What is Hello Lady! -New Division-?

50/100
Trust Score (C-)
⚠️ Use Caution

Hello Lady! -New Division- is a steam that 《淑女同萌!-New Division-》是晓WORKS于2014年末发售的校园爱情悬疑作品《淑女同萌!》的外传故事(FAN DISC)。游戏剧情采用了双线叙事模式,以在《淑女同萌!》本篇中人气极高的两位女配角菱吾森和兜山美鸟为主角,讲述了属于她们各自的故事。是一款本篇玩家不可错过的精彩外传。. It has a Nerq Trust Score of 50/100 (C-). 95 GitHub stars. Published by AKATSUKI-WORKS. Last analyzed September 2026.

Why This Score

Trust & Safety Overview

50
TRUST SCORE
C-
GRADE
95
STARS
95
DOWNLOADS

What Hello Lady! -New Division- Does

Hello Lady! -New Division- is a steam in the steam category. 《淑女同萌!-New Division-》是晓WORKS于2014年末发售的校园爱情悬疑作品《淑女同萌!》的外传故事(FAN DISC)。游戏剧情采用了双线叙事模式,以在《淑女同萌!》本篇中人气极高的两位女配角菱吾森和兜山美鸟为主角,讲述了属于她们各自的故事。是一款本篇玩家不可错过的精彩外传。. It is published by AKATSUKI-WORKS and has no specified license. With 95 GitHub stars and 95 downloads, it has a small community of users and contributors.

Who Should Use Hello Lady! -New Division-

Hello Lady! -New Division- is suitable for evaluation and non-critical use. Review the trust score breakdown before using in production.

Details

AuthorAKATSUKI-WORKS
Categorysteam
LicenseNot specified
Typesteam
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=hello-lady-new-division

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

Frequently Asked Questions

What is Hello Lady! -New Division- used for?
Hello Lady! -New Division- is a steam tool. 《淑女同萌!-New Division-》是晓WORKS于2014年末发售的校园爱情悬疑作品《淑女同萌!》的外传故事(FAN DISC)。游戏剧情采用了双线叙事模式,以在《淑女同萌!》本篇中人气极高的两位女配角菱吾森和兜山美鸟为主角,讲述了属于她们各自的故事。是一款本篇玩家不可错过的精彩外传。.
Is Hello Lady! -New Division- free?
License: Check project page. Hello Lady! -New Division- has 95 GitHub stars.
Is Hello Lady! -New Division- safe?
Hello Lady! -New Division- has a Nerq Trust Score of 50/100 (C-). Use with caution.
What are alternatives to Hello Lady! -New Division-?
Top alternatives: . See full comparison.

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

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