Is this job posting worth your time?

Paste a posting. HireProof scores how closely its wording matches postings labelled as ghost jobs — listings put up with no real intent to hire. Everything runs in this browser; nothing is uploaded.

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Try an example:

Result

Paste a posting on the left and the score appears here as you type.

How it works

Five steps, on text you can edit

The same five stages the scorer runs, on a line you can change.

    Model card

    What this model is, and what it is not

    Every number here is read from model.json. Retraining updates this page; nothing on it is typed by hand.

      What it reads

      Wording only. It cannot see how long a posting has been up, whether it has been reposted, or anything about the company — which are the strongest ghost-job signals there are. It is reading the advert, not checking the job.

      SignalWeightDirection

      Where it gets things wrong

      • A well-written ghost posting. A listing put up with no intent to hire, but written carefully, reads like any other careful listing. The model has no way to tell them apart.
      • A badly-written real job. Plenty of genuine postings are vague and jargon-heavy, especially from small employers without a recruiter. Nothing here distinguishes bad writing from bad faith.
      • Short postings. Under about 80 words there is too little text for the signals to mean anything.
      • Tech-sector wording. Most labelled postings are software and office roles. Trades, healthcare, hospitality and academia phrase things differently.
      • One person's judgement. Every label reflects one reader's call, so the model inherits their blind spots along with their reasoning.
      • English only. The phrase lists are English; anything else scores as though the wording were missing.