# Cart for Agents

> Cart for Agents is an independent publication and free tool that checks what AI shopping agents receive about individual products: which facts arrive, and which facts a shopper's question needs but never gets. We read Shopify's agent catalog (the one Shopify syndicates to ChatGPT, Microsoft Copilot, Google AI Mode and Gemini) and cross-check the open web. We do not see inside any assistant. Nothing here is paid placement.

Every human page has a machine-readable twin at the same path with .json. Cite pages by their canonical URL.

## Pages

- [Home](https://cartforagents.com/): what the free check does. Data: https://cartforagents.com/index.json
- [Research](https://cartforagents.com/research): findings, dated and sourced. Data: https://cartforagents.com/research.json
- [Guides](https://cartforagents.com/guides): practical product-evidence guides. Data: https://cartforagents.com/guides.json
- [ACO vs GEO: cited pages and product records are different wins](https://cartforagents.com/guides/aco-vs-geo): Compare citation, product, variant and offer outcomes with a paired measurement matrix; acronym definitions belong in the SEO/AEO/GEO/ACO comparison. Data: https://cartforagents.com/guides/aco-vs-geo.json
- [Agentic commerce optimization (ACO): test product evidence before chasing rank](https://cartforagents.com/guides/agent-commerce-optimization): A five-stage ACO test plan for one product: confirm eligibility, read the record agents receive, check each shopper requirement against a sourced fact, test one truthful change, then verify the offer. With stop rules, outcome measures and prior art. Data: https://cartforagents.com/guides/agent-commerce-optimization.json
- [Agent-friendly ecommerce: when you need an API and when the page is enough](https://cartforagents.com/guides/agent-friendly-ecommerce-api): Diagnose the failed retrieval route, compare faithful outputs and use a decision tree before adding an API or machine-readable endpoint. Data: https://cartforagents.com/guides/agent-friendly-ecommerce-api.json
- [Agent-ready product data: build a factual record for each SKU](https://cartforagents.com/guides/agent-ready-product-data): Record product identity, values, units, test conditions, sources, exclusions and unknowns for each variant. Includes a fill-in template, a worked humidifier record and a page-versus-catalog check. Data: https://cartforagents.com/guides/agent-ready-product-data.json
- [Agentic commerce: what Shopify merchants can control](https://cartforagents.com/guides/agentic-commerce): Follow one product through the five stages of agentic commerce, from catalog intake to checkout: who decides each one, what a Shopify merchant controls, and what to check first. Data: https://cartforagents.com/guides/agentic-commerce.json
- [Agentic Commerce Protocol: separate product discovery from checkout setup](https://cartforagents.com/guides/agentic-commerce-protocol): Use an integration checklist to distinguish feed admission, discovery data, checkout contracts and supported purchase authorization. Data: https://cartforagents.com/guides/agentic-commerce-protocol.json
- [Agentic commerce strategy: estimate effort and break-even before you start](https://cartforagents.com/guides/agentic-commerce-strategy): Use editable assumptions for fix costs, order contribution and qualified traffic to decide whether to run a bounded merchant test. Data: https://cartforagents.com/guides/agentic-commerce-strategy.json
- [AI product descriptions: open with type, use case, key numbers and limits](https://cartforagents.com/guides/ai-product-descriptions): Write the first sentence of a product description for shoppers and AI agents: product type, use case, verified measurements and honest limits, with two worked rewrites. Data: https://cartforagents.com/guides/ai-product-descriptions.json
- [AI product discovery to purchase: find where the sale stops](https://cartforagents.com/guides/ai-product-discovery): Follow one product from recommendation through seller availability, shipping, authorization and order confirmation using a handoff worksheet. Data: https://cartforagents.com/guides/ai-product-discovery.json
- [AI product visibility: design a repeatable monitoring plan](https://cartforagents.com/guides/ai-product-visibility): Choose 3 to 5 products, real customer questions, buyer contexts, routes and a recheck schedule; log every check in a 15-column ledger; and keep "returned," "recommended," "facts correct" and "sold" as separate outcomes. Data: https://cartforagents.com/guides/ai-product-visibility.json
- [AI product visibility dashboard: turn each red cell into an owned fix](https://cartforagents.com/guides/ai-product-visibility-dashboard): Specify separate visibility, factual-fidelity and commercial fields with evidence links, action owners and next-check dates; no composite readiness score. Data: https://cartforagents.com/guides/ai-product-visibility-dashboard.json
