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Resume Checker

Structure, keyword match against a job ad, and parse warnings.

What it does. This checks structure and overlap: whether the expected sections exist, whether achievements carry numbers, whether verbs are strong, and which terms from the job description are missing. It does not judge whether the writing is good — that needs a language model, and there is no backend here to run one.
Runs in your browserNothing uploadsNo signupWorks offline

How to use Resume Checker

  1. Paste your CV text — copy it out of your PDF, which also tests how it parses.
  2. Paste the job description alongside it.
  3. Work through the flagged items and the missing keywords.

What it checks

  • Sections — experience, education, skills, contact details.
  • Contactability — an email and a phone number that a parser can find.
  • Quantification — how many bullets contain a number.
  • Verb strength — bullets starting with "responsible for" or "helped with" rather than a verb.
  • Length — word count against the one-to-two page norm.
  • Keyword overlap — terms in the job description that do not appear in your CV.

The keyword comparison is the most useful single output, and it is also the one to use with judgement — see below.

Keyword matching, used honestly

Recruiters do search an ATS by keyword, so a CV that never uses the term the posting uses is genuinely harder to find. If the ad says "stakeholder management" and your CV says "worked with clients", that is worth changing.

What this is not is a licence to paste the job description into your CV. Keyword stuffing is obvious to the human who reads it next, and white text on a white background is an old trick that modern systems extract and recruiters notice.

The rule that keeps it honest: only add a keyword if it describes something you actually did. If it does, use the posting’s wording for it. If it does not, its absence is information rather than a problem.

Numbers are the highest-yield change

The difference between a weak bullet and a strong one is almost always a number.

"Improved onboarding" says nothing. "Cut onboarding from 5 days to 2 across 40 new hires" says what changed, by how much and at what scale — and it is not a claim anyone can make vaguely.

If you do not have exact figures, an honest approximation with the basis stated is fine: "roughly a third fewer support tickets in the quarter after launch". Invented precision is worse than an honest range.

Frequently asked questions

Does this give me an ATS score?

No, and be sceptical of tools that do. There is no single ATS and no published scoring model, so any number is invented. This reports specific, checkable things instead: missing sections, missing numbers, weak verbs, keyword gaps.

Should I copy keywords from the job description?

Only for things you actually did. If the ad says "stakeholder management" and you did that but called it "worked with clients", use their wording. Adding skills you do not have is obvious to the human who reads it next.

Does white text keyword stuffing work?

No. Text extraction pulls it out regardless of colour, and recruiters see it. It reads as an attempt to deceive, which is a worse outcome than a missing keyword.

How long should a CV be?

One page early career, two pages with substantial experience. Three only for academic CVs and senior technical roles where publications or projects genuinely require it.

Is my CV or the job description uploaded?

No. Everything is analysed in your browser. A CV is a dense package of personal data and a poor thing to hand to a free service.