ARC store checks

Reviewed 1h ago.

• tools: 18 tools scanned
• metadata: scanned

No findings.

Tools (18)

• check_store

  Look up one store domain and return its saved, dated checkout evidence and route results. Missing data says "not recorded". No login and no new scan.

• find_stores

  Search stores where a saved check shows an agent reached checkout, filtered by platform, protocol, or category. No login and no new scan.

• get_store_hub

  Look up a free ARC store card by host. Includes saved measurements and brand_claim ownership metadata. Brand statements are not measured by ARC; claims never change measured scores.

• google_checkout_readiness

  Read saved public Google agentic checkout readiness checks for a store. Free; no new scan or paid calls. Merchant Center feed eligibility cannot be checked from outside. Not Google approval or certification.

• product_data_check

  Free latest saved product data and return/shipping policy check from the store's pages and structured data. Reads history only; no store fetch or model call. A missing result is not a zero.

• can_agent_checkout

  Can an AI agent buy from this store or check out on this Shopify store? Free real HTTP check of any public homepage or product URL: agent catalog, product, checkout link, UCP profile, Checkout WebMCP (Shopify-only checkoutWebmcp: status, nullable detected, tools, reason; buyer approval required), Shopify WebMCP storefront adapter (used by browser agents; detected in the HTML, not a browser session), blocks, and the fix. No login, model call, payment, or browser scan. Cached per host for 24 hours. A returned link means reach checkout, not a completed purchase.

• check_agent_readiness

  Check whether personal AI agents can reach a product URL, understand it, and buy from it. Runs ARC's readiness check: crawler access, whether an agent can answer a shopper's questions from the page, and personal shopping agents trying to add to cart or reach checkout. Returns a check id — poll get_readiness_result (about 30–60 seconds). This does not ask what agents think of the brand; use ask_agents_about_brand for that.

• get_readiness_result

  Get a readiness check by id. While running, reports progress. When complete, reports whether personal agents could reach the page, understand it, and buy, plus the wall, concrete next steps, a directional score, a per-agent breakdown, and screenshots. Calling this again with the same id redisplays the result and does not start a new check. Never re-run check_agent_readiness just to see the screenshots again.

• list_readiness_checks

  List this workspace's recent readiness checks (newest first) — each store, its score, status, and id. Use an id with get_readiness_result to reopen a check.

• ask_agents_about_brand

  Ask benchmark personal-agent personas what they think of a brand and whether they would recommend it for a category. Personas: Muse-style, Instinct-style, Grok Bot-style, OpenAI dots-style, and OpenClaw-style. This tool uses benchmark personas, including the Grok Bot-style persona; these are not live consumer-product sessions. It is not the real Grok read-back on a scan and it is not the agent-rails HTTP check. What Grok tells shoppers on a scan is a real model call via API, checked against the store's pages, not the consumer Grok app. All five cart attempts, Grok included, are ARC browser cart tests. Returns, per persona: mentioned, recommended, which competitors were recommended instead, sentiment, and short quotes, plus next steps. Limited to 8 runs per workspace per day and 12 per network. Free workspaces also share a site-wide daily cap so unpaid runs cannot drain the model budget.

• get_fixes

  Concrete next steps to get recommended by personal agents and to become reachable, understandable, and buyable. Pass a readiness check id and/or the brand, category, store URL, and competitors that were recommended instead. Uses the check's evidence when an id is given. Does not start a new check.

• bulk_create_monitors

  Set up scheduled monitoring for one or more store URLs (the 'set up monitoring' flow). Validates each URL and rejects invalid/private/internal ones. GUIDED FLOW: first ask the user for the URLs (paste a list or a CSV), then the frequency (daily/weekly/monthly, default weekly). Every plan runs the core panel of personal shopping agents — no picking needed. Call once without confirmed=true to preview the exact setup and scan-credit estimate, read that summary to the user, and only after the user explicitly says yes call again with confirmed=true to create the monitors. Each scheduled run uses one scan credit. Every run emails who reached the cart, who stopped or started, the stuck step, and the fix. Weekly is what the plans include; daily only fits when the plan's scan allowance covers it.

• list_monitors

  List the workspace's monitors — each store re-checked on a schedule for whether personal agents can still reach it and buy. Includes cadence, status, last score, next run, and the monitor id.

• monitor_summary

  Overview of whether monitored stores are still buyable by personal agents: latest score, trend, status, next run, and recent regression alerts.

• update_monitor

  Change a monitor's cadence (daily/weekly/monthly) or label. Use the monitor id from list_monitors.

• pause_monitor

  Pause a monitor so it stops running on schedule (its history is kept). Use the monitor id from list_monitors.

• resume_monitor

  Resume a paused monitor.

• run_monitor_now

  Run a monitor's scan immediately (off-schedule) to establish or refresh its baseline. Consumes one scan credit — only call when the user explicitly asks to run now. Use the monitor id from list_monitors.