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Score how well your resume matches a job posting using AI. ApplyScore is an elite, evidence-based AI resume assistant designed to give you a ruthless, highly accurate analysis of how well your resume matches any job description on the web. Unlike generic AI tools that hallucinate skills or rewrite your resume with fluff, ApplyScore acts as a strict gap-analysis engine. It reads the job posting, reads your resume, and provides a concrete, auditable breakdown of your true fit. KEY FEATURES • Confidence-Weighted Fit Score: Get a realistic 0-100 score of your actual match rate. • Evidence-Based "Top Matches": See exactly which job requirements you meet, linked directly to the specific bullet points in your resume that prove it. • Prioritized Gap Analysis: Instantly identify your weak spots. ApplyScore ranks your missing requirements and weak signals so you know exactly what the hiring manager will notice. • Tailored Bullet Suggestions: Get 1-2 highly targeted, non-hallucinated resume bullet suggestions designed specifically to address your biggest gap using your existing experience. • Universal Compatibility: Works on LinkedIn, Greenhouse, Ashby, Lever, Workday, Amazon Jobs, Meta Jobs, and virtually any other job board on the internet via our advanced Web Component and Shadow DOM piercing scraper. • Privacy First: Your resume stays securely cached locally on your browser. You bring your own API key (OpenAI, Anthropic, or Google), meaning you are in complete control of your data and LLM model choice. Stop guessing what hiring managers want. Use ApplyScore to audit your resume and apply with absolute confidence.
Feb 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.