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Definition

Agent Readability

How easily AI shopping agents can parse, trust, and act on a brand's catalog, content, and policies — the agent-era equivalent of crawlability.

Definition

Agent readability is the degree to which AI shopping agents can parse, trust, and act on a brand's catalog, content, and policies. It is the agent-era equivalent of crawlability: where SEO asked "can a search engine index this page," agent readability asks "can a language model extract the facts it needs to recommend this product — and get them right."

Why it matters

AI assistants answer shopping questions by synthesizing whatever they can retrieve and parse. Brands whose product data is locked in images, JavaScript-rendered widgets, or vague copy get flattened into generic descriptions — or dropped from the answer entirely. Brands that are readable get described accurately, compared fairly, and cited. As more discovery moves through agents, readability stops being a technical nicety and becomes distribution.

What makes a store readable

The main ingredients: server-rendered pages with real text (not text baked into images), structured data (schema.org Product, Offer, FAQPage markup), explicit facts stated in prose (materials, dimensions, compatibility, policies), consistent entity naming so the brand and its products are unambiguous, machine-oriented surfaces like llms.txt and structured feeds, and crawl access for AI user agents (GPTBot, ClaudeBot, PerplexityBot) in robots.txt.

How to assess it

The honest test is behavioral: ask the major assistants the questions your buyers ask — "what does [brand] sell," "is [product] good for [use case]," "what's [brand]'s return policy" — and score the answers for accuracy, completeness, and whether the brand is cited at all. Wrong or missing answers trace back to specific readability gaps, and fixing them is concrete engineering work rather than mystique.

See agent readability in action.

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