UserTesting for AI agents
Can AI agents actually use your product?
AgentEye tests your website or app with autonomous AI agents and shows exactly where they fail, get confused, or cannot complete real user tasks.
Start free: paste your URL for an instant readability scan (llms.txt, robots.txt, sitemap and key pages). No login, no crawling beyond ~15 URLs.
Built for the agents that browse, compare and buy on your behalf
Reading is step one. Using your product is the test.
The free scan checks whether agents can discover and read your site. The Agent Test goes further: can an autonomous agent understand your product, navigate the UI, and complete real user goals — or does it fail, loop, or need human help?
Multiple attempts, screen recordings, failure traces — not a one-off browser run.
Free scan — you are here
Agent Test — structured audit
What the free scan checks
Seven transparent categories add up to a 0–100 Agent Readiness Score. This tells you whether agents can find and read your site — before you invest in a full usability audit.
Agent Discovery
llms.txt, llms-full.txt and .well-known resources that let agents find and read your site.
Crawlability & Robots
robots.txt, HTTP status and whether public pages are reachable without a login.
Sitemap & Structure
sitemap.xml coverage, canonical tags and clear meta structure.
Content Clarity
Clear titles, descriptions, a product/company summary and server-rendered content.
Docs / API Readiness
Documentation, developer/API pages, OpenAPI specs and markdown-based docs.
Trust & Canonical Facts
Contact, legal, privacy/terms pages, official links and extractable facts.
Risk, Claims & Compliance
Disclaimers, honest claims, clear pricing/limits and deprecation signals.
See what agents can — and can't — read
Every scan returns a clear score, category breakdown and highest-impact fixes. The Agent Test adds videos, screenshots and failure traces for real task completion.
agents struggle with this site
average across scanned sites: 58
Real tasks. Real failures. Real fixes.
We turn your product goals into realistic AI-user journeys — then run autonomous agents against them.
- ?Can an agent understand what the product does?
- ?Can it sign up?
- ?Can it complete onboarding?
- ?Can it book a demo?
- ?Can it use the main feature?
- ?Can it find pricing?
- ?Can it contact support?
- ?Can it complete checkout?
- ?Can it create a project?
- ?Can it connect a wallet?
A structured audit — not a one-off browser run
Four steps from product link to prioritized fixes.
- 1
Submit your product
Send us your website or app link and define what success looks like.
- 2
We create agent tasks
We turn your product goals into realistic AI-user journeys.
- 3
Agents test your product
Autonomous agents try to complete the tasks while we record every attempt.
- 4
You receive the audit
Videos, screenshots, failure traces and prioritized fixes — with optional re-test after you ship changes.
Optional re-test: after you improve the product, we run the same flows again to confirm agents can complete them.
The value is not sending one agent to your website
Developers can point a browser agent at their own product. That is easy. The hard part is knowing where agents consistently fail.
What is easy
- Send one browser agent to your site once
- Watch a single recording
- Guess whether the failure was the agent or your UI
What AgentEye adds
- Repeated agent runs across multiple attempts
- Reproducible testing with defined tasks
- Different personas and scenarios
- Screen recordings and screenshots
- Failure traces that show where and why
- Distinguish random mistakes from real product blockers
- Prioritized fix roadmap
- Optional re-test after changes
- Continuous agent testing after deployments (Continuous plan)
The value is finding where AI agents consistently fail — not proving one agent got through once.
Traditional QA checks if your product works. AgentEye checks if AI agents can use it.
Classic QA automation
Does the software technically work?
Button clicks, API responses, regression suites, CI pipelines.
Agent Usability Audit
Can an autonomous AI agent actually use the product?
Confusing flows, unclear navigation, missing context, vague labels, bad forms, poor onboarding, unclear pricing, inaccessible UI states.
We focus on agent failures like
- Confusing flows and dead ends
- Unclear navigation and missing context
- Vague button labels and bad form structure
- Poor onboarding and unclear pricing pages
- Inaccessible UI states agents cannot interpret
- Tasks that technically work but are hard for agents to complete
We do not compete head-to-head with QA tools like Momentic, QA.tech or Mabl. We add a usability layer for the agentic web — on top of your existing QA, not instead of it.
Find where agents fail — before they do
Start with a free readability scan, or skip straight to a structured Agent Usability Audit with recordings, traces and prioritized fixes.
AgentEye does not guarantee that all AI agents can use your product, and does not replace traditional QA. It helps you find where autonomous agents consistently struggle.