This paper describes the implementation and testing of our concept of adaptable rubrics, defined as analytical rubrics that arrange assessment criteria at multiple levels that can be expanded on demand. Because of its adaptable nature, these rubrics cannot be implemented in paper formats, neither are they supported by current Learning Management Systems (LMS). The main contribution of this work involves the adaptable capability of different levels of detail, which can be expanded for each rubric criterion as needed. Our rubrics platform provides specialized and intuitive tools to create and modify rubrics as well as managing metadata to support learning analytics. As an example of a practical assessment situation, a case study on Mechanical Computer Aided Design (MCAD) systems training is presented. The validation process in this scenario proved the effectiveness of our adaptable rubric platform for supporting formative assessment in a multifaceted and complex field such as MCAD. The system also showed the potential of collecting user interaction metadata, which can be used to analyze the evaluation process and guide further improvements in the teaching strategy.