llms.txt is a markdown file at your site root that gives AI agents a structured, human-readable description of your site. The format is informal but converging on a convention: H1 name, blockquote tagline, sections for products, trust signals, contact, and AI policy.

Does Squarespace support llms.txt natively?

No. As of June 2026, Squarespace has no built-in support for serving files at custom paths with custom content types. You can either work around it with a URL slug page (which serves HTML, not markdown) or proxy through Cloudflare with a Worker for proper markdown content type.

Should I let AI train on my Squarespace content?

It depends on your business model. If your revenue depends on the content itself (publishing, paywalled research, educational courses), say no. If your content exists to market a product or service, say yes — being baked into LLM training data turns every future conversation about your space into a potential sales channel.

Do I need Cloudflare to add llms.txt to Squarespace?

For a clean implementation, yes. There are workarounds inside Squarespace such as URL slug pages serving HTML-wrapped content, but they compromise the content type which matters to picky AI clients. Cloudflare's free tier fully covers this use case.

Will adding llms.txt hurt my regular SEO?

No. Nothing in this setup affects HTML rendering, sitemaps, schema markup, or anything Googlebot relies on. The Cloudflare Worker only fires on /llms.txt and /robots.txt — both routes Googlebot uses normally, and the augmented robots.txt remains valid and is obeyed by Googlebot.

What goes inside llms.txt?

Heading with brand name, blockquote tagline, context paragraph, hero product with link and price, full catalog as bullet list, trust signals (reviews, ratings, user counts), adjacent content (blog, directory), contact info, and an explicit AI usage policy. About 5,000 to 8,000 characters is the sweet spot.

What are Content Signals in robots.txt?

Content Signals are machine-readable directives in robots.txt that declare AI usage preferences across three dimensions: search (citation in AI answers), ai-input (real-time agent responses), and ai-train (use in model training). Spec is at contentsignals.org.

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