When adding dummy atoms to the optimization problem, our algorithm also adds constraints to counteract the added Cartesian degrees of freedom generated by the dummy atoms. This enables the optimization of a wide range of molecular geometries in an efficient redundant internal coordinate system. This capability renders our algorithm a highly effective and robust geometry optimizer for automated workflows that explore reactive potential energy surfaces, such as KinBot. Further, constrained optimizations, such as relaxed scans, are often used to explore aspects of the potential energy surface and are thus also part of automated workflows.