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Within code documentation – each script should have at the top a description of what the script does. Some people also have a note identifying the authors of the script. Some scripts are short, but others are complicated. For complicated scripts you might break it into sections with a description of the function or purpose of each section. Finally, sometimes code is straightforward and requires little explanation; other times it gets complicated or confusing. If someone looking over your shoulder wouldn't likely immediately understand what you are writing, add a few line-level notes of explanation. Your future self will likely appreciate it, but also explaining your logic might save you from making as many errors. Here is a place where collaborators can be helpful. In fact, I heard about on twitter (but can't currently point to) studies find that collaborating on code is more efficient and less error prone than double coding (i.e. having two people code independently to see if they produce the same results). Having one person write the code and document it well enough that a collaborator can understand it is one model. Another would be for the collaborator to write the documentation.
Some web resources for documentation:
https://blogs.oracle.com/datascience/how-to-write-production-level-code-for-data-science-projects
https://towardsdatascience.com/why-you-should-document-your-work-as-a-data-scientist-a265af8a373
https://medium.com/@andrewgoldis/how-to-document-source-code-responsibly-2b2f303aa525