Every Trails RPG, Ranked From Worst To Best

Kotaku's "Every Trails RPG, Ranked From Worst To Best" piece spotlights the entire Trails series, offering detailed rankings and commentary that is likely to drive a surge of fan‑generated traffic and AI‑powered content discovery. For website owners, this means a spike in both human visitors and automated bots hunting for game‑related data, reviews, and user‑generated discussions. Search engines and AI assistants will crawl the article to extract titles, rankings, and key descriptors, potentially indexing this content in knowledge graphs. If your site hosts fan forums, walkthroughs, or merch pages linked to the Trails franchise, you’ll see increased bot traffic trying to scrape structured data for recommendation engines or to generate AI‑driven summaries. **Actionable tips:** 1. **Update your llms.txt** to explicitly allow reputable AI crawlers (e.g., Google’s “Googlebot‑Image” for screenshots) while blocking generic data‑scraping bots with `User‑Agent: * Disallow: /` and then whitelist trusted agents. 2. **Implement bot‑behavior analytics** in llmscentral.com to differentiate genuine fan traffic from high‑frequency scrapers; set thresholds for request rates on URLs containing “trails‑rpg” or “ranking”. 3. **Add structured markup** (JSON‑LD) for game titles, rankings, and review scores on your pages so legitimate AI services can parse the data without needing to scrape, reducing unnecessary bot load.