CV Keyword Matcher
Compare CV text with a job description using local rule-based keyword matching.
Tool guide
Compare your CV with the language of a real job description
A CV can be strong and still miss the language an employer uses in a particular posting. CV Keyword Matcher gives you a quick, local comparison between the text of your CV and the job description. It looks for terms from a maintained dictionary and reports the overlap it can identify. The result is intentionally described as a keyword signal rather than an ATS score because commercial applicant-tracking systems vary widely in how they parse and rank information.
Paste the CV text into one field and the full job description into the other. The matcher processes both in the browser. It identifies relevant terms from the job description, checks whether they appear in the CV, and groups matched and missing terms for review. Use the missing list as a prompt to inspect your experience rather than adding keywords that you cannot honestly support.
Match evidence, not just words
The best CV adjustment is usually to make genuine evidence easier to find. If a job asks for stakeholder management and you have led cross-team delivery, your bullet can make that responsibility clearer. If the posting asks for a tool you have never used, do not add it simply because the matcher reports it as missing. The tool cannot distinguish genuine experience from keyword stuffing.
Why the tool runs locally
The current matcher is deterministic browser code. It does not send your CV to an external AI provider, and it does not claim to reproduce an employer’s ATS. This keeps the workflow lightweight and makes the result reproducible. It also means the dictionary has limits: synonyms, context and unusual terminology may not be captured.
A practical application workflow
Start with Job Description Analyzer to identify the major requirements. Then use CV Keyword Matcher to compare the posting with your current CV. After that, rewrite only the bullets where your real experience supports a clearer connection. Career Skills Gap Analyzer can help with genuine missing capabilities, while the Job Application Tracker can record the application and its status.
Limitations
Keyword overlap is not the same as relevance, seniority or evidence. A high percentage does not guarantee an interview, and a low percentage does not mean you are unsuitable. Always review the original posting and keep your CV truthful, specific and readable for a human recruiter.
Quick review before submitting
Read the revised CV as a person would read it. Remove awkward repetition, keep every claim truthful, and make sure the strongest evidence remains easy to understand. A keyword match is useful only when it improves clarity rather than turning the document into a list of copied terms.
How it works
Paste both texts. Matching happens entirely in the browser.
Methodology at a glance
Terms from a maintained local dictionary are detected in the job description and then checked against the CV text. The overlap percentage is a simple keyword measure, not an ATS score.
How the model is calculated
The matcher extracts terms from the job description using the same maintained local dictionary and boundary-aware matching approach used by the analyzer. It then checks whether those terms appear in the CV text after normalization. Matched and missing terms are de-duplicated so repeated mentions do not inflate the list. The overlap percentage is a simple ratio based on the terms the engine can identify; it is not an ATS score and does not weight terms by employer importance. User text is rendered safely rather than injected as raw HTML. The method is intentionally transparent and local, but it cannot understand context, synonyms or the quality of an example. A person should review every suggested change before submitting a CV.
Review inputs and assumptions before using a result for a real decision.
This tool uses local keyword matching. It does not reproduce every ATS system or predict hiring outcomes.
Sources and reference notes
No external data source. Matching uses the maintained local HireLanz keyword dictionary in the browser.
Related tools
All toolsJob Description Analyzer
Analyze a job description locally to identify skills, experience, education, work arrangement, sponsorship and salary language.
Use toolExperience Calculator
Add multiple employment periods and calculate total professional experience without double-counting overlaps.
Use toolNotice Period Calculator
Estimate an employment notice-period end date from a resignation date and notice length.
Use tool