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Data management plans (DMPs) are required from researchers seeking funding from federal agencies in the United States. Ideally, DMPs disclose how research outputs will be managed and shared. How well DMPs communicate those plans is less understood. Evaluation tools such as the DART rubric and the Belmont scorecard assess the completeness of DMPs and offer one view into what DMPs communicate. This paper compares the evaluation criteria of the two tools by applying them to the same corpus of 150 DMPs from five different NSF programs. Findings suggest that the DART rubric and the Belmont score overlap significantly, but the Belmont scorecard provides a better method to assess completeness. We find that most DMPs fail to address many of the best practices that are articulated by librarians and information professionals in the different evaluation tools. However, the evaluation methodology of both tools relies on a rating scale that does not account for the interaction of key areas of data management. This work contributes to the improvement of evaluation tools for data management planning.