POST STSS is a method of computing short-text semantic similarity (i.e. semantic textual similarity) that uses a bag-of-words approach and relies on string overlap measures and lexical distributional semantics. Similarities between individual words are weighted according to their parts of speech. The optimal POS weights are determined using an incremental, hill climbing-based technique. The only language-specific resource POST STSS requires is a part-of-speech tagger (and optionally a lemmatizer), making it applicable to most languages. Further information about the algorithm can be found in the 2015 ComSIS paper. POST STSS is implemented within the STSFineGrain package.