Sotheby's Search Lots

Purpose

Search Sotheby's auction catalog — upcoming, live, and past — across the full filter surface their public site exposes (category/department, sale type, sale status, estimate range, artist/maker, year, medium, region, lot characteristics, sort order, pagination) and return matching lots as structured JSON, plus the parent sale's metadata. Also handles direct sale-URL and direct lot-URL inputs (skipping search). Read-only — never bids, watches, or signs in.

When to Use

• Catalog-wide artist / brand monitoring ("any Basquiat coming up at Sotheby's", "every Rolex Daytona in the watches calendar").
• Department or location browse ("all upcoming Wine sales in Hong Kong", "Modern Evening sales in NY this season").
• A user-supplied search URL or sale URL — pipe straight through to lot extraction.
• A user-supplied lot URL — fetch the single lot and skip search entirely.
• Bulk pull of a sale's full lot list for analysis (price-band coverage, consignor patterns, etc.).
• Cross-sale comparison of past hammer results for a creator (subject to result-hiding gotcha below).

Workflow

Sotheby's catalog is a Next.js front end backed by Algolia (search/listing) plus a federated GraphQL gateway (lot detail, live bid state, image renditions). Both are reachable without authentication. The Algolia search-only API key rotates per page-load — harvest it from any catalog page's __NEXT_DATA__ script tag and reuse for ~3.8 hours. The browser path is significantly slower (the search/buy pages are 100% client-rendered, so snapshot-based extraction is one DOM round-trip per lot) and the API path returns the same data the rendered page would. Lead with API.

Endpoints in this skill:

• Algolia search: https://KAR1UEUPJD-dsn.algolia.net/1/indexes/{indexName} (GET or POST)
• GraphQL gateway: https://clientapi.prod.sothelabs.com/graphql (GET with query= + variables=, or POST JSON; no auth)
• Canonical web pages: https://www.sothebys.com{slug} — slug field on each Algolia hit is the lot detail path

1. Harvest a search-only Algolia key

The key is embedded in every Sotheby's catalog page under <script id="__NEXT_DATA__">. Two surfaces give two different scopes:

For most user intents (artist search, department browse, location filter, past-results) use the broad key from a browse page (/en/buy/fashion/handbag is a reliable harvest source). For a user-supplied sale URL, harvest from that page directly.

# Harvest the broad key
HTML=$(browse cloud fetch "https://www.sothebys.com/en/buy/fashion/handbag" --proxies --allow-redirects | jq -r .content)
KEY=$(echo "$HTML" | python3 -c "
import sys, re, json
m = re.search(r'<script[^>]*id=\"__NEXT_DATA__\"[^>]*>(.+?)</script>', sys.stdin.read(), re.DOTALL)
print(json.loads(m.group(1))['props']['pageProps']['algoliaSearchKey'])
")
# Constant for the foreseeable future:
APP_ID=KAR1UEUPJD

The key is base64-encoded; when decoded it carries validUntil=<epoch> (~3.8h from issuance) plus a restrictIndices list plus a hard-coded filters prefix (e.g. NOT state:Created AND NOT isHidden:true ...). Don't try to forge or modify it — Algolia signs the inner payload. Just harvest and pass through.

2. Map user filter inputs to Algolia params

Hit prod_lots for auction lots (947k records across history + upcoming), prod_product_items for the Buy-Now / Marketplace surface. The prompt's filter surface maps as:

Example — Contemporary or Modern Art, upcoming, $100k–$5M, page 0:

APP_ID=KAR1UEUPJD
FF=$(python3 -c '
import urllib.parse, json
print(urllib.parse.quote(json.dumps([
    ["departments:Contemporary Art","departments:Modern Art"],
    ["auctionState:PUBLISHED"],
    ["withdrawn:false"]
])))')
NF=$(python3 -c '
import urllib.parse, json
print(urllib.parse.quote(json.dumps(["lowEstimate>=100000","highEstimate<=5000000"])))')
URL_KEY=$(python3 -c "import urllib.parse,sys;print(urllib.parse.quote(sys.argv[1]))" "$KEY")
URL="https://${APP_ID}-dsn.algolia.net/1/indexes/prod_lots?query=&hitsPerPage=48&page=0&facetFilters=$FF&numericFilters=$NF&x-algolia-application-id=$APP_ID&x-algolia-api-key=$URL_KEY"
browse cloud fetch "$URL" --proxies

For the marketplace surface (Buy Now / Bid Now / Private Sale), swap index to prod_product_items and use these facets instead: waysToBuy (buyNow|bid|private), salesChannel, categories.lvl0, categories.lvl1, Handbag Type, Brand, etc. (Algolia returns the full facet menu via facets=["*"].) The harvested broad key works against both indices.

