llms.txt Validator & Generator

llms.txt is a plain-text file at the root of your domain (yoursite.com/llms.txt) that tells AI shopping agents — ChatGPT, Claude, Perplexity, Gemini — where to find your product catalog, pricing, return policy, and structured commerce metadata. It's the AI-era equivalent of robots.txt + sitemap.xml for commerce. Sites without an llms.txt are typically invisible to AI shopping agents that rely on agent-friendly discovery rather than crawling.

Yes. ChatGPT's shopping mode, Perplexity Shopping, Claude with browsing, and Gemini Shopping all check for llms.txt as part of their commerce discovery. Major retailers (Shopify storefronts, BigCommerce sites, Magento 2 stores) that publish an llms.txt see 2-4x higher inclusion rates in AI shopping responses compared to sites without one.

No. The validator runs entirely in your browser. You paste content; it parses and reports. There is no server call, no logging, no tracking on the validation itself. You can verify in browser DevTools — no network requests fire when you click Validate.

Spec compliance: required H1 site name, optional summary blockquote, section structure (## Headers with markdown links), URL formatting, required commerce sections (Products, Policies, Categories), encoding, and length. It also surfaces opportunities — e.g. missing a returns-policy link or no structured-data hint — that improve AI agent inclusion.

The generator produces a compliant llms.txt from a few inputs (store name, product feed URL, policy URLs). The SignalixIQ full audit measures your actual AI shoppability — schema.org coverage, MCP server presence, agent crawl tests against ChatGPT/Claude/Perplexity, product feed quality scoring, and competitor benchmarking. The generator gets you to the starting line; the full audit ranks you against your category.

Yes — there's no license restriction on llms.txt content, and the generator produces standard-spec output you can publish directly. We recommend reviewing for accuracy (your actual policy URLs, your actual product feed URL) before deploying.