Price: $13.99 - $12.99
(as of Dec 11,2024 03:21:59 UTC – Details)
The prices listed in the article are accurate as of the time of publication and may change. Please check the linked page for the most up-to-date prices.
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Product Description
【Advanced Silent Operation】This Phone Screen Auto-clicker is using spatial mapping click technology to replace the traditional mechanical click method, mute click, zero noise, and has a longer service life, adopting an innovative technology does not damage the screen of mobile phones, more sensitive and stable.
【Effortless Operation】Simply attach the click head or use the screen clip to replicate automatic finger taps. Connecting the USB interface to a power source allows immediate use, liberating your hands. Ideal for gaming, live broadcasting, and task completion with efficiency.
【Customizable Clicking Speed】Tailor your phone screen auto-clicker to suit your exact needs. Featuring 108 adjustable speed settings, you have the freedom to choose between an incredibly fast rate of 99 clicks per second or a more leisurely pace of just 1 click every 9 seconds. You can save your preferred speed and enjoy finger-like, irregular click patterns for an uninterrupted experience.
【LED display Design 】 With a built-in LED digital display that allows you to see the number of clicks, easy and convenient to operate and use, adopting an intelligent digital display to make your operation more convenient.
【Instructions for Use】Activate BOOT Mode – Begin by pressing the BOOT button to engage the device in BOOT status, where the screen will display a numerical count. Proceed by pressing the start button to initiate the clicking action, indicated by a flashing blue light. To modify the frequency while in BOOT mode, simply hold down the BOOT key for an extended adjustment.
Customers say
Customers like the ease of use, quality, and tap capacity of the video game controller. They mention it’s simple yet effective, and puts out 99 taps a second. However, some customers disagree on its functionality.
AI-generated from the text of customer reviews