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Capture a job description from any page and queue it for AI drafting in Job Genie. Job Genie - Apply to Jobs by Email Without Leaving the Page Job Genie lets you apply to jobs directly from LinkedIn, and other job boards without switching tabs or manually writing application emails. Paste a job description or upload a screenshot, and AI extracts the role, company, and contact email, then generates a tailored application email using your resume. Review the draft, attach your resume, and send it directly from your connected Gmail or Outlook account. How it works Open a job posting on any supported job board. Paste the job description or upload a screenshot. Choose a writing tone and click Analyze. Review the generated application email. Attach your resume and send it from your Gmail or Outlook account. Features Extracts job details from text and screenshots with built-in OCR. Detects contact emails from job postings. Generates tailored application emails in seconds. Five writing tones: Professional, Precise, Confident, Friendly, and Creative. Send emails through your own Gmail or Outlook account. One-click resume attachment. Track applications and their status. Daily application quota tracking. Contact Email Detection Job Genie creates application drafts only when a valid contact email is found in the job posting. It works best with direct company listings and recruiter posts that include an email address. Get Started Create a free account at jobgenie.byusman.com. Once you're signed in, the extension automatically detects your active session, so no additional login is required.
Jun 29, 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.