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Generates tailored cover letters and cold emails from job listings using AI. Works on LinkedIn, Indeed, and more. ApplyAI generates ATS-optimized cover letters and cold emails tailored to any job listing — in one click. HOW IT WORKS 1. Open any job listing on LinkedIn, Indeed, Naukri, Glassdoor, Internshala, or 10+ other platforms 2. Click the ApplyAI icon and hit "Scan Page" — it extracts the job description automatically 3. Choose your tone (Professional, Enthusiastic, Concise, or Technical) and message type (Cover Letter or Cold Email) 4. Hit Generate — get a ready-to-send message that maps your resume to the job requirements FEATURES • ATS-optimized — uses exact keywords from the job description so your application gets past automated filters • Cover letters & cold emails — two message formats with different strategies • 4 writing tones — Professional, Enthusiastic, Short & Punchy, Technical • PDF resume upload — drag & drop your resume, text extracted automatically • Platform detection — recognizes LinkedIn, Naukri, Indeed, Glassdoor, Internshala, Wellfound, YC Jobs, Lever, Greenhouse, Workday, Monster, ZipRecruiter • Editable output — tweak the generated message before copying • Live character count — track message length in real time PRIVACY • Your resume is stored locally on your device — never on our servers • Job descriptions are processed in memory and never saved • No account or sign-up required • Full privacy policy: https://m0n1shgupta.github.io/CoverAI/privacy.html
May 23, 2026
rating_count is the Chrome Web Store ratings count, not a written-review count.
Media assets
Screenshots and videos on the listing.
Has promo video
Whether the listing includes at least one video.
Languages
Declared language locales.
Developer website
Listing exposes a developer website URL.
Contact email
Listing exposes a contact email.
Keyword in name
Case-insensitive substring match in the name.
Keyword in description
Case-insensitive substring match in the description.
Keyword occurrences in description
Count of case-insensitive occurrences in the description.
Category user-count percentile
Share of same-category extensions with fewer users (null if unknown).
These are transparent listing completeness / keyword signals, not a prediction of Chrome Web Store search ranking.