3. Decode each Algolia hit (prod_lots)

Each hit on prod_lots is a flat JSON object. The fields you need:

Discover the full per-department attribute set on demand:

GET .../1/indexes/prod_lots?query=&hitsPerPage=0&facets=%5B%22*%22%5D&facetFilters=%5B%5B%22departments%3AWatches%22%5D%5D

Returns facets (every distinct value with hit-count) and facets_stats (min/max/avg/sum for every numeric attribute scoped to that department).

4. Enrich a lot with description / provenance / images via GraphQL

The Algolia hit does not include the catalogue description, dimensions, signature line, provenance, exhibition history, literature, full image renditions, condition-report disclaimers, or the realized hammer/premium price. Those live on the lot detail page's Apollo cache, served by the GraphQL gateway. Query:

query GetLot($lotId: String!) {
  lotV2(lotId: $lotId, countryOfOrigin: "US", language: ENGLISH) {
    ... on LotV2 {
      lotId
      title
      subtitle
      description           # HTML with medium/dimensions/signature/date block
      provenance            # HTML, <br>-separated
      literature            # HTML
      exhibition            # HTML
      creatorsDisplayTitle
      estimateV2 {
        ... on LowHighEstimateV2 {
          lowEstimate { amount currency }
          highEstimate { amount currency }
        }
      }
      lotNumber {
        __typename
        ... on VisibleLotNumber { lotDisplayNumber }
      }
      withdrawnState { state }       # NotAffected | Withdrawn | Passed | ...
      bidState {
        __typename
        closingTime
        sold {
          __typename                  # ResultHidden when price is suppressed
          ... on ResultVisible { __typename }  # query specific fields when surfaced
        }
      }
      media(imageSizes: [Large, Medium, Small, ExtraLarge, ExtraExtraLarge]) {
        images {
          title
          renditions { width height url imageSize }
        }
      }
    }
  }
}

Send via GET:

https://clientapi.prod.sothelabs.com/graphql?query=<urlenc-query>&variables=<urlenc-{"lotId":"..."}>

Or POST application/json with {query, variables}. Both work, no auth, no cookies.

media.images[i].renditions[j].url is a Brightspot CDN URL with size variants (Small ~385px, Medium ~800px, Large ~1024px, ExtraLarge ~2048px). Pick Large for typical use; pick ExtraExtraLarge only when zoom matters.

5. Branch on input shape

• Direct lot URL (/en/buy/auction/.../lot.<n> or /en/buy/auction/{year}/{sale}/{lot-slug}) → fetch the page, pull lotId + auctionId from __NEXT_DATA__.query, GraphQL lotV2 for the full record. Skip Algolia entirely.
• Direct sale URL (/en/buy/auction/{year}/{sale-slug}) → harvest the sale-scoped Algolia key from that page, then page through prod_lots (filter is pre-applied). algoliaJson in pageProps is the first page of results — reuse rather than re-fetching it.
• Search URL with query params → forward query params; harvest a broad key from /en/buy/fashion/handbag for the actual search.
• Department / keyword input → broad key + facetFilters as in step 2.

6. Sale-level metadata

To return sale-level fields (sale title, type, location, opening/closing datetimes, total-lot count, sale department, canonical URL) without a separate query, every Algolia lot hit carries auctionId, auctionName, auctionLocation, auctionType, auctionState, auctionDate, departments[]. To get total lot count for a sale, run a same-query Algolia call with hitsPerPage=0&facetFilters=[["auctionId:<uuid>"]] and read nbHits. Sale canonical URL: extract from any lot's slug field by trimming the last path segment (the slug for pair-of-carcasse-chenets lives under /en/buy/auction/2026/modern-evening-auction/, so the sale URL is https://www.sothebys.com/en/buy/auction/2026/modern-evening-auction).

Browser fallback

When the Algolia or GraphQL endpoints are unreachable (rare — no known anti-bot today, no auth requirements observed), drive the rendered catalog page through Browserbase with stealth:

SID=$(browse cloud sessions create --keep-alive --verified --proxies | jq -r '.id')
browse open "https://www.sothebys.com/en/buy/auction/2026/modern-evening-auction" --remote --session "$SID"
browse get markdown body --remote --session "$SID"     # extract lot grid as markdown
# Per-lot URLs are anchors of the form /en/buy/auction/{year}/{sale-slug}/{lot-slug}.
# Note: each click-into-lot costs ~3 turns; prefer the API path.
browse cloud sessions update "$SID" --status REQUEST_RELEASE

The browser path is ~100× slower than the API path on a 48-lot page (one HTTP round-trip vs. one page render + per-lot expansion).

