The checklist that reviewers for the Journal of Open Source Software use is helpful for software creators, too; see if your software meets their criteria for well-documented, runnable academic software.
This article by Raghupathi, Raghupathi, and Ren (p.6) features a rubric they used for a large-scale reproducibility study, specifically looking at whether a paper's methods, data processing, and experiment techniques are reproducible. The criteria are also useful for self-assessment.
ReScienceC is a collaborative, open source journal focused entirely on replicating the results of previously published computational research papers. The journal's articles give readers a sense of many common issues that prevent experiments from being reproduced
This resource from Library Carpentries is divided up by discipline. Each lesson has a set of ten ideas and exercises to help users in fields ranging from nanotechnology to music to assess their tools, workflows, and publications for FAIR-ness
The Turing Way is "handbook to reproducible, ethical and collaborative data science." It's an ongoing project written by collaborators across the world and incorporates practical software instruction as well as larger-picture advice about how to collaborate with others and design ethical projects.
The Practice of Reproducible Research presents concrete examples of how researchers in the data-intensive sciences are working to improve the reproducibility of their research projects. In each of the thirty-one case studies in this volume, the author or team describes the workflow that they used to complete a real-world research project. Authors highlight how they utilized particular tools, ideas, and practices to support reproducibility, emphasizing the very practical how, rather than the why or what, of conducting reproducible research. Part 1 provides an accessible introduction to reproducible research, a basic reproducible research project template, and a synthesis of lessons learned from across the thirty-one case studies. Parts 2 and 3 focus on the case studies themselves. The Practice of Reproducible Research is an invaluable resource for students and researchers who wish to better understand the practice of data-intensive sciences and learn how to make their own research more reproducible.