Command
Use the Peec MCP to pull the domain report for our tracked prompts broken down by source classification. Identify which content types are retrieved most often: editorial, UGC, institutional, or owned content. Then identify the specific channels within those types that are driving the most citations in our category right now. Based on those findings, draft two pieces of content structured around what AI currently retrieves and cites most in our space: one long-form article targeting the top editorial pattern and one listicle targeting the top UGC pattern. Save each as a WordPress draft using the WordPress MCP. Schedule this as a weekly Claude task to flag new channel opportunities automatically.
Content strategy without channel data is mostly guesswork. Teams publish across every format and platform because no one has clear evidence about which ones actually influence AI citations in their specific category. The reality is that different categories have completely different source preferences: AI might heavily weight Reddit for one type of query and rely almost entirely on editorial content for another.
This surfaces the actual distribution for your category using real retrieval data, then puts that insight directly into your content planning.
The output is not just a channel recommendation. It is a piece of content built for the channel that is already working, structured based on what AI currently trusts.
