citelayer • AI Visibility Plugin for WordPress

WordPress site owners who want their content discovered by AI systems like ChatGPT, Claude, Perplexity, Gemini, and Grok can now make their websites visible to these large language models without writing any code. citelayer is a WordPress plugin that automatically generates the technical signals and structured data that AI crawlers need to find, read, and cite content properly. The plugin operates through six integrated layers designed to maximize content visibility across major AI systems. At its core, citelayer automatically generates and injects Schema.org structured data into WordPress pages and posts, eliminating manual coding and plugin conflicts. This makes content consistently interpretable by LLMs, search engines, and knowledge graphs. The plugin also creates llms.txt files, which function as the robots.txt equivalent for the AI era, telling language models what a site contains and how to read it. Beyond structured data, citelayer enriches websites with additional technical layers including UCP and WebMCP endpoints, which expose content through the protocols AI agents use to fetch and reason over websites. Different AI models follow different citation patterns, and the plugin adds data layers compatible with any LLM to ensure broad compatibility. Installation follows a three-step process: users install and connect the plugin, which then automatically injects and structures their content, with performance tracking capabilities coming soon. The plugin lives directly in the WordPress admin panel with no external dashboards or separate accounts required. It works with existing themes and plugins while respecting site performance. Several monitoring and analytics features are currently in active development. LLM monitoring will run regular probes to detect whether ChatGPT, Gemini, Claude, and other major models actually cite a site's content, logging every mention. An AI Visibility Score will provide a single trackable metric reflecting how often and accurately LLMs reference a site, allowing users to benchmark against their own historical data. Competitor analysis will reveal which sites AI systems cite instead and surface the structural and content patterns that give those competitors an advantage. The tool is designed for developers, SEOs, and agencies who recognize that AI systems cite sources rather than rank pages, requiring a different optimization approach than traditional search engine optimization.