{"slug": "67-of-chinese-export-brands-serve-llms-txt-we-read-them-most-are-empty", "title": "67% of Chinese Export Brands Serve llms.txt. We Read Them. Most Are Empty.", "summary": "A scan of 59 Chinese cross-border brand websites found that none block OAI-SearchBot, 67.4% serve an llms.txt file, and only 1.9% carry FAQPage schema. However, four out of five llms.txt files contained no brand information, being Shopify platform templates about payment protocols. The findings suggest that while the door is open for AI crawlers, the room is empty.", "body_md": "A scan of 59 Chinese cross-border brand websites found that none block OAI-SearchBot, 67.4% serve an llms.txt file, and only 1.9% carry FAQPage schema. But when we opened the llms.txt files, four out of five contained no brand information — they were Shopify platform templates about payment protocols. The door is open, but the room is empty. Raw data and the scanning script are included below.\n\nThe [first article in this series](https://www.promptzone.com/[ARTICLE-URL]?ref=icp-study) scanned 100 AI tool websites and found something counterintuitive: almost nobody blocks AI search crawlers, but the industry is checking the wrong one.\n\nThat scan explicitly noted a limit: \"Whether the same holds for a DTC brand or a manufacturing exporter is a separate question this sample cannot answer.\"\n\nThis article answers that question. Instead of AI companies, we scanned 59 Chinese-origin brands that sell internationally through their own websites — from Anker and SHEIN to mid-tier outdoor gear and e-bike makers. These are the brands that would benefit most from showing up when someone asks ChatGPT \"what's a good portable power station for camping?\"\n\nThe results did not match what I expected, and the real finding was not in any of the metrics I planned to check.\n\n59 Chinese cross-border brand domains across 18 product categories: consumer electronics, smart home, portable power, DTC fashion, beauty, outdoor gear, LED displays, 3D printers, digital tablets, e-bikes, projectors, smart pet devices, audio, rugged phones, and wearables.\n\nAbout a third are well-known names: Anker, SHEIN, Roborock, EcoFlow, Govee. The rest are mid-tier brands — Tribit, Blackdeer, Oukitel, Fiido, Engwe — the kind that would benefit most from AI visibility but are unlikely to have a dedicated AI-SEO person.\n\nOf the 59, 53 returned their homepage (HTTP 200). 2 returned 403, and 4 failed to connect (DNS timeout or abort). Every metric below uses only the sites where that specific signal was conclusively readable — not 59, not 53, but the per-metric denominator noted in each table.\n\nThe same scanning script as the first article: zero LLM calls, failures recorded as errors, no defaults masquerading as data.\n\n| Crawler | AI tools (n=68) | Export brands (n=47) |\n|---|---|---|\nOAI-SearchBot (ChatGPT search) |\n0% |\n0% |\n| ChatGPT-User (live fetch) | 0% | 0% |\n| GPTBot (training) | 5.9% | 2.1% |\n| ClaudeBot | 5.9% | 2.1% |\n| PerplexityBot | 1.5% | 0% |\n| Google-Extended | 5.9% | 2.1% |\n| CCBot | 7.4% | 2.1% |\n| Bytespider | 5.9% | 2.1% |\n\nThe blocking rate is even lower than AI companies. Only one brand — Elegoo, a 3D printer maker — blocks GPTBot, and it leaves OAI-SearchBot open. That is the same deliberate, informed pattern from the first scan: opt out of training data, stay in the search index.\n\nFor anyone still worried about \"accidental crawler blocking\" as a major risk: in a combined sample of 159 sites across two very different populations, zero block OAI-SearchBot. Zero block ChatGPT-User. The door is open.\n\nThe question, then, is what is behind that door.\n\nOf the 43 sites where the llms.txt check was conclusive, 29 served a file — 67.4%.