Tailor Your Resume to the Job Description

How ATS keyword matching actually works

Almost every mid-size and large US employer routes applications through an applicant tracking system — Workday, Greenhouse, Lever, iCIMS, and Taleo cover most of the market. Two things happen to your resume there. First, the system parses it: it reads the text and tries to sort it into fields like contact info, work history, education, and skills. Second, it becomes searchable: when a recruiter opens the requisition, they filter the applicant pool by the skills and titles the hiring manager asked for — "SQL", "stakeholder management", "B2B SaaS". Resumes that never mention those terms simply do not appear in the filtered list, regardless of how qualified the person is.

The practical takeaway: mirroring the exact vocabulary of the job description is not gaming the system — it is translation. You may write "built churn-prediction models"; the posting says "machine learning". A human would connect those; a keyword filter often will not. This tool automates that comparison: it extracts the skills, tools, and recurring phrases from the posting, then checks each one against your resume text.

How to use the tool

Copy the entire job posting — responsibilities, requirements, and preferred qualifications — and paste it into the first box. Then open your resume, select all, and paste the plain text into the second box. Pick the closest role family so the built-in skill lexicon is weighted toward your field (software engineering, product, data, marketing, or a general list). The report shows your coverage of the required keywords, a per-keyword match table with where each match was found, density warnings, and an ATS format self-check for the file itself.

A worked example

Say the posting for a data analyst role lists "Required: SQL, Python, data visualization, A/B testing" and "Preferred: dbt, Snowflake". Your resume mentions SQL three times and Python twice — good. It says "built dashboards" but never the phrase "data visualization", and A/B testing appears nowhere. Coverage: 2 of 4 required keywords, 50%. The fix is not to sprinkle "A/B testing" randomly — it is to rewrite one honest bullet: "Designed and analyzed A/B tests for the onboarding flow, lifting activation 12%", and to rename the dashboard bullet to use the posting's own phrase. Re-run the check and coverage jumps to 100% of required keywords — with bullets that are also stronger for the human reader.

Keywords get you found. Bullets get you interviews.

A keyword match only decides whether your resume surfaces in a search. What happens next is a human skim of six to ten seconds, and what survives that skim is specific, quantified accomplishment bullets. Once your coverage is above 80% on required keywords, put the rest of your effort into bullet quality: rewrite weak lines with the STAR method builder, pressure-test your stories with a timed round in the practice tool, and after the interview, close the loop with the follow-up email generator.

Privacy by design

Resumes and job descriptions are sensitive — they reveal your employer, your history, and where you are applying. This tool never transmits either text. Extraction and matching run entirely inside your browser tab; there is no server call, no storage, and no analytics event containing your inputs. When you close the tab, everything is gone.

Frequently asked questions