Data collection and cleaning workflows implement highly repetitive but extremely important processes. In this article, we describe an update to iefieldkit, a package developed to standardize and simplify best practices for high-quality primary data collection across the World Bank’s Development Impact Evaluation department. The first release of iefieldkit provided workflows to automate error checking for Open Data Kit-based survey modules, duplicate management, data cleaning, and codebook creation. This update to the package includes improved commands to document and implement data point corrections, verify the structure or contents of data using codebooks, and create replication ready data through automated variable subsetting.