- [AI shopping agents: compare capabilities and merchant controls](https://cartforagents.com/guides/ai-shopping-agent): Compare research, product comparison and purchase capabilities with merchant controls over facts, distribution and checkout eligibility. Data: https://cartforagents.com/guides/ai-shopping-agent.json
- [AI shopping for small businesses: where a small DTC brand can win](https://cartforagents.com/guides/ai-shopping-for-small-business): Check eligibility, buyer constraints, evidence gaps and operating costs before choosing a product cohort or assuming bigger brands always win. Data: https://cartforagents.com/guides/ai-shopping-for-small-business.json
- [AI shopping personalization: control context before comparing results](https://cartforagents.com/guides/ai-shopping-personalization): Compare thin and richly constrained buyer profiles, record memory and country settings, and preserve product disqualifiers in a context-control card. Data: https://cartforagents.com/guides/ai-shopping-personalization.json
- [AI shopping platforms: compare data routes and checkout](https://cartforagents.com/guides/ai-shopping-platforms): Compare ChatGPT, Google AI Mode and Gemini, Perplexity and Microsoft Copilot by how your product data reaches each one, what changes results, and where checkout happens. Data: https://cartforagents.com/guides/ai-shopping-platforms.json
- [AI shopping prompt tracking: build test prompts from real customer questions](https://cartforagents.com/guides/ai-shopping-prompt-tracking): Build a CSV panel with shopper situations, hard constraints, preferences and evidence sources; Google keyword volume is not agent-prompt demand. Data: https://cartforagents.com/guides/ai-shopping-prompt-tracking.json
- [AI visibility: distinguish mentions, citations and product outcomes](https://cartforagents.com/guides/ai-visibility): Classify a brand mention, source citation, product retrieval, recommendation and completed order with examples of what each does not prove. Data: https://cartforagents.com/guides/ai-visibility.json
- [Product-level AI visibility audit: find the next factual fix](https://cartforagents.com/guides/ai-visibility-audit): Run a one-product audit with shopper constraints, received evidence, unknowns and an owner-assigned fix worksheet, not a readiness grade. Data: https://cartforagents.com/guides/ai-visibility-audit.json
- [AI visibility checker accuracy: test what each checker actually reads](https://cartforagents.com/guides/ai-visibility-checker-accuracy): Test an AI visibility checker before you trust it: what it fetched, which fields it read, how it handles missing data, and a rubric for judging any product-URL check. Data: https://cartforagents.com/guides/ai-visibility-checker-accuracy.json
- [AI visibility score: check the denominator before you trust the number](https://cartforagents.com/guides/ai-visibility-score): Ask how a score samples products, contexts and time, handles missing data and weights components using an independent score-review checklist. Data: https://cartforagents.com/guides/ai-visibility-score.json
- [Amazon Rufus optimization for DTC brands: find the Amazon route your products are on](https://cartforagents.com/guides/amazon-rufus-optimization): Use a naming timeline and channel map to distinguish marketplace listings, off-Amazon offers and merchant-controlled product evidence. Data: https://cartforagents.com/guides/amazon-rufus-optimization.json
- [ChatGPT product feeds: map fields, approval and schema conflicts](https://cartforagents.com/guides/chatgpt-product-feed): Map source fields to the documented feed contract, preserve variant identity and resolve conflicting examples without mixing schema versions. Data: https://cartforagents.com/guides/chatgpt-product-feed.json
- [ChatGPT visibility tracking: a repeatable protocol for manual checks](https://cartforagents.com/guides/chatgpt-visibility-tracking): Record market, account context, model versus product, returned representations and repeated outcomes using a fixed protocol and failure log. Data: https://cartforagents.com/guides/chatgpt-visibility-tracking.json
- [Copilot shopping: check merchant data, engagement and sponsored results](https://cartforagents.com/guides/copilot-shopping): Compare merchant feeds, web sources, likely engagement and sponsorship statements; record what Microsoft documents and what remains unknown. Data: https://cartforagents.com/guides/copilot-shopping.json
- [Generative engine optimization for ecommerce: a merchant task backlog](https://cartforagents.com/guides/generative-engine-optimization-ecommerce): Prioritize crawlability, source evidence, product facts and feed consistency using owners, acceptance checks and a worked merchant backlog. Data: https://cartforagents.com/guides/generative-engine-optimization-ecommerce.json
