Tarte

www.tartecosmetics.com

Last scanned Jun 20, 2026, 6:16 AM

Verdict

Closed to AI agents

ARC Score v1.0

45/100Mixed

How it's computed →

Agent access19.4/50

Structured data4/25

Protocol files12/15

Scan stability10/10

Agent access

Agent	Status	Source
GPTBot	Blocked	UA test: blocked by site defenses
ChatGPT-User	Blocked	UA test: blocked by site defenses
ClaudeBot	Blocked	UA test: blocked by site defenses
Claude-Web	Allowed	robots.txt: Allow
PerplexityBot	Blocked	UA test: blocked by site defenses
Google-Extended	Blocked	UA test: blocked by site defenses
Amazonbot	Blocked	robots.txt: Disallow
Bingbot	Allowed	robots.txt: Allow
CCBot	Blocked	UA test: blocked by site defenses

Infrastructure

PlatformcustomCDNcloudflareWAFnone

Data signals

JSON-LDNot detected
Schema.org ProductNot detected
Open GraphNo
Product feedNo
llms.txtYes

Change history · last 90 days

18 changes

Apr 5, 2026
robots.txt presencefalse→true
Google-Extended robots.txtno_rule→allowed
CCBot robots.txtno_rule→allowed
Amazonbot robots.txtno_rule→blocked
PerplexityBot robots.txtno_rule→allowed
Claude-Web robots.txtno_rule→allowed
ClaudeBot robots.txtno_rule→allowed
ChatGPT-User robots.txtno_rule→allowed
GPTBot robots.txtno_rule→allowed
Apr 4, 2026
Google-Extended robots.txtallowed→no_rule
CCBot robots.txtallowed→no_rule
Amazonbot robots.txtblocked→no_rule
robots.txt presencetrue→false
PerplexityBot robots.txtallowed→no_rule
Claude-Web robots.txtallowed→no_rule
ClaudeBot robots.txtallowed→no_rule
ChatGPT-User robots.txtallowed→no_rule
GPTBot robots.txtallowed→no_rule

The free public window is 90 days. Multi-year history, watchlists, and change alerts are part of Pro.

Fix it with Claude Code

Each failed check below has a ready-made prompt tailored to this scan's findings. Run it in Claude Code from your site's repository.

✗robots.txt blocks 1 AI agentshow prompt

My e-commerce site is tartecosmetics.com. Our robots.txt currently disallows these AI agents, which prevents AI assistants from reading, recommending, or buying our products:

- Amazonbot (Amazon — Buy For Me)

Find where robots.txt is generated or stored in this repository (static file in public/, a robots route/handler, or platform config). Then:

1. Add an explicit "Allow: /" rule for each agent above (keep any existing Disallow rules for genuinely private paths like /cart, /checkout, /account).
2. Do NOT loosen rules for any user-agent we haven't listed, and preserve the existing sitemap reference.
3. Show me a diff of the change and list each agent whose effective access changes from blocked to allowed.
4. If robots.txt is managed by the e-commerce platform rather than this repo, tell me exactly where in the platform's admin to change it instead.

Context: this was flagged by ARC Report (arcreport.ai/brand) — verify after deploy by fetching https://tartecosmetics.com/robots.txt and checking the rules for each agent listed above.

✗WAF/CDN blocks 6 agents despite robots.txt allowing themshow prompt

My e-commerce site is tartecosmetics.com. Our robots.txt does not block these AI agents, but live HTTP tests show our WAF/CDN returns 403s or challenge pages to them:

- GPTBot (OpenAI — ChatGPT training)
- ChatGPT-User (OpenAI — ChatGPT live browsing)
- ClaudeBot (Anthropic — Claude training)
- PerplexityBot (Perplexity — Perplexity / Comet)
- Google-Extended (Google — AI Mode / Gemini)
- CCBot (Common Crawl — Open training data)

This means our stated policy (allow) and our enforcement (block) disagree, and AI assistants silently fail on our store. In this repository and our infrastructure config:

1. Search for bot-management or firewall configuration (Cloudflare rules in code/terraform, vercel.json, middleware that filters user-agents, security headers config).
2. Where we control it in code, add allowlist entries for the user-agents above — scoped to product, category, and content pages only; keep protections on /cart, /checkout, /account, and admin routes.
3. Show me the diff, and flag any rule you find that blanket-blocks "bot-like" traffic.
4. If the blocking happens in a dashboard we don't keep in code (e.g. Cloudflare Super Bot Fight Mode, DataDome, PerimeterX), tell me the exact product setting to change and what to set it to.

After deploy, verify with: curl -A "GPTBot/1.0" -I https://tartecosmetics.com/ (expect 200, not 403).

✗No JSON-LD structured datashow prompt

My e-commerce site is tartecosmetics.com. A scan found no JSON-LD structured data at all, so AI shopping agents can't reliably read our product names, prices, availability, or images.

In this repository:

1. Find the product page template/component and add a JSON-LD <script type="application/ld+json"> block with Schema.org Product markup: name, description, image, sku, brand, and an Offer with price, priceCurrency, availability (use schema.org/InStock | OutOfStock), and url. Populate every field from our real product data — no placeholders.
2. Add an Organization JSON-LD block to the base layout (name, url, logo) if missing.
3. If we have category/listing pages, add ItemList markup referencing the product URLs.
4. Show me one fully rendered example of the JSON-LD for a real product, then validate the shape against Google's Rich Results requirements for Product and fix any warnings you can detect statically.

Verify after deploy with https://search.google.com/test/rich-results on a product URL.

✗No Open Graph tagsshow prompt

My e-commerce site is tartecosmetics.com. A scan found no Open Graph meta tags, so link previews and many AI agents see untitled, imageless pages.

In this repository:

1. Add og:title, og:description, og:image, og:url, and og:type to the base layout's <head>, with sensible site-wide defaults.
2. On product pages, override them per product: og:type "product", the product image as og:image (absolute URL, ≥1200×630 where available), and the live price in og:description.
3. Add twitter:card "summary_large_image" alongside.
4. Show me the diff and one rendered <head> for a real product page.

✗No machine-readable product feedshow prompt

My e-commerce site is tartecosmetics.com. A scan found no machine-readable product feed, which feed-based AI shopping agents (ChatGPT Shopping, Klarna, Google AI Mode) rely on.

In this repository:

1. Determine where product data lives (database models, CMS, platform API) and add a product feed endpoint — Google Merchant–compatible XML (RSS 2.0 with the g: namespace) at /feeds/products.xml, or JSON if that's more idiomatic here.
2. Include per item: id, title, description, link, image_link, price with currency, availability, brand, and gtin/mpn when we have them.
3. Paginate or stream if the catalog is large; cache for ~1 hour.
4. Link the feed from robots.txt or a <link rel="alternate"> in the layout, show me the diff, and print the first two feed items rendered from real data.

Embed this score

HTML

<a href="https://www.arcreport.ai/brand/tarte"><img src="https://www.arcreport.ai/badge/tarte.svg" alt="ARC Score for Tarte" height="22"></a>

Markdown

[![ARC Score for Tarte](https://www.arcreport.ai/badge/tarte.svg)](https://www.arcreport.ai/brand/tarte)

Updates automatically with each daily scan.

Scanned daily via robots.txt parsing and live HTTP tests for 9 AI agents. Changes are confirmed across two consecutive scans before publishing. Read the full methodology →