Technical transparency · 29 October 2026

    FreeCVAudit accuracy benchmark

    We tested a synthetic corpus of 40 CVs covering text-based PDFs, simple multi-column and table layouts, Word documents, raster scans and four languages. We publish the generation method, individual outcomes, missed issues and limitations.

    Disclosure: This evaluation was conducted by FreeCVAudit, not commissioned or independently reviewed by a third party. Anyone can regenerate the synthetic examples and check them against the live tool. The full production analysis code is not publicly released, so an exact offline rerun requires access to that code.

    Measurement run: · Free audit methodology

    Measured results

    40

    Synthetic CV files

    34/34

    Seeded issues detected by a rule

    32/34

    Seeded issues visible to users

    4/4

    Image-only scans flagged (free audit)

    0 seeded issue(s) missed by their specific detection rule; 2 additional seeded issue(s) triggered an internal rule but did not appear in the 3–4 visible findings. 0 file(s) produced extraction exceptions. 6 of 6 unseeded baseline CV(s) still received warnings. Baseline files are not professionally validated error-free CVs, so those warnings must not be described as measured false positives.

    What was tested

    • 18 generated text PDFs, including standard pages, simulated two-column text and table-like grid lines.
    • 18 generated DOCX files, including standard paragraphs and Word tables.
    • 4 raster-image-only PDFs containing no embedded selectable text.
    • English, French, Arabic and Spanish examples, with controlled changes to contact details, CV sections, action verbs, numbers, bullets, length and repetitive wording.

    What was not tested

    • Actual employer ATS platforms, interview rates, job outcomes, or the probability of passing any ATS.
    • Gemini OCR transcription fidelity for paid revisions. The production service can OCR low-text scans after payment, but no paid OCR call was made during this free-audit benchmark.
    • Commercial or externally sourced CV documents, real photos, handwriting, watermarks or severely degraded scans.
    • Word layout fidelity and visual accessibility beyond the extractor's text output. The synthetic PDF column and table cases do not establish performance on all complex CV layouts.

    Reproduce the test

    All samples are synthetic. Download the JavaScript generator and run it with Node.js to recreate the 40 PDF/DOCX files. The manifest identifies the deliberately injected issue in each file; the results JSON contains document hashes, extractor outcomes, issue detection and the findings actually displayed. To independently verify the live behavior, upload any fixture on the homepage and compare its free-audit findings to the corresponding row below. No payment is required for that check.

    node generate-corpus.mjs ./fixtures

    The automated benchmark runs with the application's production extractor and deterministic audit engine in the deployment build. Runtime, dependencies and source hashes are recorded in the JSON report. Generation does not access customer data.

    Results for each CV

    “Detected, not shown” means the seeded issue matched a production signal but did not rank among the audit's limited number of displayed findings. Download any sample to inspect it.

    Individual document types, seeded issues, extraction and audit results
    FileFormat / layoutLanguageDeliberately seeded issueResultExtraction
    p01.pdfPDF · standardenNo deliberately seeded issueBaseline (not graded)Text marker recovered
    p02.pdfPDF · standardencontact detailsShown in free auditText marker recovered
    p03.pdfPDF · standardenmissing sectionsShown in free auditText marker recovered
    p04.pdfPDF · standardenduties not valueShown in free auditText marker recovered
    p05.pdfPDF · standardenno quantificationShown in free auditText marker recovered
    p06.pdfPDF · standardenbullet densityShown in free auditText marker recovered
    p07.pdfPDF · standardenlength imbalanceShown in free auditText marker recovered
    p08.pdfPDF · standardenrepetitive phrasingShown in free auditText marker recovered
    p09.pdfPDF · standardenNo deliberately seeded issueBaseline (not graded)Text marker recovered
    p10.pdfPDF · standardencontact detailsShown in free auditText marker recovered
    p11.pdfPDF · two-columnsenmissing sectionsShown in free auditText marker recovered
    p12.pdfPDF · two-columnsenduties not valueShown in free auditText marker recovered
    p13.pdfPDF · two-columnsenno quantificationShown in free auditText marker recovered
    p14.pdfPDF · two-columnsenbullet densityShown in free auditText marker recovered
    p15.pdfPDF · tableenlength imbalanceShown in free auditText marker recovered
    p16.pdfPDF · tableenrepetitive phrasingShown in free auditText marker recovered
    p17.pdfPDF · tableenNo deliberately seeded issueBaseline (not graded)Text marker recovered
    p18.pdfPDF · tableencontact detailsShown in free auditText marker recovered
    d01.docxDOCX · standardenNo deliberately seeded issueBaseline (not graded)Text marker recovered
    d02.docxDOCX · standardencontact detailsShown in free auditText marker recovered
    d03.docxDOCX · standardenmissing sectionsShown in free auditText marker recovered
    d04.docxDOCX · tableenduties not valueShown in free auditText marker recovered
    d05.docxDOCX · standardenno quantificationShown in free auditText marker recovered
    d06.docxDOCX · standardenbullet densityShown in free auditText marker recovered
    d07.docxDOCX · standardenlength imbalanceShown in free auditText marker recovered
    d08.docxDOCX · tableenrepetitive phrasingShown in free auditText marker recovered
    d09.docxDOCX · standardfrNo deliberately seeded issueBaseline (not graded)Text marker recovered
    d10.docxDOCX · standardfrcontact detailsShown in free auditText marker recovered
    d11.docxDOCX · standardfrmissing sectionsShown in free auditText marker recovered
    d12.docxDOCX · tablefrduties not valueShown in free auditText marker recovered
    d13.docxDOCX · standardarno quantificationDetected, not shownText marker recovered
    d14.docxDOCX · standardarbullet densityDetected, not shownText marker recovered
    d15.docxDOCX · standardarlength imbalanceShown in free auditText marker recovered
    d16.docxDOCX · tablearrepetitive phrasingShown in free auditText marker recovered
    d17.docxDOCX · standardesNo deliberately seeded issueBaseline (not graded)Text marker recovered
    d18.docxDOCX · standardescontact detailsShown in free auditText marker recovered
    s01.pdfScanned PDF · rasterenimage onlyShown in free auditImage-only warning
    s02.pdfScanned PDF · rasterenimage onlyShown in free auditImage-only warning
    s03.pdfScanned PDF · rasterenimage onlyShown in free auditImage-only warning
    s04.pdfScanned PDF · rasterenimage onlyShown in free auditImage-only warning

    Interpretation and limitations

    Each sample has one controlled target alteration or no deliberately planted issue. The detection measurement tests whether the corresponding rule fires; the visible measurement tests whether it is among the three or four highest-priority findings shown to the user. This is not comprehensive human annotation, and the measured ratio is not general CV-audit accuracy, sensitivity, specificity or an ATS pass rate.

    The free tool analyses extracted text, not PDF visual geometry. It cannot verify visual reading order, hidden text, tables reconstructed incorrectly, or a particular recruitment platform's interpretation. English and French section patterns are better represented in the current heuristics than Arabic or Spanish; a multilingual document can be misclassified. Internal diagnostic scores are capped and do not represent calibrated probabilities of recruitment success.

    For scanned documents, the free audit reports the absence of text. Following payment, the separate Gemini-powered workflow can transcribe the scan before generating a revised CV. That capability should not be confused with the free audit's scan detection, and its accuracy requires a separate verified evaluation with transcription-level ground truth. No OCR accuracy percentage is claimed here.

    Benchmark operator: FreeCVAudit.com · synthetic input set · version 2026-10-29. Report a discrepancy or request a re-test.