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Scans checkouts locally for dark patterns. Spot deceptive shopping traps and manipulative UX before you check out. PatternSleuth AI is your on-device defensive shopping copilot that automatically detects, highlights, and explains deceptive design patterns (dark patterns) across ecommerce websites, booking portals, and subscription services. ⚡ WHAT PATTERNSLEUTH AI DETECTS • Fake Scarcity & Urgency: Identifies artificial stock countdowns, fabricated viewer counters, and high-pressure purchase timers. • Sneaky Fees & Basket Stuffing: Uncovers hidden charges, auto-added protection plans, and pre-selected add-ons before final payment. • Confirmshaming & Trick Questions: Highlights guilt-inducing opt-out buttons and convoluted double-negative opt-in checkboxes. • Hidden Subscriptions: Flags recurring billing disguised as one-time purchases and buried auto-renewal terms. 🛡️ KEY HIGHLIGHTS • Visual Element Highlighting: Injects clear on-page visual borders around manipulative UI components. • Plain-English Deception Audits: Delivers an interactive side panel scoring overall site deception risk and explaining the trick. • 100% On-Device Privacy: Powered entirely by Chrome's built-in local AI runtime (window.ai / Gemini Nano). Your shopping activity, cart contents, and visited pages remain strictly inside your device's memory. 🚀 HOW TO USE 1. Navigate to any online store, travel booking site, or checkout flow. 2. Click the PatternSleuth AI icon (in the pinned extensions) 3. Review the on-page highlighted deception warnings and side audit breakdown. 🔒 PRIVACY & SYSTEM DISCLAIMERS • Zero Data Collection: PatternSleuth AI runs strictly on-device in volatile local memory. Zero browsing data, form inputs, or shopping sessions are ever transmitted to external servers. • System Requirements: Inference performance depends on your local hardware specifications (GPU/CPU/RAM) and Chrome's built-in AI runtime. • Informational Use Only: Pattern detections are generated by an on-device AI model for consumer awareness and educational convenience.
rating_count is the Chrome Web Store ratings count, not a written-review count.