Naukri does not publish how it ranks candidates, and no outside tool has its internal algorithm. What we can describe — and what this checker tests — is how résumé parsers and recruiter keyword search generally work:

1. 1

   Parse

   When you upload a CV, a résumé parser extracts its text and tries to split it into fields: name, contact details, current designation, employers, dates, education and skills. Columns, tables, text boxes and images are the usual reasons text comes out jumbled or missing.

2. 2

   Index

   The extracted fields sit alongside your Naukri profile (headline, key skills, total experience, location, notice period). If the parser could not find your Skills section, those skills simply are not there to be searched.

3. 3

   Search & filter

   Recruiters searching Naukri's résumé database type keywords — a skill, a tool, a job title — and narrow by filters such as experience, location, salary and how recently the profile was active. Résumés that contain the exact terms and fit the filters are the ones that show up.

4. 4

   Shortlist

   A recruiter scans the results list, opens a handful of profiles and reads the résumé itself. A clear headline, a short summary and a skills list that matches the search are what earn the click and the call.

The practical upshot: if a parser cannot read a line, a recruiter cannot find it. Most low scores come from layout (columns, tables, graphics) or from using different words than the job description — both fixable in an afternoon. For the longer background on Naukri, Resdex and profile vs résumé, read our guide to how Naukri uses ATS.