What is FluentAssert?

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

FluentAssert is a nuget that Fluent assertions express what you want tested instead of how. This project also provides a simple BDD framework that lets you write tests that can be easily understood and verified by non-developers. It has a Nerq Trust Score of 53/100 (C-). 0 GitHub stars. Published by handcraftsman, sshetty, wbinford. Last analyzed April 2026.

Why This Score

Trust & Safety Overview

53
TRUST SCORE
C-
GRADE
0
STARS
0
DOWNLOADS

What FluentAssert Does

FluentAssert is a nuget in the nuget category. Fluent assertions express what you want tested instead of how. This project also provides a simple BDD framework that lets you write tests that can be easily understood and verified by non-developers.. It is published by handcraftsman, sshetty, wbinford and has no specified license. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.

Who Should Use FluentAssert

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

Details

Authorhandcraftsman, sshetty, wbinford
Categorynuget
LicenseNot specified
Typenuget
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=fluentassert

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

Frequently Asked Questions

What is FluentAssert used for?
FluentAssert is a nuget tool. Fluent assertions express what you want tested instead of how. This project also provides a simple BDD framework that lets you write tests that can be easily understood and verified by non-developers.
Is FluentAssert free?
License: Check project page. FluentAssert has 0 GitHub stars.
Is FluentAssert safe?
FluentAssert has a Nerq Trust Score of 53/100 (C-). Use with caution.
What are alternatives to FluentAssert?
Top alternatives: . See full comparison.

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

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