AI content readiness scorer (AEO / GEO)

1. Paste your draft to get a readiness score and ranked fixes.
2. Lead with the answer. Put a direct, self-contained answer in the first sentence or two of each section.
3. Use question headings that mirror the prompts people type.
4. Add specifics and structure - stats, definitions, and lists or tables an engine can lift cleanly.
5. Re-score and publish once the citability signals are green.

Traditional SEO optimizes a page to rank in a list of links; AEO/GEO optimizes the content to be quoted inside an AI-generated answer. They share a foundation - clear structure, accurate facts, crawlability - but AEO adds emphasis on self-contained, extractable passages. In classic SEO you can win by being comprehensive; in AEO you win by being the clearest, most quotable source for a specific question. The two reinforce each other: content built to be cited by AI also tends to earn featured snippets and better engagement in regular search.

Answer engines assemble responses from two places: the model's training data, and live retrieval from the web (the citations you see in Perplexity, ChatGPT search, and AI Overviews). You can't change what a model was trained on, but you have a lot of influence over retrieval - and retrieval is where citations and referral traffic come from. Engines preferentially pull passages that directly answer the query, are dense with verifiable specifics, and sit on a crawlable, trustworthy page. Writing for that is exactly what this scorer measures.

• Burying the answer. If the reader has to scroll past three paragraphs of preamble, the engine won't find a clean quote.
• Vague, padded prose. Fluff with no specifics gives the model nothing concrete to cite.
• Walls of text. No headings, lists, or tables makes extraction hard.
• Undefined jargon. Define the entities and terms so the model can reason about them.
• No freshness signals. Undated, stale content loses to current sources.