Upload your resume and paste a job posting. Get your match score, missing keywords, and specific gaps in about 30 seconds.
About This Tool
The comparison is per posting, not general. A resume is not strong or weak on its own, it is a match or a mismatch for one job. Two openings with the same title routinely score differently against the same document, because the companies describe the work in different words. “Demand generation” and “paid advertising” mean the same thing to a person and different things to a keyword search.
It is built for people applying to roles where postings use specific vocabulary: nurses, software engineers, accountants, project managers, and the other roles with a role keyword guide. If you are sending a cover letter with the same application, the cover letter checker runs the same comparison on that.
Built from real job postings, not generic AI advice
The same experience, written so a keyword scan can see it. Illustrative, from the software engineer guide.
Before
Built web applications and worked with APIs
After
Architected React + FastAPI platform serving 400k MAU; introduced GraphQL federation layer reducing mobile API payload 60% and cutting Time to Interactive from 4.1s to 1.8s
The Dealbreaker Scan
From the posting
Whether the role is remote, hybrid or onsite, and any travel, security clearance, visa sponsorship or pay range the posting states, shown next to your score so you do not have to dig for them.
Against your resume
Items the posting marks as required, such as years of experience, a license, a clearance or a named technology, that your resume shows no evidence of. When two or more are missing, they are listed before your score as something to weigh before you apply.
The job description is split into skills, tools and qualifications, most important first. Each one is checked against your resume for direct evidence or clearly equivalent experience, and ambiguous cases count as missing, so the score understates rather than flatters. The percentage is matched divided by the total, minus five points for each missing item from the job's top five skills or top three tools, capped at 94 and floored at 8. The same inputs give the same score.
Read the missing list as a question, not a task list: a term is worth adding only where you have done the work and your resume describes it in different words. A high score is not an interview. It means the wording lines up, and a person still reads the resume.
Our match score is not an employer's ATS score.
It is our own measurement, calculated by the method above and published in full. It is not a Workday, Greenhouse, iCIMS or Lever score, we have no access to those systems, and no vendor discloses one. The full method, step by step · What an ATS actually does
✓ This is for you if…
✗ This is NOT for you if…
ChatGPT reads your resume and suggests improvements from general knowledge. ZoeVera does one narrower thing: it takes a specific job description, extracts its skills, tools and qualifications, classifies each one as matched or missing against your resume, and returns the ratio as a score. The same extraction and the same rule run every time, at temperature 0, so the score does not drift between runs. You also get a skip signal when the role is a clear mismatch, and the posting's logistics — remote, visa, pay — pulled out for you. The whole method is published on the about page.
The analysis shows your ATS match score, the exact keywords missing from your resume against that job description, your bullet strength score, the weak phrases a reader has to work past, and a skip signal if the role is a clear mismatch. It also pulls job logistics automatically — remote vs. onsite, travel requirements, clearance needs, visa sponsorship, and pay range — so you're not hunting through the posting yourself. No signup required.
Your resume and job description are used only to generate your analysis and are not stored, sold, or used to train any AI model. Each session is independent.
Pricing
Up to 20 analyses in 24 hours
Up to 100 analyses over 30 days
Unlimited analyses for 30 days
Everything behind the checker, one page per question.
3,518 postings from 81 companies, counted term by term from the public Greenhouse job board API, mostly US technology companies. How this was counted, and what it cannot tell you →
Software Engineer Keywords →
1,360 postings from 72 companies
Marketing Keywords →
347 postings from 62 companies
Cybersecurity Keywords →
212 postings from 51 companies
Accountant Keywords →
123 postings from 49 companies
Account Executive Keywords →
921 postings from 52 companies
Product Manager Keywords →
421 postings from 62 companies
DevOps & SRE Keywords →
134 postings from 41 companies
How ATS screening works →
Parsing, recruiter search, knockout rules, ranking — and the steps that follow from them
Reading a keyword gap →
What a missing-keyword list is, and which entries are worth acting on
What an ATS match score means →
What a good score is, and why no employer publishes one to beat
Tailor your resume to a job description →
Step by step, for one specific posting
Passing ATS but no interviews →
What a match score cannot see, measured against 1,360 postings
What recruiters look for →
What gets read once a resume comes back in a search
Resume keywords by industry →
Keyword categories across every major vertical
Cover letter checker →
Five-dimension score, and whether the letter adds anything the resume does not
ZoeVera is an independently built tool, running since March 2026, with no team of recruiters, no proprietary hiring dataset and no access to any employer's applicant tracking system. What it has instead is checkable: a published scoring method, and keyword figures from public postings with their limits stated. Who built this and how the score is calculated · ZoeVera on LinkedIn