Can I vibe code Jobscan?
Scores your resume against a job posting's ATS keywords.
The core comparison — paste your resume and a job description, get matched and missing keywords with suggestions — is exactly what LLMs are good at, and a personal version is genuinely a one-sitting build you can run on unlimited postings, unlike Jobscan's scan quotas. The 'kinda' is their claimed edge: research into how specific ATS systems actually parse and rank, recruiter-side benchmarks, and the LinkedIn tooling around it. Whether that data is worth $50 a month is between you and your job search.
Build a personal resume-vs-job-description matcher. Two paste boxes (resume as Markdown or PDF upload with text extraction, and the job posting). One LLM call returns structured JSON: match score, hard skills present/missing, soft skills, seniority fit, and specific rewrite suggestions quoting my actual bullets — with a strict instruction to never invent experience I don't have. Render it as a clean report with a keyword checklist. Store each scan in Postgres keyed by company and role so I can track versions per application and diff my resume between scans. Next.js on Vercel, Postgres, one API route to the LLM.
A resume tuner: paste a job description and your resume, and an LLM returns a match score, missing keywords, and honest line-by-line suggestions, with history per application.
- Jobscan's research into how specific ATS platforms parse and rank resumes
- Benchmarks from millions of scans telling you what score gets callbacks
- LinkedIn profile optimization and cover-letter tooling
- A guided job-tracker workflow instead of a tool you maintain mid-job-hunt
Job seekers in ATS-heavy industries pay for the reassurance of scores calibrated against real ATS behavior, not just an LLM's educated opinion.
A prompt is the first move, not the whole game. Course 01 teaches you to take a prompt like this one to a shipped, working app — reviewing, correcting, and steering the agent the whole way.
Start Course 01 →