CrystallizeBoutique Universe

Build yours with AI

A store like Boutique Universe, with your brand

Copy this prompt and paste it into a coding agent (Claude Code, Cursor or Codex) in an empty folder. It asks for your Crystallize tenant, your products and your brand, then builds the store on your own tenant.

Raw Markdown

I want a storefront for my business that works like Boutique Universe (https://boutique-universe.superfast.shop), a demo store built on Crystallize: Small hotels, villas and unusual places to stay, booked natively in Crystallize: rooms and cabins from a pool, experiences in time slots, and a concierge that searches, checks availability and holds the dates.

The content model and the wiring below are proven in that store: keep them for the features I want, and rename things to fit my trade. If a feature doesn't fit my business, leave its parts out rather than forcing it. Everything I see is mine to decide: brand, colours, typography, layout, copy and pages. Don't copy the demo's look; build my brand.

What the demo does: native booking, time-slot bookings, vector personalisation, explainable ranking, member pricing, multiple markets, ai concierge. It is B2C, in English, Norwegian, Swedish, Dutch; my markets and languages may differ.

How to work with me

  • You need to run commands, edit files and use MCP tools. If you can't (for example in a plain chat), tell me, and suggest I paste this prompt into Claude Code, Cursor or another coding agent instead.
  • Ask your questions a few at a time (three to five), in the order of the steps below, and suggest a sensible default for each so I can just say yes. Ask each thing once, even where two lists overlap, and ask the ones that change the build first. Don't start a step before the one before it is done.
  • The technical detail below is for you. Talk to me in plain words, and explain a choice only when I need to make it.
  • Keep the folder empty until step 5, apart from .env.local.
  • Never ask me to paste an access token secret into the chat, and tell me not to paste a filled-in command or its output either. Tell me which command to run or which file to put it in, and I'll do it.
  • Before you create or change anything in Crystallize, show me the plan (shapes, pieces, topics, price variants, markets) and wait for my yes. Before an import, show me a sample of five items.
  • Use the Crystallize skills (the skills MCP tool, or the use-crystallize plugin) for how-to: content-model, information-architecture, taxonomy, data-creation, mass-operations, pricing, query, mutation, js-api-client, responsive-images, payments, and when this store needs them subscriptions, bookable-resources, vector-ranking and permissions. Where this prompt and a skill disagree, the skill wins. Check the live schemas with the MCP instead of guessing field names.
  • When something I asked for isn't possible in Crystallize the way I pictured it, say so and offer the closest thing that is.
  • The storefront never reads from the Core API on customer-facing pages. Products, public prices, stock and content come from the Discovery API and the Catalogue API; confidential prices (negotiated B2B price lists) from the Catalogue API on the server.
  • Use the Shop API for everything about customers: carts, checkout, customers, orders (including orders created directly, such as renewals), order meta, pipeline stages, payments and subscription contracts. Take the customer identifier from the server session, never from the browser. The Core API is for setup scripts, back-office tools, scheduled jobs and what the Shop API can't do, always on the server and never once per page view.

Step 1: Crystallize tenant, tokens and MCP

Ask me:

  1. Do I have a Crystallize account and a tenant for this store? If not, I sign up for free at https://app.crystallize.com/signup and create an empty tenant. Ask for its tenant identifier.
  2. Do I have access tokens? If not, tell me: in the Crystallize App, go to Settings → Access Tokens → Generate a new token, name it, and keep the ID and the secret (the secret is shown once). A token acts with its user's role, so while we build, that user needs to be Tenant Admin (or have a role that can write shapes, pieces, topics, items and prices and run mass operations). Once the store is built, switch the MCP to a token from a read-only user.
  3. Is the Crystallize MCP connected, with write access? Check that you have its write tools (run-mass-operation, mutate-core), not only the read tools (tenant-overview, fetch-content-model): with only the read tools, it was added without ?exposeWrite=true. If it's missing, have me run this in my terminal with my own token, then restart you:
    npx add-mcp "https://mcp.crystallize.com/mcp?exposeWrite=true" \
  --header "X-Crystallize-Access-Token-Id: <token id>" \
  --header "X-Crystallize-Access-Token-Secret: <token secret>"
    If the MCP can't be connected in my tool, say so and fall back to scripts that call the Crystallize APIs with the tokens from .env.local. In Claude Code, also suggest the Crystallize skills: /plugin marketplace add crystallizeapi/ai, then /plugin install use-crystallize@crystallize-ai. The plugin brings its own read-only Crystallize MCP entry with placeholder credentials: keep using the one added above (and add &exposeSkills=false to its URL once the plugin's skills are installed).
  4. Confirm the connection with tenant-overview, and tell me what's already in the tenant. If it isn't empty, ask whether to build next to what's there or in a fresh tenant.

