# How Do Sellers Get Discovered by AI Agents? URL: https://firestarter.network/blog/how-sellers-get-discovered-by-ai-agents Published: 2026-06-12 Author: Victor Young AI agents do not browse, they query. Sellers get discovered by having structured, complete, queryable listings. Here is what agents look for, three ways to list, and the economics of selling to them. Sellers get discovered by AI agents by being queryable, not by being visible. An agent shopping for "65W USB-C charger under $40 with two-day shipping" does not scroll a category page or notice your banner; it runs a structured query against a commerce API and gets back listings whose fields match. Discovery for agents is a data-quality contest: the sellers who win are the ones whose price, stock, shipping, and product attributes are accurate, complete, and machine-readable. Everything you know about ranking for human eyeballs (photography, urgency badges, sponsored placement) is irrelevant to a buyer that reads JSON. That is a genuinely different game from SEO and marketplace ads, and it is currently early enough that small sellers can compete with large ones on equal terms. Here is how agent discovery actually works and how to get listed. ## Agents Do Not Browse, They Query A human shopper discovers products through a funnel of impressions: search results, thumbnails, reviews, comparison tabs. An agent discovers products in one step: it sends a query with hard constraints (category, price ceiling, shipping window, required attributes) and receives matching listings as structured data. This collapses the discovery funnel into a filter. There is no impression to win, no click-through to optimize, no cart-abandonment to retarget. Either your listing matches the constraints and is in the result set, or it does not and you were never considered. The agent then compares the matches on the fields they expose and proposes one to its human for approval. Two consequences follow for sellers. First, completeness is reach: every missing field is a constraint you can no longer match. A listing without a shipping-time field is invisible to every query that filters on delivery speed. Second, accuracy is survival: an agent that gets burned by stale stock or a price that changed at checkout will deprioritize the source that burned it, and unlike a human, it never forgets. ## What Agents Actually Look For When an agent evaluates listings on Firestarter, it reads fields, and the fields that decide most purchases are unglamorous: - **Price, all-in.** Item price plus shipping, comparable across sellers. Agents routinely reject the cheaper item with expensive shipping; humans often miss it. - **Live stock status.** "In stock" that turns out false at execution is the single fastest way to get deprioritized. - **Shipping time and method.** Many agent queries carry a deadline ("arrives before Friday"). No shipping data means no match. - **Structured attributes.** Wattage, dimensions, material, compatibility, pack count. Agents match constraints literally: a "2-pack" in the title but not in a quantity field is a parsing gamble you will sometimes lose. - **Fulfillment track record.** Because settlement on Firestarter is escrow-based and gated on delivery confirmation, your delivery history is data. Sellers who ship reliably build a record that agents can weigh; sellers who do not, build the opposite. Notice what is absent: brand storytelling, lifestyle imagery, review-count theater. Agents weigh what they can verify. For a fuller treatment of selling mechanics end to end, see the [guide to selling to AI agents](/blog/sell-to-ai-agents-guide). ## Three Ways to Get Listed Getting discovered starts with getting your catalog into the structured layer agents query. Firestarter supports three paths, in increasing order of effort: **1. Platform sync.** If you sell on Shopify, WooCommerce, BigCommerce, Wix, or Squarespace, you connect your store and your catalog syncs automatically, typically in about 30 seconds. Prices and stock stay in sync afterward, which handles the accuracy problem for you. **2. CSV or JSON upload.** If your catalog lives in a spreadsheet or an ERP export, upload it directly. This suits sellers off the major platforms or with custom systems. You own keeping it current, so pair it with a re-upload cadence that matches how fast your stock moves. **3. SELL.md.** Publish a structured markdown file describing your products at a known path on your own site, and agents can discover your catalog from your domain itself. It is the lowest-friction option for small catalogs and the most aligned with how agent-readable the web is becoming. All three feed the same searchable layer. Start with whichever matches where your catalog lives today; the [sell page](/sell) walks through each setup. ## The Economics Agent commerce on Firestarter prices differently from marketplaces, and the difference is the point: - **No listing fees.** Listing your catalog costs nothing, by any of the three paths. Agent searches against it are free too. - **3% commission, completed sales only.** Firestarter takes 3% when a sale completes, meaning escrow settled on confirmed delivery. An order that falls through costs you nothing. - **Buyers pay no transaction fees.** The buyer side runs on execution tokens, so there is no fee wedged between your price and what the buyer's agent compares. Your listed price is the price that competes. - **Founding sellers: 0% for 12 months.** Early sellers pay no commission for their first 12 months, capped at 10 sellers per category. If your category is open, the early-mover discount is literal. Compare that to the 15% and up that large marketplaces take, before ads. We wrote about [what marketplace fees do to small sellers](/blog/marketplace-fees-killing-small-sellers); the agent channel is partly a response to exactly that squeeze. ## How to Win the Ranking That Is Not a Ranking There is no bid auction for agent attention, but there is an order to result sets, and you influence it with the same things that make agents trust you: 1. **Fill every field.** Audit your listings for missing attributes, shipping data, and stock flags. Completeness expands the set of queries you can match. 2. **Keep price and stock live.** Use platform sync if you can. Staleness is the most expensive data problem because it converts matches into failed executions. 3. **Ship like settlement depends on it.** It does. Confirmed deliveries settle your escrow and compound into a track record that agents weigh on the next query. 4. **Price all-in honestly.** Agents compare totals. Shifting margin into shipping does not work on a buyer that adds the columns. This is unglamorous work, which is exactly why it is an opportunity: most catalogs are incomplete, and the sellers who clean theirs up first inherit the matches everyone else is silently failing. The broader shift is covered in our [agentic commerce trends](/blog/agentic-commerce-trends-2026) outlook. ## The Bottom Line AI agents discover sellers through structured queries, so discovery is earned with complete, accurate, queryable listings and a reliable fulfillment record, not with ad spend. List by platform sync, CSV/JSON, or SELL.md, keep the data live, and the economics (3% on completed sales only, free listings, founding sellers at 0% for a year) leave the margin advantage with you rather than a marketplace. --- ## FAQ ### Do I need to be on Shopify to sell to AI agents? No. Platform sync (Shopify, WooCommerce, BigCommerce, Wix, Squarespace) is the fastest path at about 30 seconds, but CSV/JSON upload covers custom systems and spreadsheets, and SELL.md lets you publish an agent-readable catalog from your own site with no platform at all. ### How much does it cost to list products for AI agents? Nothing. Listing is free on all three paths, and agent searches against your catalog are free. You pay a 3% commission only when a sale completes, defined as escrow settling on confirmed delivery. Founding sellers pay 0% for their first 12 months, capped at 10 sellers per category. ### Can agents find my products if my data is incomplete? Only for queries that do not touch the missing fields, which in practice means you silently drop out of a large share of searches. A listing without shipping time is invisible to every deadline-constrained query. Completeness is the closest thing agent discovery has to reach. ### Do reviews matter to AI agents? Far less than they matter to humans, and less than fulfillment data. Agents weigh verifiable signals: field completeness, price accuracy at execution, and delivery track record from escrow settlement. A five-star wall does not parse into a constraint match; a history of confirmed on-time deliveries does.