Make the match legible.

The source lowercases text, extracts terms of at least three characters with its regular expression, removes listed stop words, and deduplicates terms. In an illustrative job text Python SQL Python and resume SQL, two unique job terms meet one unique resume term: Python is missing and SQL matches. These bars use one hundred fifty pixels per unique term. This is lexical guidance rather than a real applicant tracking system score or hiring prediction. The source displays at most eight missing and eight matching terms. A ten-term missing set therefore displays eight while its status can count all ten role terms. These bars use forty pixels per term. Download includes the visible lists and bullet guidance, not the complete original documents or hidden missing terms. Inspect this limitation before treating the report as exhaustive. The source recognizes nine action-word alternatives in resume sentences: build, built, led, created, improved, managed, launched, reduced and increased. One matching alternative selects guidance to keep strong verbs and add a supported measurable outcome. These bars use forty pixels per count. The code does not rewrite a bullet, validate an achievement or guarantee ATS passage. Inputs persist locally when compared.