We present the R package and web app "statcheck" to automatically detect statistical reporting inconsistencies in primary studies and meta-analyses. Previous research has shown a high prevalence of reported p-values that are inconsistent--meaning a re-calculated p-value, based on the reported test statistic and degrees of freedom, does not match the author-reported p-value. Such inconsistencies affect the reproducibility and evidential value of published findings. The tool "statcheck" can help researchers to identify statistical inconsistencies so that they may correct them. In this paper, we provide an overview of the prevalence and consequences of statistical reporting inconsistencies. We also discuss the tool "statcheck" in more detail and give an example of how it can be used in a meta-analysis. We end with some recommendations concerning the use of "statcheck" in meta-analyses and make a case for better reporting standards of statistical results.