- [SEO, AEO, GEO and ACO: which merchant job does each cover?](https://cartforagents.com/guides/geo-vs-seo): Match search indexing, answer citation, product evidence and purchase execution to the responsible team and a measurable outcome. Data: https://cartforagents.com/guides/geo-vs-seo.json
- [Google AI Mode and Gemini shopping: check your merchant data routes](https://cartforagents.com/guides/google-ai-mode-shopping): Separate indexed web content, Merchant Center data and checkout eligibility using a route teardown and merchant verification checklist. Data: https://cartforagents.com/guides/google-ai-mode-shopping.json
- [Google Merchant Center free listings: check eligibility for Gemini and Shopping](https://cartforagents.com/guides/google-merchant-center-free-listings): Get Google Merchant Center free listings approved and eligible for Gemini: permission, product status, required attributes and price parity, in the order to check them. Data: https://cartforagents.com/guides/google-merchant-center-free-listings.json
- [Google UCP checkout: verify eligibility, exclusions and rollout](https://cartforagents.com/guides/google-ucp-checkout): Run an account-and-market preflight using a dated rollout conflict table, unsupported-product checks and explicit unknowns. Data: https://cartforagents.com/guides/google-ucp-checkout.json
- [GTIN, MPN, SKU and UPID: choose the correct product identifier](https://cartforagents.com/guides/gtin-mpn-sku): Use an identifier decision table to distinguish manufacturer, merchant and catalog identities, including legitimate missing-ID cases. Data: https://cartforagents.com/guides/gtin-mpn-sku.json
- [How AI shopping agents choose products: what the evidence shows](https://cartforagents.com/guides/how-ai-shopping-agents-choose-products): Separate official selection inputs, controlled experiments and vendor observations in a stage-by-stage ledger with methods and limitations. Data: https://cartforagents.com/guides/how-ai-shopping-agents-choose-products.json
- [How to rank in ChatGPT shopping: four checks for product recommendations](https://cartforagents.com/guides/how-to-rank-in-chatgpt): Check admission, received product facts, shopper context and merchant offers in sequence; separate documented inputs from ranking guesses. Data: https://cartforagents.com/guides/how-to-rank-in-chatgpt.json
- [Humidifier field guide for shopping agents: questions to ask, evidence to require, when none fit](https://cartforagents.com/guides/humidifier-field-guide): Ask about room size, noise and runtime; require values with units and test conditions; separate unknown from incompatible; say none fit when no humidifier meets a hard requirement. A neutral rubric with red flags and a worked example. No product picks. Data: https://cartforagents.com/guides/humidifier-field-guide.json
- [Humidifier product data: publish noise, room coverage and runtime](https://cartforagents.com/guides/humidifier-product-data): Map noise, area, output, tank and runtime claims to modes, conditions and sources, using a dated numeric-versus-vague Catalog example. Data: https://cartforagents.com/guides/humidifier-product-data.json
- [Machine-readable product data: keep JSON twins matching the visible page](https://cartforagents.com/guides/machine-readable-product-data): Use a versioned product-evidence JSON example and parity checks for values, scope, sources and unknowns; no special-file ranking promise. Data: https://cartforagents.com/guides/machine-readable-product-data.json
- [Meta Muse shopping: distinguish catalog presence from browser discovery](https://cartforagents.com/guides/meta-muse-shopping): How Meta's Muse agent finds products through your catalog and through its own browser, and which merchant facts to check on each route. Data: https://cartforagents.com/guides/meta-muse-shopping.json
- [Negative product attributes: publish who and what your product is not for](https://cartforagents.com/guides/negative-product-attributes): Represent not-for statements and fit exclusions in a proposed fact schema with merchant examples, not instructions that override a shopper. Data: https://cartforagents.com/guides/negative-product-attributes.json
- [Perplexity shopping: check merchant admission and data routes](https://cartforagents.com/guides/perplexity-shopping): Separate public-web discovery from merchant-program admission, specification sharing and historical checkout arrangements in a route checklist. Data: https://cartforagents.com/guides/perplexity-shopping.json
- [Pet product data: make paw size and weather claims checkable](https://cartforagents.com/guides/pet-product-data): Use paw or body measurements, size conditions and weather-claim sources; separate product variety from seller variety in a dated shelf example. Data: https://cartforagents.com/guides/pet-product-data.json
