Developed a configurable evaluation workflow enhancement for the RapidataAI/rapidata-python-sdk, introducing a should_accept_incorrect parameter to support flexible acceptance of incorrect validations during evaluation. This feature was integrated into both the EvaluationWorkflow and EvaluationWorkflowModel, with careful propagation of the new parameter and comprehensive updates to internal documentation. The work emphasized maintainability and clarity, ensuring strong commit traceability and clear guidance for future developers. Utilizing Python and software development best practices, the enhancement enables more nuanced quality assurance and experimentation scenarios, allowing teams to tailor evaluation fidelity and risk assessment processes to specific business needs without introducing new bugs.