“粘贴测试”和开放爬虫可能把非公开定价内容交给第三方
原文依据:4 处指南让代理把定价 URL 或渲染后的页面文本交给具备联网能力的 AI,并建议允许 AI 搜索机器人抓取以及公开机器可读的价格。它没有先要求确认页面和文本是否可公开。
若审计对象是预发布、登录后、客户专属或包含未公开折扣的页面,URL、套餐、价格及相关页面文本可能被外部 AI 服务接收、记录或索引。
指南确实要求把 URL 或渲染后的页面文本交给外部联网 AI,并把允许 AI 搜索机器人抓取列为通过条件。对公开定价页通常合理,但若页面需登录、包含谈判价、客户专属条款或尚未发布的文本,粘贴内容或开放抓取会把信息交给第三方。来源没有先要求确认公开性或获得授权。用户可限制测试为已公开 URL,并禁止提交受限页面文本或修改爬虫策略。
**Fast check — the "paste test":** give the pricing URL to a browsing-capable AI (Perplexity, ChatGPT with search, Claude with web) — or paste the rendered page text — and ask "what are the plans and prices?" A clean miss means agents fetching your page will struggle too (a heuristic, not proof every agent fails).The AI-readiness fixes are usually high-impact, low-effort (put prices in text, add `Offer` schema). Hand implementation to **schema** (Product/Offer JSON-LD) and **ai-seo** (extractability, AI-bot access, `llms.txt`).查看另外 3 个位置
| 9 | **Per-tier depth in text** | Each plan's inclusions, limits, and quotas stated in words | Differences shown only as checkmark columns in an image; limits unnamed || 10 | **Structured data & extractability** | `Product`/`Offer` schema markup, clean semantic HTML, AI search/agent bots allowed to crawl (`llms.txt` is a nice-to-have, not yet a standard) | No schema; pricing behind auth/interaction; AI *search* bots blocked in robots.txt |Dimensions 7 and 10 hand off to **`schema`** (Product/Offer JSON-LD) and **`ai-seo`** (extractability, AI-bot access, `llms.txt`) for implementation.- **JS-only render / auth wall** — if the price only appears after interaction or login, most fetchers won't see it (only JS-rendering agents might).- **Blocked AI *search* bots** — the crawlers that feed AI *answers* are the search agents, not the training crawlers: OpenAI's `OAI-SearchBot`, Anthropic's `Claude-SearchBot` / `Claude-User`, Perplexity's `PerplexityBot`. Blocking `GPTBot` only opts out of model *training*, not ChatGPT Search — so check which bots your robots.txt actually blocks. (Bot access is `ai-seo`'s domain — hand it off there.)1. **Load context** — read `.agents/product-marketing.md` (ICP, positioning) so "clarity" is judged against the *right* buyer.2. **Fetch the page as an agent would** — get the rendered text/HTML, not a screenshot. Note immediately whether prices appear in the text (that's dimension 7).3. **Run the paste test** — ask an LLM for the plans and prices from the URL; record what it gets wrong or misses.4. **Score all 10 dimensions** Pass/Partial/Gap with a one-line reason each.