This is a set of basic guidelines to follow when assessing a manuscript for peer review in STEM fields. Information was compiled from several sources including The American Chemical Society (ACS) Reviewer Lab, the Public Library of Science (PLoS) Reviewer center and PREreview guidelines and code of conduct. \cite{lab,center,review}Before you pick an article to review:Is the research in your field of research or expertise?It is important to have some experience or working knowledge of the field in order to write substantive feedback that authors can include in their manuscripts.Do you have any conflicts of interest?Conflicts of interest influence your ability to give impartial feedback. If you answer yes to any of these questions you should not review the manuscript.Are you close friends with the authors?Are you from the same institution?Do you directly compete with the authors?Do you have a contentious relationship with the authors.Have you collaborated with the authors in the last 5 years?Would you benefit financially from the publication of this work?Understand your biasesOur biases emerge when our environment shapes the way we think about certain people, places or things. Everyone has some level of bias however, is important to not let our biases influence our ability to give reasonable and impartial feedback for scientific work. Here we list a few biases discussed in the ACS Reviewer Lab. \cite{lab}Ethnic and Gender Biases – the assumption that certain genders or ethnic backgrounds produce research that requires additional scrutiny.Geographic bias – the assumption that research that comes from certain countries is of higher or lower quality.Model Bias – The assumption that certain models are better than others for studying or understanding natural phenomena.Positive Bias – The assumption that research with a positive result better in quality than negative results which are scrutinized more carefully.Prestige bias – the assumption that research from known universities is better than research from institutions that are not well recognized.