In contrast, there has been little advance in the development and validation of best practices associated with the bioinformatics processing of wocDNA COI metabarcoding data (but see Yang et al., 2020 for error reduction). Outside of taxonomic assignment, discussion of customising or parameterising tools for the purposes of working with wocDNA COI metabarcoding is very rare, with most papers simply reporting using tools with default settings. Our review has revealed heterogeneity in the number of tasks, the order of these within pipelines, and the tools used to implement them, along with a lack of even basic adaptations to the COI metabarcode for most of the papers. The majority of available software and resources for metabarcoding bioinformatics are still those that have been developed around the 16S rRNA gene (the primary target for microbiome metabarcoding), including the most popular software packages (e.g. USEARCH) and sets of wrapper scripts (e.g. QIIME, OBItools).  While in many cases these methods may carry over to COI without issue, we observe very few studies that report consideration or analysis that assesses or validates the suitability of software choices for COI. These issues suggest that the expansion of wocDNA COI metabarcoding is proceeding at a pace and manner that could lose sight of or simply ignore the challenges inherent in producing high‐quality data and reproducible methods (Baker et al., 2016; Zinger et al., 2019), and lose out on the potential for exploiting the benefits of the COI marker for wocDNA metabarcoding of Metazoa.