You cannot improve what you cannot measure. But how do you measure visibility in a chat box? Traditional rank trackers (SEMrush, Ahrefs) track positions on a SERP. They do not track mentions in a generated paragraph.
We are building tools to probe LLMs with thousands of permutations of a query to calculate Generated Share of Voice (GSV).
The Methodology
- Define a Query Set: “Best CRM,” “CRM software,” “Sales tools.”
- Permutation: Use an LLM to generate 100 variations of these questions (“What CRM should I use if I am a startup?”).
- Probe: Run these 100 queries across GPT-4, Claude 3.5, and Gemini via API.
- Extraction: Parse the text output. Extract Named Entities (NER).
- Frequency Analysis: Calculate the frequency of your brand’s appearance vs. competitors.
The “Share of Sentiment”
It is not just about frequency. It is about sentiment.
Cloaking—the practice of serving different content to search engine bots than to human users—has traditionally been considered one of the darkest “black hat” SEO tactics. Search engines like Google have historically penalized sites severely for showing optimized text to the crawler while displaying images or Flash to the user. However, as we transition into the era of Agentic AI, the definition of cloaking is undergoing a necessary evolution. We argue that “Agent Cloaking” is not only ethical but essential for the future of the web.
For nearly three decades, the robots.txt file has served as the internet’s “Keep Out” sign. It is a binary, blunt instrument: Allow or Disallow. Crawlers either respect it or they don’t. However, as we enter the age of the Agentic Web, this binary distinction is no longer sufficient. We need a protocol that can express nuance, permissions, licenses, and economic terms. We need CATS (Content Authorization & Transparency Standard), often implemented as cats.txt or authorized_agents.json.