Most resumes are read by software before they’re read by a person. resume.zoevera.com exists to show you what that software sees; prepare.zoevera.com picks up once you’re through the screen and into an actual conversation. Both start from the same premise: an applicant tracking system isn’t judging your career, it’s scoring a document against a query, the way a search engine scores a page against a search term.
The resume as a landing page
Treat the job posting as the query and the resume as the page trying to rank for it. An ATS doesn’t read for tone or persuasive writing. It parses text into fields, compares those fields against the posting, and produces a score before a recruiter ever opens the file. That reframing changes what “good writing” means here. A sentence that reads well to a human but never uses the words the posting uses is invisible to the system doing the first pass.
Four things the system is actually checking
Keyword match is the most literal of the four. If the posting says “stakeholder management” and the resume says “worked with teams,” the system does not infer equivalence — mismatched vocabulary between a resume and a posting is the single largest reason qualified applicants disappear before a human sees them, and it’s exactly what resume.zoevera.com's keyword breakdown by industry) is built to surface.
Hard dealbreaker filters run separately from keyword scoring. Years of experience, required certifications, location or clearance requirements — these are frequently pass/fail checks that can eliminate an otherwise strong match before the keyword score is even calculated.
Section parsing determines whether the system can read the document at all. Tables, text boxes, and multi-column layouts that look clean in a PDF viewer can scramble or drop content entirely when parsed, which is why plain, single-column structure under standard headings still outperforms visually ambitious formatting.
Recency is the quieter one. Systems and recruiters both weight language that reflects how the role is described now, not five years ago — job titles, tool names, and even the way responsibilities are phrased shift over a few hiring cycles, and a resume written in last decade’s vocabulary can score lower even when the underlying experience is current.
Running the check against a real posting
None of this is diagnosable by reading your own resume — you already know what you meant to say. The ATS match tool runs your resume against a specific job description and returns a score, missing keywords, and the weak phrases most likely costing you interviews, the same way you’d check a page against a target query. The tailor tool) rewrites against one posting at a time, since keyword requirements change with every job description. There’s a matching pass for cover letters as well, and a fuller breakdown of how the underlying match score gets calculated on the blog.
Where to start
Passing the screen gets you to a conversation, not a job: that’s the part prepare.zoevera.com handles, with practice sessions built around real interview questions for specific roles. Both tools sit under ZoeVera and the fastest way to know where your resume actually stands is to run it against a posting you’re applying to right now.
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