The storefront needs the tenant identifier and its own credentials: an access token pair for the Shop API (server only), and a static auth token if Discovery and the Catalogue API are secured. Don't reuse the admin build token in production. Put them in .env.local (have me fill in the secrets) and make sure .env* is in .gitignore.

Step 2: my business and my brand

Ask me:

  • What I sell, who buys it, and what makes us different. My brand name and a one-line pitch.
  • My markets, currencies and languages, and my VAT/tax setup.
  • Where my product data lives today: a spreadsheet or CSV, an export from Shopify, WooCommerce or another platform, a PIM or ERP, my current website, or nothing yet. Where my product images are.
  • My brand: logo (SVG if I have it), colours, typefaces, tone of voice, and two or three sites whose look I like. If I have no brand guide, propose a direction from my answers and show it before building pages.
  • Where it should run: my own domain, and hosting (suggest Vercel for Next.js).

Then ask what is particular to this kind of store:

  • Which places do I rent out, and is each booked by room or as a whole place? Are rooms named units, or identical rooms sold from a capacity?
  • My rate plans per stay (flexible, non-refundable, half-board, long-stay, members) and their prices per night, in which currencies, including or excluding VAT.
  • My booking rules: cancellation windows, how far ahead guests can book, minimum nights, fixed arrival days, check-in and check-out times.
  • Experiences I sell: times, duration, seats per slot, per person or private group, season, minimum age, who hosts them.
  • My markets, languages and VAT rates (accommodation is often taxed differently from services).
  • Loyalty tiers and their discounts, and anything members-only.
  • The themes or moods my places group into, and my regions. My own photography, or stock photos with credits?
  • An AI concierge on the site: yes or no? If yes, which AI provider and key. And my payment provider.

Step 3: the content model

Create this in my tenant with the MCP, renamed to fit my trade, after I have approved the plan. Keep the structure: it is what the storefront's features depend on.

Build in dependency order, since mass operations run in sequence with no rollback: pieces and shapes (empty first, then their components), topic maps (at most 30 topics per topic/create), price variants, markets and VAT types, the folder tree (two to four levels, five to twelve per level), and only then items. Use lowercase-hyphen identifiers. Decide now which fields are translated and which are discoverable. Restrict every item relation with acceptedShapeIdentifiers. Never add price or stock components to a shape: variants have them built in.

Text components are translated; everything is discoverable. Every shape except host gets an seo piece (title, description, image).

  • destination (folder): tagline, intro, hero images, location, map zoom, best season, getting there, worth knowing, stories.
  • property (folder): tagline, intro, cover (one image) and gallery (up to 24), story (paragraphs), location, place, booking-model (rooms or whole), service-level, price-from, max guests, bedrooms, check-in and check-out times, worth knowing, house rules, getting there, host relation, nearby relation → property (max 4), rating, review count, booked-30d, members-only boolean.
  • stay (product, the bookable resource): tagline, description, images, max guests, bedrooms, beds, size (m²), view, min nights, check-in days (empty = any day), features, rating, review count, booked-30d.
    • Variants are rate plans, attribute plan (flexible, non-refundable, half-board, long-stay, members). Variant components: includes, cancellation, min nights, members-only.
  • experience (product, sold in time slots): tagline, description, images, duration (minutes), capacity (seats per slot), meeting point, season, slot times, weather-dependent, minimum age, host. One variant, attribute unit = person or group.
  • host (document): portrait, role, bio, quote, languages, response time, three picks.
  • universe (document, a curated world): tagline, manifesto, hero, accent colour, properties (up to 24), stories. story (document) for the journal.
  • Catalogue: /stays/<destination>/<property>/<stay or experience>, plus /hosts, /universes, /journal.
  • Topic maps, where each root is a taste dimension: universe, destination, stay type, setting, pace (quiet/social), finish (rustic/refined), reach (remote/connected), climate (cold/warm), travel party, amenity, price band. Properties carry all of them; stays their own price band; experiences destination, universe and setting.
  • Pricing: prices excluding VAT, per night per unit, one price variant per currency. VAT types for accommodation and for experiences.
  • Member tiers as markets (e.g. explorer, insider, inner circle) with percentage price lists (−5, −10, −15 %). Members-only rate plans and places are hidden from lower tiers.
  • No stock locations: availability comes from booking pools.
  • Order pipelines: Stays (confirmed, pre-arrival, in house, completed, cancelled) and Experiences (booked, confirmed with host, done, cancelled).

Step 4: my data

Import my products and content with mass operations, mapping my data onto the model: validate each file with build-mass-operation, run it with run-mass-operation and follow it with get-mass-operation-status. Read the operation logs, not just the task status: a task can finish as complete with failed operations, and there is no rollback. Give every upsert a resourceIdentifier so a re-run updates instead of duplicating, and chunk large imports. Start with a small batch, check it in the Crystallize App with me, then run the rest.