Site-Specific Gotchas

• auctionState has 5 values with non-obvious semantics. From a 947k-lot index sample: PUBLISHED (8k) = upcoming, lots not yet open for bidding. OPENED (77k) = currently biddable (Timed or Live in their open window). CLOSING (15k) = timed auction in its final-hour wind-down. LIVE (317k) = lots from completed live-auctioneer sales (past results). CLOSED (521k) = lots from completed timed auctions / older live sales (past results). For "upcoming," filter PUBLISHED. For "currently biddable now," filter OPENED OR CLOSING. For "past results," filter LIVE OR CLOSED. Do not assume LIVE means "live right now" — it does not. When in doubt, cross-check against auctionDate vs current epoch.
• Hammer prices are not in the Algolia search index (price is null on virtually every CLOSED lot — 520k samples). For each past lot whose hammer the user wants, query lotV2(lotId).bidState.sold over GraphQL. The result is a union: ResultHidden means Sotheby's has not authorized publication (very common — many lots default to hidden, especially modern/contemporary) and there is no public surface for that price short of a Sotheby's account; ResultVisible carries the realized hammer + buyer's premium. If many lots in a result set return ResultHidden, surface that to the user honestly — don't guess or infer from estimate. This is the "registration wall" the task description hints at; account-walled price-history is a confirmed limitation, not a workaround opportunity.
• Test / QA / staging records leak into the production Algolia index. Names containing "TEST", "(COPY)", "QA ", "IT Test", "Test Sale", "Clerk Test", "TEST (ignore)", "MH 05162023 (Test)", etc. are real records that satisfy NOT isTestRecord:1 AND NOT state:Created because Sotheby's flags don't always cover them. Add a client-side regex filter for auctionName matching /\b(TEST|COPY|QA|Clerk Test|10\.24 TEST|MH 0\d)\b/i and drop those hits. The base count is reduced by ~5-15% after this filter (e.g., 333 → ~300 on the Contemporary Art upcoming sample).
• Algolia search key rotates per page-load with validUntil ≈ now + 3.8 hours. Harvested keys are stable for that window; if you're caching, expire at validUntil and re-harvest. The application ID KAR1UEUPJD and the index name prod_lots (also prod_product_items for marketplace) are stable.
• The key from a sale-detail page is locked to that auctionId by an embedded filter (e.g. ... AND auctionId:c11be70d-... AND ...). Catalog-wide searches will silently return only that auction's lots. Use a key harvested from a /BrowsePage page (e.g., /en/buy/fashion/handbag) for cross-sale work.
• Facet OR vs AND: Algolia facetFilters=[[A,B],[C]] is (A OR B) AND C. Multiple departments / locations / types go in the inner array; cross-dimension AND goes in the outer array. Getting this inverted is the most common silent-failure mode.
• objectTypes always includes the sentinel "All" alongside the real type ("Painting", "Watch", etc.). When filtering, use the real type — don't include "All" in the filter.
• GraphQL introspection is disabled (Cosmo Router). You cannot __type or __schema the gateway. Field discovery is via observing __NEXT_DATA__.props.pageProps.apolloCache on a real page — that cache holds the exact subset the front end uses. Use those typenames and fragments verbatim.
• GraphQL is federated and the same field name can have different return types on sibling types. Specifically: LotV2.slug is an AuctionSlug-bearing object ({auctionSlug{name year} lotSlug}); Auction.slug is a String! scalar (was an AuctionSlug object on AuctionCard in older cache). Adding a subselection on the wrong one returns the misleading error Field "slug" must not have a selection since type "String!" has no subfields. even though another slug field in the same query requires one. Easiest fix: omit auction.slug from queries — auction.slug is just name + "/" + year if you need it; the lot's own slug plus the auction's title is enough.
• /bsp-api/* is disallowed in robots.txt and the one observed endpoint (/bsp-api/lot/details?itemId=<uuid>) returns an HTML widget page, not JSON. Don't waste time on bsp-api as a data source.
• /en/results is the legacy AEM (Adobe Experience Manager) past-results page, not Next.js — it has no __NEXT_DATA__ and no embedded Algolia key. Don't harvest from /en/results; harvest from a /en/buy/* browse page instead.
• /en/auctions, /en/auctions/upcoming, /en/buy/auction, /en/buy/now all return 404 (despite serving full HTML). Don't use them as entry points. Valid catalog entry points: /en/calendar, /en/results, /en/buy/{cat}/{subcat} (e.g., /en/buy/fashion/handbag, /en/buy/luxury/jewelry), and specific sale URLs /en/buy/auction/{year}/{sale-slug}.
• Many high-value live auctions carry both an English and a Chinese description block concatenated in the description HTML. The split is a literal ---...--- divider line. Parse and keep only the English portion when emitting lot_description, or expose both as description_en + description_zh.
• HiddenLotNumber vs VisibleLotNumber: For Premium / private-treaty lots, lotNumber.__typename === "HiddenLotNumber" and there's no lotDisplayNumber. Don't error — surface as lot_number: null and add a premium: true flag.
• Lot images are CDN-side cropped + resized via Brightspot URL params (/dims4/default/.../crop/.../resize/.../...). The URL embeds the crop spec — don't try to template it. Pick a rendition by imageSize and pass through.
• Read-only enforcement: skip every "Register to Bid", "Place Bid", "Buy Now", "Make Offer", "Watch Lot", "Sign In", "Subscribe" control on the rendered pages. None of those have any analog on the API path; the API path is read-only by construction.