- [Product claim provenance: tie every claim to its value, scope and source](https://cartforagents.com/guides/product-claim-provenance): Use a proposed JSON claim record with variant binding, units, conditions, provenance and unknown states; it is not an industry protocol. Data: https://cartforagents.com/guides/product-claim-provenance.json
- [Product constraint coverage: check evidence for each shopper requirement](https://cartforagents.com/guides/product-constraint-coverage): Map a known shopper brief to supporting, missing or conflicting facts; separate evidence coverage from product quality and recommendation probability. Data: https://cartforagents.com/guides/product-constraint-coverage.json
- [Product data freshness for AI: what to recheck and how often](https://cartforagents.com/guides/product-data-freshness-for-ai): Set recheck triggers for price, inventory, policies and specifications; distinguish real verification dates from decorative updated-year labels. Data: https://cartforagents.com/guides/product-data-freshness-for-ai.json
- [Product evidence graphs: keep variant, component and seller facts in place](https://cartforagents.com/guides/product-evidence-graph): Model product, variant and offer relationships with explicit inheritance and exclusion edges; keep sibling-choice experiments separate. Data: https://cartforagents.com/guides/product-evidence-graph.json
- [Product feed optimization for AI shopping: map and validate every field](https://cartforagents.com/guides/product-feed-optimization): Trace source facts through transformations to feed output using field mappings, validation rules, variant checks and explicit unknowns. Data: https://cartforagents.com/guides/product-feed-optimization.json
- [Product feed price mismatch: reconcile page, feed and structured data](https://cartforagents.com/guides/product-feed-price-mismatch): Fix price and stock mismatches between your product page, feeds and structured data: pick the source of truth, compare timestamps, and tell lag from a mapping bug. Data: https://cartforagents.com/guides/product-feed-price-mismatch.json
- [Product material data: tie composition and certification claims to proof](https://cartforagents.com/guides/product-material-data): Separate composition, performance and certification claims using source, issuer, scope and expiry fields in a substantiation worksheet. Data: https://cartforagents.com/guides/product-material-data.json
- [Product not showing in ChatGPT? Find the stage that's failing](https://cartforagents.com/guides/product-not-showing-in-chatgpt): Work through admission, retrieval, facts, market context and offers with an evidence log before changing product copy. Data: https://cartforagents.com/guides/product-not-showing-in-chatgpt.json
- [Product-page prompt injection: treat ranking manipulation as a security failure](https://cartforagents.com/guides/product-page-prompt-injection): Find and remove product-page text written to manipulate AI agents, including copy you didn't write, with a defensive checklist and what to publish instead. Data: https://cartforagents.com/guides/product-page-prompt-injection.json
- [Product schema markup: match every marked-up value to the visible page](https://cartforagents.com/guides/product-schema-markup): An annotated Product and Offer JSON-LD example, and the checks that keep every marked-up price, stock, identifier and policy value identical to the visible page. Data: https://cartforagents.com/guides/product-schema-markup.json
- [Product specification template: comparable values, units and test conditions](https://cartforagents.com/guides/product-specification-template): Use a specification template to retain units, measurement conditions, source dates and uncertainty instead of treating bare numbers as comparable. Data: https://cartforagents.com/guides/product-specification-template.json
- [Product variant structured data: tie size, colour, price and stock to the right SKU](https://cartforagents.com/guides/product-variant-structured-data): Build an identity and inheritance matrix that preserves buyer-relevant sibling differences and prevents facts leaking between variants. Data: https://cartforagents.com/guides/product-variant-structured-data.json
- [Share of constraint coverage: calculate it on a real shopper brief](https://cartforagents.com/guides/share-of-constraint-coverage): Calculate a proposed evidence-coverage measure on a worked humidifier brief, keeping unknown, conflicting and inapplicable facts separate. Data: https://cartforagents.com/guides/share-of-constraint-coverage.json
- [Shipping and return policy structured data: attach each promise to the right offer](https://cartforagents.com/guides/shipping-return-policy-structured-data): Map destination, handling, transit, return windows and SKU exceptions to offers, with source dates and unsupported destinations explicit. Data: https://cartforagents.com/guides/shipping-return-policy-structured-data.json
