Curated by Vinod Kumar Jain & Amit Jain · All Frontier Global · free, no login
Paste your resume and the job description. This compares them entirely in your browser — nothing is uploaded, nothing is stored — and reports the terms you share, the frequent description terms you are missing, and whether the sections a reader expects are present. It matches words, not merit. Human readers decide, and keyword-stuffing is visible, counterproductive and dishonest.
What it actually does
Tokenises both texts — lowercases, strips punctuation, drops a list of common English words that carry no signal.
Counts term frequency in the job description and takes the most frequent remaining terms as the ones the description emphasises.
Reports overlap — which of those emphasised terms appear anywhere in your resume, and which do not.
Checks for sections a human reader and most parsers expect: experience, education, skills and a contact route.
Match rate = emphasised description terms found in the resume ÷ emphasised terms considered × 100. It is a crude measure and is presented as one.
Honest limits
This matches words, not merit. A high score means your vocabulary overlaps the description’s. It says nothing about whether you can do the job, and no employer decides on this number.
Never keyword-stuff. Padding a resume with terms you cannot substantiate fails at the first human reading and at the first interview question. If a term is missing because you lack the experience, the honest fix is to say so or to gain it — not to insert the word.
No applicant tracking system is modelled. These systems differ, most rank far less mechanically than folklore suggests, and none of them publishes its ranking. Anyone selling you a score against a named system is guessing.
Stemming is not applied. “Manage” and “management” count separately, which will overstate what you are missing. Read the list, do not obey it.
Formatting, file type and layout matter to real parsers and are not examined here at all.
Sources
None. No applicant tracking system, ranking model or recruiter survey is consulted, embedded or modelled — the comparison is plain word-frequency arithmetic run in your browser on the two texts you pasted. Nothing is uploaded and nothing is stored.