Decode the AI Citation Formula
Scrape top-cited domains and extract a replicable content formula.
ChatBakers 
Claude 
Firecrawl What this workflow does
There is a pattern in what AI cites and most content teams cannot see it because they are looking at their own content rather than the sources AI actually trusts. The top-cited domains in any category share structural and editorial characteristics that are not obvious until you look at them side by side.
This finds those domains, scrapes the specific articles AI retrieves most often, and extracts the common patterns: content length, heading structure, use of data and statistics, types of claims made, entities mentioned, and how the topic is framed.
The output is a concrete content formula derived from real evidence, not best practices or generic SEO advice. Your team can follow it tomorrow.
Example prompt
ChatBakers MCP connected ❯ Pull the domain report for our tracked prompts and identify the top 10 most-cited domains. Scrape the highest-cited article from each of those domains. Analyse what they share structurally: content length, heading structure, use of data and statistics, types of claims made, entities mentioned, and how they frame the topic. Return a replicable content formula with specific structural and editorial choices our team can follow to increase our chances of being cited by AI in this category.
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