Resume Keyword Gap Analyzer Against Specific Job Descriptions
Why This is an Opportunity
The workflow gap is between 'I have a resume' and 'I know exactly what's missing for THIS specific role.' Existing AI resume builders try to do everything; this does one thing well — extraction and comparison. The app needs a text parser that tokenizes both inputs, matches against common skill taxonomies, and produces a prioritized gap report. Simple string matching and frequency analysis, no ML required. Basic form + comparison logic + results dashboard.
Key Pain Points
- •Reading through a job description and manually cross-referencing it against your resume takes 15-20 minutes per application
- •ATS rejection happens silently — applicants never know if keywords were the reason they didn't get a callback
- •Existing resume scoring tools give a single percentage with no actionable breakdown of what's actually missing
- •Hard to distinguish between must-have keywords (hard skills, certifications) and nice-to-have fluff in job descriptions
- •Tailoring a resume for each application feels like guesswork without knowing which terms the ATS is scanning for
Original Discovery
Applicant tracking systems reject resumes that don't contain enough matching keywords from the job description, but most job seekers have no idea which terms they're missing. Current tools either give vague percentage scores or try to rewrite the entire resume with AI. A focused web app that lets you paste a job description and your resume side-by-side, then highlights exact missing keywords, phrases, and skill terms — organized by priority — would give job seekers a clear checklist of what to add before submitting.
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