Publish every imported item in each language: the storefront only sees published versions (in a mass operation, item/publish needs real itemIds). Import images from URLs with copyRemoteAsset, or upload them (presigned upload, then registerImage). Renditions are generated in a queue: after a large import, republish once they exist, and have the storefront fall back to the original image URL while variants is empty. Before building pages, query Discovery once; if the tenant isn't ignited yet, run igniteDiscoApi (with stacks: opensearch if we use vector ranking), wait for the task to complete, and allow a few minutes. If I have no data yet, create a small, clearly labelled placeholder set (ten or so products) so we can build the pages, and remind me to replace it.

  • The demo's places are fictional, one JSON file per property plus a translation per language, with Unsplash photos credited in the caption.
  • From me: my places, their rooms or units, rate plans and prices, experiences and slots, hosts, photos, regions, booking policies, VAT and loyalty tiers.
  • Build order: tenant → model → topics → catalogue → booking setup → images → translations → vectors (last) → customers.

Step 5: the storefront

  • Next.js (App Router) on Vercel, a map (MapLibre), plain fetch GraphQL clients.
  • Discovery API for every read. Shop API for holds, carts and orders: the server exchanges the tokens for a JWT at /auth/token (scopes cart, cart:admin, order, plus a separate server-only token with booking and booking:admin for the booking admin); the browser only holds the cart id in an httpOnly cookie.
  • Booking setup (Core API):
    • Booking policies with a booking horizon, cancellation window and hold times. The demo uses: hotel rooms (450 days ahead, cancel 48 h), whole places (cancel 14 days), experiences (cancel 24 h), pending holds 20 minutes, placed holds 24 hours. Every duration is in seconds (450 days = 38880000, 48 h = 172800, 20 min = 1200): read humanized back after createBookingPolicy. After editing a policy, run reapplyBookablePolicy per product, then publish.
    • setBookable on each stay product: named rooms → a unit pool, identical rooms → a capacity pool, a whole place → a pool of one; an experience → a capacity of seats. All rate plans share the product's pool. Publish afterwards.
  • Availability: Shop availability(productId, sku, range, granularitySec: 86400, language) gives free, freeUnitIds and reason per night (language is required; the wrong one reads as not bookable). nearestAvailability(productId, sku, around, durationSec, n, language) suggests other dates, and checkBooking does a dry run. The storefront enforces minimum nights and arrival days.
  • Hold: hydrate an empty cart with the context (language, currency, price variant, markets, customer), then bookSkuItem with quantity (rooms or guests), tax rate and the booking window (in the property's time zone). The input is { sku, quantity, booking: { start, end, unitId? }, meta }. Check __typename: conflicts come back as results (ReservationConflict, NotBookable, InvalidRange, InvalidUnitId), not errors; on a conflict, try the next free unit. Write the unit id into the line meta yourself. The Shop API prices a booked line as one night: add the other nights as an external companion line pointing at it.
  • Checkout: check the holds are still live → setCustomer, with checkout meta on the cart through hydrate(input: { meta }) → place → confirmCartBooking → /order createFromCart into the right pipeline → wait for the cart's order id → confirmCartBooking again to link the reservations to the order. Don't call fulfill. A confirmed reservation never expires: if payment fails after the first confirmCartBooking, cancel the reservations on /booking/admin (cancel or bulkCancel).
  • Taste ranking:
    • Vocabularies: world (universe, setting, stay type), mood (pace, finish, reach, climate), party (travel party, price band).
    • Set every property's, stay's and experience's taste from its topics: setItemTaste → rewrite the variant components → publishItem per item and language → igniteDiscoApi(stacks: opensearch), and poll until it's complete.
    • Build the guest's taste per request from their persona, a mood dial and past stays, pass it as context.userTaste, and rank with tasteCosine per vocabulary plus boosts on rating and bookings. Build the "because…" lines from the guest's own taste weights and the item's topics; use explain: true only behind a debug flag, since it's a tuning tool. With no taste yet, rank on the house terms only.
  • Concierge (optional): a streamed chat endpoint with tools that search stays, show a property, check availability, hold a stay or experience and show the trip, all over Discovery and the Shop API. It only holds after the guest says yes.
  • Env: CRYSTALLIZE_TENANT_IDENTIFIER, CRYSTALLIZE_ACCESS_TOKEN_ID, CRYSTALLIZE_ACCESS_TOKEN_SECRET, NEXT_PUBLIC_SITE_URL, and the AI provider's key if there is a concierge.

Build my design, not a demo's: my typefaces, colours and tone, with pages that suit my products. Show me the home page, a category and a product page early, and adjust the design with me before building the rest.

