An applicant tracking system rejects most CVs before a person reads one. This tool runs the same kind of checks first, then explains what to change and generates the material to change it with.
The tool parses a CV out of PDF, DOCX or plain text, extracts the skills it can identify against a categorised database of over three hundred technical terms, and scores the document the way an applicant tracking system would — contact details, section structure, keyword coverage, length and formatting.
Matching is semantic rather than literal, so a CV listing PyTorch is credited against a role asking for deep learning. From the gap between CV and role it generates tailored output: a cover letter, an eight-week learning plan for the missing skills, likely interview questions, and rewrite suggestions shown as before-and-after lines.
A recruiter mode reverses the flow, ranking a batch of CVs against a single job description.
Most applications are filtered automatically, and the filter is not reading for talent — it is reading for structure and keywords. A strong candidate with a badly structured CV loses to a weaker one with a well structured CV, and neither ever learns why.
Generic advice does not help, because the answer depends on the specific gap between one CV and one role. That comparison is mechanical, which makes it a good fit for software.
Extraction handles the document formats, skill recognition works against a curated database rather than free-form guessing, and a semantic scorer catches equivalences that exact matching misses. The ATS checks and section scoring are deterministic rules — they produce the same result every time, which matters when someone is acting on the advice.
Only the generative parts — cover letter, roadmap, interview prep, rewrites — use a language model, and it runs locally.
Real applicant tracking systems differ between vendors and are not public. The ATS checks encode widely documented conventions — they are a reasonable proxy, not a simulation of any specific system, and no pass-rate figure is claimed.
Skill extraction is bounded by the database: a genuinely novel technology will not be recognised until it is added. Salary estimates are indicative ranges, not offers.
The analyzer is live on this site. Upload a CV and a job description and see the gap analysis it produces.