- [Shopify Agentic Storefronts: map merchant and platform responsibilities](https://cartforagents.com/guides/shopify-agentic-storefronts): Map Shopify Catalog eligibility, data mapping, variant grouping, generated fields, distribution routes, crawler and opt-out controls, and downstream assistant and checkout decisions to what Shopify, the merchant, the platform and the buyer control. Data: https://cartforagents.com/guides/shopify-agentic-storefronts.json
- [Shopify Agentic tab: interpret listing quality and search previews](https://cartforagents.com/guides/shopify-agentic-tab): Read the public admin documentation with an annotated walkthrough, separating preview evidence from downstream assistant recommendations. Data: https://cartforagents.com/guides/shopify-agentic-tab.json
- [Shopify Catalog requirements: check each gate when a product is excluded](https://cartforagents.com/guides/shopify-catalog-requirements): Check every Shopify Catalog gate in order, from store standing to product rules, to find out whether a product was excluded or simply outranked. Data: https://cartforagents.com/guides/shopify-catalog-requirements.json
- [Shopify and ChatGPT: check what is automatic and what you control](https://cartforagents.com/guides/shopify-chatgpt): Separate Shopify distribution from merchant-owned product facts, eligibility checks and downstream offers in an ownership checklist. Data: https://cartforagents.com/guides/shopify-chatgpt.json
- [Shopify Global Catalog: distinguish products, UPIDs and seller offers](https://cartforagents.com/guides/shopify-global-catalog): Tell search results, UPID clusters, variants and seller offers apart in Shopify's Global Catalog, with an identity diagram and the unit to use for every count. Data: https://cartforagents.com/guides/shopify-global-catalog.json
- [Shopify metafields for AI: verify which facts reach Shopify Catalog](https://cartforagents.com/guides/shopify-metafields-ai): Map merchant-entered fields to returned records, distinguish inferred attributes and leave unobserved mappings unknown. Data: https://cartforagents.com/guides/shopify-metafields-ai.json
- [Showing up in AI shopping carts: what merchants can optimize at each step](https://cartforagents.com/guides/showing-up-in-ai-shopping-carts): The four steps from AI recommendation to completed order, and what a merchant can optimize at each one: facts, variants, price, shipping, policies and checkout settings. Data: https://cartforagents.com/guides/showing-up-in-ai-shopping-carts.json
- [Size chart accessibility: publish fit measurements as a text table](https://cartforagents.com/guides/size-chart-accessibility): Build an accessible measurement table with garment versus body dimensions, units, tolerances and fit caveats alongside any size-chart image. Data: https://cartforagents.com/guides/size-chart-accessibility.json
- [Spec-sold products: turn shopper requirements into category facts and rule-out conditions](https://cartforagents.com/guides/spec-sold-product-guides): Translate buying requirements into category fields, units, conditions, sources and rule-out conditions, with a worked humidifier worksheet and short contrasts for winter clothing, travel bags and cosmetics. Data: https://cartforagents.com/guides/spec-sold-product-guides.json
- [Track ChatGPT traffic in GA4: set up an AI assistant channel](https://cartforagents.com/guides/track-chatgpt-traffic-ga4): Set up GA4's AI Assistant channel or a stricter custom channel group for ChatGPT, Gemini, Copilot and other assistants, with a tested regex and a reading checklist. Data: https://cartforagents.com/guides/track-chatgpt-traffic-ga4.json
- [Travel product data: carry-on dimensions, capacity and airline fit](https://cartforagents.com/guides/travel-product-data): Publish carry-on claims shoppers and agents can check: external dimensions, loaded state, capacity method, and the airline limits you compared against, with dates. Data: https://cartforagents.com/guides/travel-product-data.json
- [UCP vs ACP: compare contracts before choosing an integration](https://cartforagents.com/guides/ucp-vs-acp): Compare protocol roles, discovery and execution boundaries with version notes, supported capabilities and unresolved interoperability questions. Data: https://cartforagents.com/guides/ucp-vs-acp.json
- [Unit pricing for ecommerce: compare multipacks and bundles fairly](https://cartforagents.com/guides/unit-pricing-ecommerce): Record pack counts, net contents, currency and variant scope in a unit-price worksheet; keep bundle checkout eligibility separate. Data: https://cartforagents.com/guides/unit-pricing-ecommerce.json
