Google Lighthouse now includes an Agentic Browsing category that audits how well AI agents are able to navigate, understand, and act on a site.
Google’s documentation notes that the Agentic Browsing category is experimental. Practically speaking, that means you need to run Lighthouse in Chrome Canary, Google's experimental Chrome channel that’s released daily.
The Agentic Browsing category runs three sets of checks:
- WebMCP: Validates your WebMCP integration — a proposed web standard that lets a site provide directions for AI agents to act upon
- Agent-centric accessibility: Reviews the part of your accessibility tree that matters most for machine interaction, including names and labels, tree integrity, and visibility
- Stability and discoverability: Measures Cumulative Layout Shift (CLS) and checks for the presence of an llms.txt file
Marie Haynes, Owner of Marie Haynes Consulting, shared an X post about the announcement that pointed out how interesting it is that one of the checks centers on an llms.txt file:
Per Google's documentation, the standards for the agentic web are still emerging. Instead of the familiar 0–100 score, the Agentic Browsing category shows a ratio of how many readiness checks your site passes.
What the Agentic Browsing category signals for marketers
Agentic readiness has been easy to put off until now, but the recent change to Lighthouse signals that isn’t feasible for much longer.
Agentic protocols and tools are arriving fast. Just recently, Google has been building toward an agentic web with:
- AI performance report in Merchant Center: Tracks how AI-generated shopping experiences are performing
- AI Assistant channel in GA4: Attributes traffic from AI assistants as its own channel in Google Analytics
- Google-Agent user agent: A dedicated crawler identity that signals when Google's AI agents are visiting and interacting with your site
- Universal Commerce Protocol: A standard that lets AI agents complete purchases across retailers without leaving Google's surfaces
- WebMCP: A proposed web standard that, if adopted, would let sites direct agents on how to act
A Google-backed audit for agentic readiness provides search marketers with a reputable way to justify their work to stakeholders.
Google has also said llms.txt isn't required for generative AI search. Its inclusion here suggests the file matters more when your site has agent-specific elements, which is exactly what the Agentic Browsing report evaluates.
How to measure visibility beyond Google's surfaces
For an agent to act on a website, it must first be visible to AI platforms, including ChatGPT and Perplexity.
Semrush One combines both the AI Visibility Toolkit and the SEO Toolkit to let you track your presence across numerous AI platforms and search engines in one place.
Use the AI Visibility Toolkit to monitor citation frequency and visibility trends across AI tools. And to see which of your URLs get cited, the grounding queries that trigger those citations, and citation counts by platform.
Then confirm you aren't accidentally blocking AI agents using Site Audit. Unintentionally blocking AI crawlers limits your AI visibility.
For larger and more complex organizations, Semrush Enterprise AIO reveals in-depth insights about your share of voice, visibility, and AI referral traffic across platforms.
