An illustration with sample files; your own files show their own results.
BeforeResumes the parser misreads
Two columns read straight across
Contact lost in the header
Skill bars and icons
AfterRebuilt so every parser reads it
One clean column
Contact moved into the body
Plain text, nothing lost
Greenhouse Resume Checker: Check Your Sections and Contact Details
Greenhouse maps a resume onto a candidate profile, and that mapping works best when sections carry conventional names and contact details sit in plain text. A creative heading such as "My Journey" gives a parser nothing to anchor to, and a contact block built from icons or images gives it nothing to read.
The tool above detects your sections, maps them onto canonical headings, exposes the contact block as plain text and rebuilds the resume as a clean, searchable PDF, DOCX or Markdown file. The audit scores the result against five ATS pipelines, Greenhouse included. It is a local simulation, not a connection to Greenhouse.
ATS Resume Fixer: Check and Fix How ATS Reads Your Resume
Applicant Tracking Systems read a resume (or CV) as one linear text stream, and they fail in predictable ways: columns interleave, ligatures and broken fonts turn into garbage, content in form fields or images is dropped, and headers get truncated. The ATS Resume Fixer rebuilds your resume or CV as a single-column, machine-readable document, entirely in your browser. Your file never leaves your device.
What it does
Spatial linearization: an XY-cut engine finds column gutters and block gaps and flattens columns, sidebars and visual tables into one reading order.
Glyph & CMap repair: expands ligatures (fi, fl, ffi…), neutralises Private-Use-Area characters from broken CMaps, and folds exotic bullets, dashes and quotes to plain equivalents.
Artifact stripping: the output is rebuilt from text only, so images, skill bars, decorative vectors, form fields and annotations are gone by construction.
Semantic restructuring: content is sorted into canonical sections (Contact, Summary, Experience, Skills, Education, Certifications…).
Dual-target output: a searchable text PDF plus an unstyled DOCX and Markdown, ready for any parser.
Headless ATS audit: a built-in mock parser scores machine readability and projects it onto five pipelines: Workday, Taleo, Greenhouse, Lever and iCIMS.
A note on PDF/A
The PDF is a clean, searchable text PDF with ISO core fonts and a classic cross-reference table, which covers everything an ATS relies on. It is deliberately not stamped as PDF/A-1b/2b: true conformance needs colour profiles, XMP metadata and a validating toolchain that a client-side tool cannot guarantee. You get a document that parses correctly, not a badge it cannot verify.
Frequently asked questions
What does Greenhouse need to parse a resume well?
Conventional section names such as Experience, Education and Skills, and contact details as plain text. The audit checks both and reports which sections it recognised and whether the contact fields can be extracted.
Can I keep creative section headings?
You can, but a heading a parser does not recognise may not map to the right profile field. The ATS Resume Fixer maps sections onto canonical anchors, so the structure survives even when your original wording was unusual. Keep a designed version for human readers alongside the parser-friendly one.
Is this the same parser that Greenhouse runs?
No. It is an independent local simulation built from documented parsing behaviour, so it can flag likely problems but cannot reproduce Greenhouse's exact output. Treat a clean audit as a good sign, not a guarantee.
Is my resume uploaded anywhere to be checked?
No. The whole check runs in your browser and the file is never uploaded. Previewing and checking need no account; an account is needed only to spend tokens when you download the result.
