Six questions, one fan-out, one finished piece of content.
The agent learns your business, generates the fragment space engines would retrieve against for one head query, and then writes the content for whichever fragment you choose. It is the method running on one query instead of your whole category.
The Citabld Agent is a free tool that intakes a brand's category, buyer, and one head query, generates a modeled subquery fan-out across seven AI engines, and drafts one extraction-engineered content unit for a chosen subquery. It demonstrates the Citabld method on a single query; the paid Query Map covers an entire category.
Every row it returns is labeled MODELED, because nothing here was captured from a live engine.
Generated from engine behavior profiles, not observed retrieval.
Where a statistic belongs, the draft marks it as needing a source.
This is the method on a single head query. The Query Map covers a category.
What the agent will not do
It will not present modeled rows as measured, and every row it returns is labeled MODELED because nothing here was captured from a live engine. It will not invent statistics; where a number belongs, the draft marks it as needing a source. It does not score your coverage against competitors or capture the live citation landscape. Those come from the Query Map.