CommerceTXT – An open standard for AI shopping context (like llms.txt)
Hi HN, author here. I built CommerceTXT because I got tired of the fragility of extracting pricing and inventory data from HTML. AI agents currently waste ~8k tokens just to parse a product page, only to hallucinate the price or miss the fact that it's "Out of Stock". CommerceTXT is a strict, read-only text protocol (CC0 Public Domain) designed to give agents deterministic ground truth. Think of it as `robots.txt` + `llms.txt` but structured specifically for transactions. Key technical decisions v1.0: 1. *Fractal Architecture:* Root -> Category -> Product files. Agents only fetch what they…
In plain words
CommerceTXT is an open standard text protocol designed to provide AI agents with reliable product, pricing, and inventory data from e-commerce sites. Rather than parsing HTML, agents access structured product information in a fractal file system, reducing token usage from roughly 8,500 to 380 per product while eliminating hallucination risks around prices and stock status. The read-only format follows the pattern of robots.txt and llms.txt, offering deterministic ground truth for AI-driven shopping interactions without transaction capabilities to avoid security issues.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hi HN, author here. I built CommerceTXT because I got tired of the fragility of extracting pricing and inventory data from HTML. AI agents currently waste ~8k tokens just to parse a product page, only to hallucinate the price or miss the fact that it's "Out of Stock". CommerceTXT is a strict, read-only text protocol (CC0 Public Domain) designed to give agents deterministic ground truth. Think of it as `robots.txt` + `llms.txt` but structured specifically for transactions. Key technical decisions v1.0: 1. *Fractal Architecture:* Root -> Category -> Product files. Agents only fetch what they need (saves bandwidth/tokens). 2. *Strictly Read-Only:* v1.0 intentionally excludes transactions/actions to avoid security nightmares. It's purely context. 3. *Token Efficiency:* A typical product definition is ~380 tokens vs ~8,500 for the HTML equivalent. 4. *Anti-Hallucination:* Includes directives like @INVENTORY with timestamps and @REVIEWS with verification sources. The spec is live and open. I'd love your feedback on the directive structure and especially on the "Trust & Verification" concepts we're exploring. Spec: https://github.com/commercetxt/commercetxt Website: https://commercetxt.org
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