Well-curated data repositories enhance the discovery, access, integration, and analysis of scientific data. They maximize research impacts and ensure the accuracy of data-driven technologies. The BonaRes Repository is a FAIR and open infrastructure for soil and agricultural research data publication. Alongside this repository, we are developing DQ-Kit, a web application that automates comprehensive data quality assurance. DQ-Kit offers automated guidance on data elements that require review and confirmation. DQ-Kit checks encompass four main categories. First, it addresses formal criteria such as atomization of data, structural consistency, and other formatting issues. Second, DQ-Kit provides a summary of variables, their properties, and summary statistics. Third, DQ-Kit allows for the exploration of relationships among variables and patterns of missingness. Lastly, we are planning to implement data plausibility checks flagging variables that contain theoretically "impossible" values and values that seem empirically implausible based on existing knowledge. Initially, this functionality may be limited to soil data, where our team possesses the necessary expertise. We focus on "data fitness for use," emphasizing data suitability for specific purposes and amplifying the impact of data providers. We plan to enhance the metadata at the BonaRes Repository with DQ-Kit results, enabling seamless quality control and facilitating dataset comparisons. Ultimately, we aim to offer DQ-Kit as open-source software, inviting community contributions – including from the FAIRagro community - to its development. In summary, DQ-Kit ensures the integrity and reliability of scientific data at the BonaRes Repository and beyond, supporting various research endeavors.