What is ™ Go?

53/100
Trust Score (C-)
⚠️ Use Caution

™ Go is a ios that ・GO is most used Taxi App(Taxi booking app)in Japan GO is Japan's No.1 App (cab app) with the most extensive service coverage., available in all 47 prefectures across Japan! Coverage extends to all ma. It has a Nerq Trust Score of 53/100 (C-). 0 GitHub stars. Published by GO Inc.. Last analyzed March 2026.

Why This Score

Trust & Safety Overview

53
TRUST SCORE
C-
GRADE
0
STARS
0
DOWNLOADS

What ™ Go Does

™ Go is a ios in the ios category. ・GO is most used Taxi App(Taxi booking app)in Japan GO is Japan's No.1 App (cab app) with the most extensive service coverage., available in all 47 prefectures across Japan! Coverage extends to all major tourist areas, such as Hokkaido, Tokyo, Kyoto, Osaka, Fukuoka, and Okinawa. * Sourced from data.ai by Sensor Tower - Number of Taxi App(cab app) downloads in Japan - Survey period: October 1, 202. It is published by GO Inc. and has no specified license. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.

Who Should Use ™ Go

™ Go is suitable for evaluation and non-critical use. Review the trust score breakdown before using in production.

Details

AuthorGO Inc.
Categoryios
LicenseNot specified
Typeios
SourceView on GitHub
Security Score0/100
Activity Score0/100

How to Get Started

Check the trust score before installing:

curl nerq.ai/v1/preflight?target=go

Setup guide · Full safety report · Production review · Is it safe?

Frequently Asked Questions

What is ™ Go used for?
™ Go is a ios tool. ・GO is most used Taxi App(Taxi booking app)in Japan GO is Japan's No.1 App (cab app) with the most extensive service coverage., available in all 47 prefectures across Japan! Coverage extends to all ma.
Is ™ Go free?
License: Check project page. ™ Go has 0 GitHub stars.
Is ™ Go safe?
™ Go has a Nerq Trust Score of 53/100 (C-). Use with caution.
What are alternatives to ™ Go?
Top alternatives: . See full comparison.

Last updated March 2026. Trust scores based on automated analysis of public data.