Over 34 days, I’ve created more than 10 SEO agent skills. Six worked perfectly on the first run. The other four are why I can now walk you through the folder structure details that most LinkedIn posts about AI SEO skills skip. What actually makes these agents dependable isn’t fancier prompts—it’s the underlying architecture. Below is how to design an agent from zero, test it properly, debug it, and deploy it with confidence. Why most AI SEO skills fall apart Here’s what a standard “AI SEO prompt” on LinkedIn usually looks like: You are an SEO expert. Analyze the following website and provide a comprehensive audit with recommendations. That’s the whole thing. Maybe they tack on a few formatting rules. Then they share a screenshot of the response, rack up 500 likes, and move on. The output looks polished. It sounds authoritative. It’s also wrong about 40% of the time. I know because I tried this exact method. Early on, I pointed an agent at a site and said, “find SEO issues.” It returned 20 issues. Eight of them weren’t real. The agent had never even crawled some of the URLs it was confidently reporting on. Three core problems doom single-prompt skills: No tools: The agent has no mechanism to actually inspect the site. It relies on training data and guesswork. Ask, “Does this site use canonical tags?” and it hallucinates what the site might look like instead of fetching and parsing the HTML. No verification: No one validates whether the findings are accurate. The agent claims, “missing meta descriptions on 15 pages.” Which…