\n\nThat is nearly double the 38.8% found in AI-native tools. My initial reaction was that Chinese export brands were somehow ahead. The data looked clean. The file existed. The scanner confirmed it was not an HTML error page.\n\nThen I read the files.\n\nI pulled the actual llms.txt content from five brands: Anker, Florasis, Tribit, Blackdeer, and Oukitel. Four of the five contained identical text:\n\n`/.well-known/ucp`\n\nendpoint for payment handlingThese are Shopify platform templates. The file exists at `/llms.txt`\n\nbecause Shopify puts it there, not because someone at the brand wrote it.\n\nThe one exception was Anker. Its llms.txt described the brand's positioning, listed eight product categories, named three proprietary technologies (GaNPrime, PowerIQ, SolarSaga), and outlined its global site structure. That is what a real llms.txt looks like.\n\n| Brand | llms.txt content | Platform template? | Useful for AI citation? |\n|---|---|---|---|\n| Anker | Brand positioning + 8 product categories + 3 proprietary technologies + global site structure | No — human-written | Yes |\n| Florasis | Shop skill / UCP protocol / payment instructions | Yes — Shopify | No |\n| Tribit | Shop skill / UCP protocol / payment instructions | Yes — Shopify | No |\n| Blackdeer | Shop skill / UCP protocol / payment instructions | Yes — Shopify | No |\n| Oukitel | Shop skill / UCP protocol / payment instructions | Yes — Shopify | No |\n\nThis is a spot check of 5, not a census of 29. I cannot say exactly how many of the 29 are platform templates. But the pattern is clear enough to state: the headline number — 67.4% llms.txt adoption — overstates the reality. Most of these files tell an AI model nothing about the brand.\n\nThe premise of llms.txt, per its [proposal](https://llmstxt.org/), is to give AI models \"concise, expert-level information\" about a site. A platform template about payment protocols does not fulfill that premise. It is a box checked without the work done.\n\nOf the 53 sites whose homepage HTML parsed, exactly 1 carried FAQPage schema: [Fire-Maple](https://www.fire-maple.com), a camping stove maker. That is 1.9%.\n\nIn the AI-native tool cohort, FAQPage was at 12% — already low. Among export brands, it is essentially absent.\n\nThis is the number that should concern these brands most. They sell physical products. Their customers ask comparison questions — \"which portable power station is best for a campervan?\" or \"what's a good budget e-bike for commuting?\" — exactly the kind of question AI answer engines surface structured FAQ content for.\n\nOrganization schema tells an engine what entity a site belongs to. 52.8% of these brands have it (vs 36% for AI tools), likely because Shopify themes include it by default. But Organization schema says \"I exist.\" FAQPage schema says \"here are the answers to the questions people ask about my products.\" The second one is what gets cited.\n\nThe pattern from the first scan repeats, but sharper: platform-provided defaults are widely adopted (Organization schema, llms.txt files). Anything requiring brand effort is not (FAQPage schema, meaningful llms.txt content).\n\nCombine all three findings and the picture is this:\n\nThese brands are technically open to AI. But they have nothing structured for AI to say about them. When someone asks ChatGPT for a product recommendation in their category, there is no structured content pulling the AI's answer toward their brand.\n\nI had expected to find that export brands were behind on the basics — maybe blocking crawlers, maybe missing robots.txt. Instead, the basics are fine. The gap is one level up: between being crawlable and being citable.