Checklist

AI Shopping Agent Readiness

Use this checklist to make product and policy data easier for AI shopping systems to discover, compare, and route to the right human-owned checkout flow.

Discovery

Product URLs are discoverable

Product and category URLs are linked, included in sitemaps, and not hidden behind fragile client-only navigation.

Add product/category URLs to sitemaps and ensure important product pages render useful HTML.
Product Data

Product structured data is complete

Product pages expose price, availability, SKU, brand, images, reviews, and offer data where applicable.

Audit JSON-LD/Product schema and fill missing offer, availability, shipping, and return policy fields.
Product Data

Product feed is clean and current

Catalog feeds are up to date, deduplicated, and aligned with on-page product data.

Reconcile feed values with product pages and document update frequency.
Agent Access

Crawler and AI-agent access is intentional

robots.txt, bot policies, and CDN rules reflect an intentional choice rather than accidental blocking.

Review AI/search bot access, document allow/block decisions, and test public pages from a neutral client.
Agent Access

AI-readable site notes exist

The site has clear machine-readable pointers such as llms.txt or equivalent documentation for key content areas.

Add llms.txt or a concise AI-readable guide that points to product, policy, and support resources.
Policy

Shipping, returns, and trust policies are explicit

Agents and users can find shipping costs, return windows, support contacts, and fulfillment constraints.

Publish structured policy pages and link them from product and checkout flows.
Protocol

Protocol ownership is assigned

A named team owns UCP/ACP monitoring, implementation decisions, and change review.

Assign an owner across ecommerce, SEO, engineering, and payments.
Checkout

Checkout and payment handoff is documented

The team understands which checkout steps can be agent-mediated and which require user confirmation.

Map payment-provider guidance, consent points, and escalation paths.
Monitoring

Agentic commerce changes are monitored

The team has a recurring process for tracking protocol, platform, and search changes.

Set a weekly review cadence and record source-backed changes in a changelog.
Monitoring

Measurement can separate AI-shopping signals

Analytics and logs can identify bot access, product-feed issues, and search/agent referrals where available.

Add log review, GSC query tracking, and event measurement for product discovery flows.