Blockchain technology transformed multiple sectors by enabling security, transparency, and decentralization. Yet, evaluating the quality of blockchain-based systems remains a complex task due to their distributed nature and the absence of specific standards. In this context, this study proposes a sociotechnical research design for the development and evaluation of an intelligent platform that supports quality assessment in blockchain systems. The solution integrates a curated catalog of software quality metrics aligned with ISO/IEC 25010 and a chatbot powered by Retrieval-Augmented Generation (RAG) that assists researchers and practitioners in identifying and applying appropriate metrics. Grounded in the Design Science Research (DSR) methodology, the study combines technical and social analyses to assess aspects such as efficiency, latency, usability, and perceived usefulness. The work contributes by presenting a methodological framework and an intelligent artifact that foster standardization, transparency, and collaborative knowledge building in the evaluation of blockchain quality.