The reproducibility of computational pipelines is an expectation in biomedical science, particularly in critical domains like human health. In this context, reporting next-generation genome sequencing methods used in precision medicine spurred the development of the IEEE 2791-2020 standard for Bioinformatics Analyses Generated by High-Throughput Sequencing (HTS), known as the BioCompute Object (BCO). Championed by the USA’s Food and Drug Administration, the BCO is a pragmatic framework for documenting pipelines; however, it has not been systematically assessed for its reproducibility claims. This study uses the PRIMAD model, a conceptual framework for describing computational experiments for reproducibility purposes, to systematically review the BCO for depth and coverage. A meticulous mapping of BCO and PRIMAD elements onto a published BCO use case reveals potential omissions and necessary extensions within both frameworks. This underscores the significance of systematically validating claims of reproducibility for published digital objects, thereby enhancing the reliability of scientific research in bioscience and related disciplines. The associated publication for this study can be found on arXiv at: http://arxiv.org/abs/2412.07502 This study, along with its associated artifacts, is reported as a RO-Crate, providing a structured reporting approach.