- [Universal Commerce Protocol (UCP): capabilities, checkout and merchant controls](https://cartforagents.com/guides/universal-commerce-protocol): What the Universal Commerce Protocol covers for merchants: the /.well-known/ucp profile, catalog, cart, checkout and orders, read against a real store profile. Data: https://cartforagents.com/guides/universal-commerce-protocol.json
- [Winter clothing product data: temperature ratings, scope and fit](https://cartforagents.com/guides/winter-clothing-product-data): Publish temperature units, activity and layering conditions, garment fit and rating provenance; use our corrected matcher example as a warning. Data: https://cartforagents.com/guides/winter-clothing-product-data.json
- [AI shopping product research: what 162 searches returned from Shopify's agent catalog](https://cartforagents.com/research/agent-shopping-research): What 162 shopper searches returned from Shopify's agent catalog on October 26, 2026: 1,620 listings, which facts were present or blank, worked examples and a mistake we made. Data: https://cartforagents.com/research/agent-shopping-research.json
- [Product data unit normalization: how we mistook -30 °C for a missing rating](https://cartforagents.com/research/ai-product-data-unit-normalization): Reconstruct our minus-30 normalization failure with raw passages, expected matches and regression cases before labeling a product fact absent. Data: https://cartforagents.com/research/ai-product-data-unit-normalization.json
- [Seller concentration in AI shopping results: count products, variants and sellers](https://cartforagents.com/research/ai-shopping-seller-concentration): Ten results can be one seller: a recount of dog-boot, backpack and tent shelves in Shopify's agent catalog by product ID, variant and seller. Data: https://cartforagents.com/research/ai-shopping-seller-concentration.json
- [AI visibility score methodology: why we retired our own score](https://cartforagents.com/research/ai-visibility-score-methodology): Rebuild the failure of our first gap score using missingness, normalization errors and component contribution checks rather than a replacement grade. Data: https://cartforagents.com/research/ai-visibility-score-methodology.json
- [Which article titles AI agents cite: a simulation across Claude, GPT and Gemini](https://cartforagents.com/research/article-titles-agent-reading-simulation): Plain titles were cited almost every time, clever ones mostly weren't: a simulation of which article titles Claude, GPT and Gemini models cite and choose to read. Data: https://cartforagents.com/research/article-titles-agent-reading-simulation.json
- [Missing product review data: a blank rating is not a zero](https://cartforagents.com/research/missing-product-review-data): Audit absent, null, explicit-zero and positive review states with field paths and denominator rules before calculating summaries. Data: https://cartforagents.com/research/missing-product-review-data.json
- [Shopify Catalog vs ChatGPT results: how to report a catalog finding](https://cartforagents.com/research/shopify-catalog-vs-chatgpt-results): Use a proxy-to-outcome checklist to distinguish returned Catalog facts from live assistant retrieval, recommendations, seller choice and orders. Data: https://cartforagents.com/research/shopify-catalog-vs-chatgpt-results.json
- [Native checkout in Shopify Catalog: all 1,620 results said no, and every one had a buy link](https://cartforagents.com/research/ucp-catalog-native-checkout-research): Recount first-variant checkout flags in the tested unpersonalized context and separate a false flag from all live purchase routes. Data: https://cartforagents.com/research/ucp-catalog-native-checkout-research.json
- [Vague vs specific product facts: simulated picks by Claude, GPT and Gemini models](https://cartforagents.com/research/vague-specific-product-facts-simulation): Vague listings were almost never picked; factual ones won when they answered the shopper's brief. Pick counts across Claude, GPT and Gemini models, by brief and product. Data: https://cartforagents.com/research/vague-specific-product-facts-simulation.json
- [Quiet vs 21 dB: which humidifier facts reach AI shopping agents](https://cartforagents.com/research/quiet-humidifiers): Every noise statement on a humidifier shelf in Shopify's agent catalog, traced to the field it came from: which listings gave a decibel figure and which only said quiet. Data: https://cartforagents.com/research/quiet-humidifiers.json
- [For agents](https://cartforagents.com/for-agents): how to read and cite this site. Data: https://cartforagents.com/for-agents.json
- [Full text](https://cartforagents.com/llms-full.txt): every article above in one plain-text file.
- [Sample shelf check](https://cartforagents.com/check/sample): what a report looks like. Sample data, not a real product. Data: https://cartforagents.com/check/sample.json