The commonly accepted definition of research software is "Any software created during the research process or for a research purpose". It can come in many format and could be developed for different applications such as artificial intelligence (AI)/machine learning (ML) models with Python, data visualization tools with Jupyter notebook, or data analysis code with R.

The FAIR (Findable, Accessible, Interoperable, Reusable) Principles for Research Software (FAIR4RS Principles) are a set of high-level instructions established by the research software community to make software reusable. Making research software FAIR means complying with each of the 17 FAIR principles.

Just install codefair from the GitHub marketplace on your software’s GitHub repository. By communicating with you through GitHub issues and submitting pull requests, codefair will then make sure that your software follows best coding practices, provides metadata in standard format, includes a license file, is archived on Zenodo, and much more to align with the FAIR4RS principles.

Currently, codefair helps make software FAIR by following the FAIR Biomedical Research software (FAIR-BioRS) guidelines. Therefore it is design mainly for biomedical research software. However, most of the steps of the FAIR-BioRS guidelines are applicable to any research software irrespective of the field of research. Therefore, anyone developing a research software can use codefair.