Crawl access
robots.txt, sitemap references, search crawler access, and whether product/collection paths are accidentally blocked.
AI Commerce Readiness audit
Shopify AI Commerce Readiness Audit
See whether search engines, AI assistants, and emerging shopping agents can crawl, understand, recommend, and hand off your Shopify catalog — and whether the store is prepared to measure the revenue that follows.
AI discovery files
llms.txt, llms-full.txt, agents.md, and optional /.well-known/ucp discovery so assistants know which pages matter.
Commerce readiness
Product JSON-LD, product URLs, policy/contact links, variant clarity, answer-ready content, and attribution gaps for AI-referred traffic.
Crawler policy, not crawler panic
Make an intentional crawler policy.
The audit does not tell merchants to allow every AI crawler. It separates answer/search crawlers from training crawlers, flags accidental blanket blocks, and helps you decide what should be discoverable.
- Allow discovery on purpose: product, collection, blog, and policy pages should be crawlable when visibility matters.
- Control training deliberately: GPTBot, CCBot, ClaudeBot, Google-Extended, and similar agents can be a brand/IP decision.
- Give agents context: curated llms.txt and agents.md files point assistants at canonical pages instead of making them guess.
What the free audit checks
- robots.txt and sitemap.xml discovery
- AI crawler rules for OAI-SearchBot, ChatGPT-User, PerplexityBot, GPTBot, ClaudeBot, CCBot, and related agents
- llms.txt, llms-full.txt, agents.md, and optional UCP discovery
- Product JSON-LD, canonicals, Open Graph, headings, and answer-ready page structure
- Shopify commerce signals: product URLs, policy/contact links, crawlable product pages, and AI attribution handoff readiness
Honeybound cleanup sprint
If the report finds gaps, Honeybound can clean up the implementation: robots policy, curated AI discovery files, structured data, FAQ/content sections, and Search Console validation.