Every page is built for search engines, answer engines and AI agents from the start, not added at the end:

  • SEO: server-rendered HTML, one <h1>, a unique title and description, canonical URLs, hreflang per language, a sitemap and robots.txt, and clean, translated paths.
  • Structured data: JSON-LD on every page that has a subject: Organization and WebSite (with a SearchAction) on the home page, Product with Offer (price, currency, availability) on product pages, BreadcrumbList on categories and products, Article or Recipe on content. Generate it from the same data as the page.
  • GEO, for answer engines and agents: /llms.txt (an H1, a summary, links to every section), /llms-full.txt, and a Markdown twin of every page (its URL plus .md, or Accept: text/markdown), with prices, stock and facts written out in plain sentences.
  • Agents can act, not only read: register the store's actions (search, add to cart, check availability) with WebMCP (navigator.modelContext.registerTool, or annotated forms), and keep the accessibility tree clean: semantic HTML, labelled controls, real buttons and links.
  • Fast and stable: responsive images from Crystallize, no layout shift (reserve space for images and late content), little client JavaScript. Aim for 100 in every Lighthouse category (Performance, Accessibility, Best Practices, SEO; heavy 3D or video pages may score lower on performance) and pass every Agentic Browsing check.

Step 6: run it, then ship it

Run it locally and walk me through each feature above with my own data. Fix what I find. Before you call it done, run Lighthouse on the home page, a category and a product page (npx lighthouse <url> --only-categories=performance,accessibility,best-practices,seo,agentic-browsing), validate the JSON-LD (https://validator.schema.org), open /llms.txt and a page's .md twin, and fix what falls short. Deploy only when I ask: set the same environment variables on the host, point my domain, and give me the live URL.

Watch out for

  • Set item tastes last: setItemTaste writes drafts and empties variant components. Rewrite the rate-plan components, publish every language and re-index; redo it after any catalogue change.
  • Updating with components replaces the whole set; use updateComponent. updateProduct(variants) replaces all variants.
  • Send numeric components with units when creating a product, even optional ones.
  • bookSkuItem quantity is pool units, not nights. Repricing a booked line makes place fail, so use companion lines. Serialise booking writes per cart (a concurrent bookSkuItem silently loses one) and read the cart back. Every hydrate must resend each booked line with its booking { start, end, unitId }, line id and meta, or that booking is cancelled. Remove a booking by re-hydrating without it. After place the cart can't be hydrated.
  • Set the customer on the cart before booking: a reservation records its holder only when it's made. An orphaned hold lets go by itself after the pending hold time. Give rate-plan variants images (the admin calendar shows them).
  • In Discovery, pass context as a variable (its weight keys contain colons; rankBy too, ideally); tieBreaker is required; never send context: null; vocabulary enum values only exist after an index run; new components need a re-index and a few minutes.
  • Resend pathIdentifier on every topic translation, parents first.
  • A percentage price list adds its modifier: a discount is negative.
  • Orders must be created through the Shop API.
  • Don't invent facts about my business (prices, stock, certifications, delivery promises). Ask, or leave a clearly marked placeholder.

And for every Crystallize store, from the skills:

  • Orders: create and change them through the Shop API /order (createFromCart, create, setMeta with merge: true, addToStage, setPayments). Editing an order in Core adds a duplicate to the Shop API's list. Read a customer's orders with the identifier from the session, limit: 100, grouped by coreId (keep the newest). Seed order history through /order create, not Core registerOrder. The order id is the cart id; don't call fulfill after createFromCart.
  • Payments: create the order from the payment provider's verified webhook, never from the browser, once per cart.
  • Cart meta goes in hydrate(input: { meta }); hydrate is the whole cart, so send every line each time.
  • Images: serve them straight from Crystallize (not through an image optimizer such as next/image in its default setup): a WebP srcset from the returned variants with an accurate sizes, falling back to the original URL while renditions are missing. Replace an image by uploading a new one, not with registerImageRevision.
  • Ranking (if the store ranks per shopper): check that __type(name: "RankByInput") exists; pass context as a variable, with userTaste entries of { vocabulary, weights, magnitude } (magnitude = the square root of the sum of squared weights); tieBreaker is required; don't combine sorting with ranking, and page with skip and limit inside the rerank window; introspect TenantRankByField for field names; leave context out when there's no taste; use explain: true only for tuning.
  • Bookings (if the store books): durations are in seconds; the role needs the bookingPolicies permission; put the customer on the cart before bookSkuItem; every hydrate must resend each booked line with its window and unit, or the booking is cancelled; remove a booking by re-hydrating without it.

Done when

  • My tenant has the content model above with my products, prices and images in it.
  • The storefront runs on my domain in my brand, and every feature I chose works with my data: we have clicked through each one together.
  • Lighthouse scores close to 100 in every category and every Agentic Browsing check passes on the home, category and product pages.
  • I know how to add a product, change a price and publish, in the Crystallize App.