence in the construction industry for their practical advantages and remarkable structural performance. As the demand for cost-effective frame designs continues to grow, the need for innovative approaches for designing frames has become vital. Previous research has demonstrated the effectiveness of algorithm-based optimization techniques for the cost-effective design of steel frames. However, the inherent complexity of these methods hampers practical implementation and industrial adoption. Remarkably, a notable gap exists in prior research-the absence of parametric investigations on design variables of cost-optimized steel frames. This gap not only conceals the uncharted structural behavior of optimized frames but also holds the potential to empower engineers with the ability to optimize designs without relying on complex techniques. Consequently, this study endeavors to bridge this gap by developing a user-friendly tool for cost-effective design optimization of compact steel beam-column sections and utilize it to develop novel parametric trends. The study exclusively focuses on compact sections to attain full plastic moment capacity, a pivotal factor in maximizing cost optimization. The tool, integrated seamlessly into the MS Excel environment, mathematically models the steel beam-column design and optimizes it using the evolutionary algorithm (EA). The results unveil remarkable cost savings, reaching a staggering 28.95% and 35.82% for Examples 1, 2, respectively. Hereafter, a comprehensive parametric analysis is performed that reveals critical trends for design variables such as web depth, grade of steel, flange, and web slenderness ratios. The findings present valuable insights and optimal ranges for cost reduction through the selection of depth, geometric configurations, web and flange slenderness ratios, unbraced lengths, and material strength. Engineers can leverage these trends to practically optimize cost efficiency and make informed decisions when designing steel frames.