What is AIO Checker?
AIO Checker analyses how well your website is optimised for discovery and citation by large language models like ChatGPT, Claude, and Gemini. The tool examines your site's structure, metadata, content formatting, and other signals that influence whether an LLM will reference your pages when answering user queries. You receive an AIO (AI Optimisation) score ranging from 0 to 100, along with specific, actionable recommendations and code snippets to improve your standing. This is particularly useful for content creators, publishers, and businesses that want their work properly attributed and discovered by AI systems that increasingly serve as information discovery tools.
Key Features
AIO scoring system
Get a 0-100 score indicating how well your site is optimised for LLM citation and discovery
LLM perspective analysis
See how ChatGPT, Claude, and Gemini evaluate your website's visibility to their systems
Actionable recommendations
Receive specific, prioritised suggestions for improvement
Code snippets
Get ready-to-use code examples to implement recommended changes
Free tier access
Test the tool on your website without payment
Competitive insights
Understand how your optimisation compares across industry standards
Pros & Cons
Advantages
- Addresses a real problem; as LLMs become primary information sources, websites need visibility signals tailored to them
- Free tier lets you test immediately without commitment
- Provides concrete code examples, not vague advice
- Focuses on practical optimisation rather than theoretical SEO
Limitations
- Limited transparency on exactly which factors comprise the AIO score algorithm
- LLM citation preferences evolve frequently; recommendations may have varying longevity
- Works best for established websites with existing content; less useful for new sites with minimal indexing history
Use Cases
Publishers checking whether their articles are properly formatted for LLM citation and attribution
Content teams optimising site structure to improve visibility to AI-powered search and recommendation systems
E-commerce sites ensuring product information is discoverable when users query AI assistants
Technical writers and documentation teams verifying their content meets LLM indexing expectations
SEO professionals adapting strategies to account for AI-driven information discovery alongside traditional search