Evaluating web usability typically requires time-consuming user studies and expert reviews, which often limits iteration speed during product development, especially for small teams and agile workflows. We present Avenir-UX, a user-experience evaluation agent that simulates user behavior on websites and produces standardized usability. Unlike traditional tools that rely on DOM parsing, Avenir-UX grounds actions and observations, enabling it to interact with real web pages end-to-end while maintaining a coherent trace of the user journey. Building on Avenir-Web, our system pairs this robust interaction with simulated user behavior profiles and a structured evaluation protocol that integrates the System Usability Scale (SUS), step-wise Single Ease Questions (SEQ), and concurrent Think Aloud. Subsequently, a comprehensive User Experience (UX) report will be generated. We discuss the architecture of Avenir-UX and illustrate how its multimodal grounding improves robustness for web-based interaction and UX evaluation scenarios, paving the way for a new era of continuous, scalable, and data-driven usability testing that empowers every developer to build web interfaces that are usable. Code is available at: https://github.com/Onflow-AI/Avenir-UX
Figures & tables
Figure 1. From deployment to insights: Avenir-UX’s web agents autonomously test your application and generate comprehensive UX reports with SEQ and SUS scores.
Active Think-Aloud Real-time verbalization of reasoning.
Table 1. Comparison of UXAgent and Avenir-UX
Statement
1
2
3
4
5
1
I think that I would like to use this system frequently.
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◯
◯
◯
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2
I found the system unnecessarily complex.
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◯
◯
◯
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3
I thought the system was easy to use.
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◯
◯
◯
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4
I think that I would need the support of a technical person to be able to use this system.
◯
◯
◯
◯
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5
I found the various functions in this system were well integrated.
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◯
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6
I thought there was too much inconsistency in this system.
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◯
◯
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Table 2. The System Usability Scale ( Brooke, 1996 )
Score
Grade
%
Score
Grade
%
> 84.1
A+
96–100
71.1–72.5
C+
60–64
80.8–84.0
A
90–95
65.0–71.0
C
41–59
78.9–80.7
A-
85–89
62.7–64.9
C-
35–40
77.2–78.8
B+
80–84
51.7–62.6
D
15–34
74.1–77.1
B
70–79
< 51.7
F
0–14
72.6–74.0
B-
65–69
Table 3. Sauro-Lewis Curved Grading Scale (CGS)
Statement
1
2
3
4
5
6
7
1
Overall, how difficult or easy was this task?
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◯
◯
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1: Very Difficult, 7: Very Easy
Table 4. The Single Ease Question (SEQ) ( Sauro and Dumas, 2009 )
Figure 2. Avenir-UX system architecture built on the Avenir-Web framework.
Figure 3. Recreation.gov task execution workflow showing bimodal performance across five stages. Green boxes indicate successful interactions (SEQ ≥ 6.5), yellow boxes indicate friction points (SEQ ≤ 3.3), resulting in a SUS score of 55.0/100.0.