Expected Output

{
  "input": {
    "query": "basquiat",
    "department": "Contemporary Art",
    "sale_status": "past",
    "min_estimate_usd": 1000000,
    "page": 0,
    "hits_per_page": 48
  },
  "total_results": 131,
  "page": 0,
  "total_pages": 3,
  "lots": [
    {
      "lot_id": "475ab55a-95dd-4ede-b86a-79cf6bfb5493",
      "lot_number": "4",
      "title": "Moon View",
      "subtitle": null,
      "artist_or_maker": "Jean-Michel Basquiat",
      "artist_dates": "1960 - 1988",
      "categories": ["Contemporary Art"],
      "object_types": ["Painting"],
      "currency": "USD",
      "low_estimate": 7000000,
      "high_estimate": 10000000,
      "estimate_upon_request": false,
      "current_bid_or_hammer": null,
      "sold": null,
      "sold_with_premium": null,
      "buyers_premium_pct": null,
      "result_status": "ResultHidden",
      "withdrawn": false,
      "withdrawn_state": "NotAffected",
      "lot_state": "Closed",
      "description": "<p>signed, titled and dated <em>1984</em> (on the reverse)</p><p>acrylic, colored Xerox paper collage and oilstick on canvas</p><p>66 by 60 ¼ in. 167.6 by 153 cm.</p>",
      "provenance": "Larry Gagosian Gallery, New York<br/>The Broad Art Foundation (acquired from the above in 1984)<br/>...",
      "literature": "Galerie Enrico Navarra, et al., <em>Jean-Michel Basquiat</em>, ...",
      "exhibition": "Arizona, Phoenix Art Museum, <em>American Art of the 1980s</em>, 1986, no. 2, n.p.; ...",
      "condition_report_available": true,
      "collection": "The Mo Ostin Collection",
      "primary_image_url": "https://sothebys-md.brightspotcdn.com/dims4/default/.../resize/1024x1111!/quality/90/?url=...n11332-b43vx-t1-01a-new.jpg",
      "additional_image_urls": [],
      "lot_url": "https://www.sothebys.com/en/buy/auction/2023/the-mo-ostin-collection-evening-auction/moon-view-2",
      "sale": {
        "sale_id": "8bbd4ef4-f194-462b-b8c2-66ba86a9558e",
        "sale_title": "The Mo Ostin Collection Evening Auction",
        "sale_type": "Live",
        "sale_status": "CLOSED",
        "sale_location": "New York",
        "sale_date": "2023-05-16T22:00Z",
        "sale_departments": ["Contemporary Art"],
        "sale_url": "https://www.sothebys.com/en/buy/auction/2023/the-mo-ostin-collection-evening-auction"
      }
    }
  ]
}

Variant shapes by sale status:

// Upcoming (PUBLISHED) — current_bid_or_hammer is the starting bid or null
{ "current_bid_or_hammer": 5000000, "sold": null, "result_status": null, "sale": {"sale_status": "PUBLISHED"} }

// Currently biddable (OPENED / CLOSING) — current_bid_or_hammer is latest bid via GraphQL bidState.latestBid
{ "current_bid_or_hammer": 6200000, "so