\n\nThe same four checks from the first article, adapted for DTC brands:\n\n**Open yoursite.com/robots.txt** and search for\n\n`OAI-SearchBot`\n\n. You are almost certainly not blocking it — but verify, because the cost of being wrong is invisible (you simply do not appear in ChatGPT answers, with no error message).**Open yoursite.com/llms.txt**. If the content mentions \"Shop skill,\" \"UCP protocol,\" or \"unauthorized purchases\" and says nothing about your products, it is a Shopify template. It is not helping you.\n\n**Ask ChatGPT: \"What is [your brand]?\"** and then **\"What is the best [your product category] for [common use case]?\"** The first question tests whether AI knows you exist. The second tests whether it would recommend you. The second one matters more.\n\n**View source on your top product page**, search for `FAQPage`\n\n. In this sample, 98% had nothing. If you add FAQ schema to even one product page that answers a \"which X is best for Y?\" question, you are ahead of virtually every brand in this data set.\n\n**Platform attribution is a spot check, not a census.** We read 5 llms.txt files and found 4 were Shopify templates. We did not read all 29. The true proportion of template-vs-real is unknown.\n\n**This scan measures structure, not outcomes.** Having FAQPage schema does not guarantee AI citation. Not having it does not prevent citation. What the data shows is that these brands have not done the structural work that makes citation more likely.\n\n**Sample composition matters.** These are known Chinese export brands with their own websites. The long tail of smaller exporters, Amazon-only sellers, or brands without English-language sites could look very different.\n\n**One snapshot, one day.** All fetches happened on 2026-08-07.\n\nSame scanner as the first article: a single Node script with no dependencies beyond `fetch`\n\n. It reads a newline-delimited list of domains and writes a CSV plus a summary JSON where each metric carries its own denominator.\n\nThe input is a manually curated list of 59 domains. It is not sampled from a systematic source the way the first scan used awesome-ai-tools. That means it is not reproducible from a deterministic procedure — it is a purposive sample, selected to cover the product categories most relevant to AI-search recommendation queries.\n\nI run [BrandGEO](https://brandgeo.app?ref=devto), which does a fuller version of this analysis for individual sites. The thing this scan taught me: the problem for export brands is not access. It is answerability.\n\n| Crawler | Blocked | Rate |\n|---|---|---|\n| GPTBot (training) | 1 / 47 | 2.1% |\nOAI-SearchBot (ChatGPT search) |\n0 / 47 |\n0% |\n| ChatGPT-User (live fetch) | 0 / 47 | 0% |\n| ClaudeBot | 1 / 47 | 2.1% |\n| PerplexityBot | 0 / 47 | 0% |\n| Google-Extended | 1 / 47 | 2.1% |\n| CCBot | 1 / 47 | 2.1% |\n| Bytespider | 1 / 47 | 2.1% |\n\n| Signal | Present / readable | Rate |\n|---|---|---|\n| robots.txt exists | 44 / 47 | 93.6% |\n| llms.txt served | 29 / 43 | 67.4% |\n| Organization schema | 28 / 53 | 52.8% |\n| FAQPage schema | 1 / 53 | 1.9% |\n\n| Signal | AI tools | Export brands | Delta |\n|---|---|---|---|\n| Blocks OAI-SearchBot | 0% (0/68) | 0% (0/47) | — |\n| Blocks GPTBot | 5.9% (4/68) | 2.1% (1/47) | -3.8pp |\n| llms.txt served | 38.8% (26/67) | 67.4% (29/43) | +28.6pp |\n| FAQPage schema | 12% (9/75) | 1.9% (1/53) | -10.1pp |\n| Organization schema | 36% (27/75) | 52.8% (28/53) | +16.8pp |\n\n59 domains · fetched with HTTP 200: 53 · HTTP 403: 2 · failed to connect: 4\n\nScan date: 2026-08-07\n\n**Sites that blocked GPTBot:** Elegoo (also blocks ClaudeBot, Google-Extended, CCBot, Bytespider; does NOT block OAI-SearchBot or PerplexityBot)\n\n**Sites that did not respond:** Dreame (DNS), ColorKey (DNS), PatPat (403), Absen (403), Bambu Lab (timeout), Dangbei (DNS)\n\n**Site with FAQPage schema:** Fire-Maple\n\n| Category | Count | Example brands |\n|---|---|---|\n| Consumer electronics / robot cleaning | 7 | Anker, Roborock, Ecovacs, Dreame, Tineco, Narwal, Eufy |\n| 3C accessories / charging | 2 | Ugreen, Baseus |\n| Smart home / lighting / security | 6 | Govee, Yeelight, Reolink, SwitchBot, Aqara, Sonoff |\n| Portable power / energy storage | 4 | EcoFlow, Bluetti, Jackery, Growatt |\n| Fashion / fast fashion | 6 | SHEIN, Cider, Cupshe, Halara, BloomChic, PatPat |\n| Beauty / cosmetics | 4 | Florasis, Zeesea, ColorKey, Perfect Diary |\n| Outdoor / camping | 3 | Naturehike, Blackdeer, Fire-Maple |\n| LED display (B2B) | 3 | Unilumin, Absen, Leyard |\n| 3D printing / maker | 4 | Creality, Anycubic, Elegoo, Bambu Lab |\n| Digital tablets / drawing | 2 | XP-Pen, Huion |\n| Camera accessories | 1 | SmallRig |\n| Electric mobility | 5 | Segway, Fiido, Engwe, ADO, Hiboy |\n| Power tools | 1 | Worx |\n| Projectors | 2 | XGIMI, Dangbei |\n| Smart pet | 2 | Petkit, Catlink |\n| Audio / headphones | 4 | Edifier, SoundPEATS, QCY, Tribit |\n| Rugged phones | 2 | Blackview, Oukitel |\n| Smart wearables | 1 | Amazfit |\n\nBecause the first article scanned AI tools — a savvy cohort that is not representative of the brands those tools are supposed to help. Chinese cross-border brands are the fastest-growing segment of global DTC ecommerce, and their AI visibility posture had not been measured.\n\nIt is a directional sample, not a census. The confidence intervals are wider than the first article's 100-site scan. The llms.txt spot check (5 sites) is a small sample that prompted a finding, not a final measurement. These limits are stated in the text.\n\nBased on our spot check, yes. Four of five sampled files contained identical Shopify platform text with no brand-specific content. The Shopify documentation does not prominently describe this feature, but the file content — referencing Shopify-specific protocols like Shop skill and UCP — makes the origin clear.\n\nWrite a real one. Include: your brand name and what you sell, your key product categories, any proprietary technologies or differentiators, and the structure of your site. The llms.txt proposal at [llmstxt.org](https://llmstxt.org/) has a format guide. Anker's llms.txt is a good reference for what \"done well\" looks like for a consumer brand.\n\nThis scan only measured Chinese-origin export brands. However, the structural pattern — platform defaults adopted, brand-specific effort absent — is unlikely to be unique to Chinese brands. Any brand on Shopify would see the same auto-generated llms.txt. Whether their FAQPage adoption is equally low is an open question.", "url": "https://wpnews.pro/news/67-of-chinese-export-brands-serve-llms-txt-we-read-them-most-are-empty", "canonical_source": "https://dev.to/sevenailab/67-of-chinese-export-brands-serve-llmstxt-we-read-them-most-are-empty-4chl", "published_at": "2026-08-10 18:13:34+00:00", "updated_at": "2026-08-10 18:49:05.707011+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-products", "ai-tools", "developer-tools"], "entities": ["Anker", "SHEIN", "Roborock", "EcoFlow", "Govee", "Elegoo", "Shopify", "OAI-SearchBot"], "alternates": {"html": "https://wpnews.pro/news/67-of-chinese-export-brands-serve-llms-txt-we-read-them-most-are-empty", "markdown": "https://wpnews.pro/news/67-of-chinese-export-brands-serve-llms-txt-we-read-them-most-are-empty.md", "text": "https://wpnews.pro/news/67-of-chinese-export-brands-serve-llms-txt-we-read-them-most-are-empty.txt", "jsonld": "https://wpnews.pro/news/67-of-chinese-export-brands-serve-llms-txt-we-read-them-most-are-empty.jsonld"}}