Grailed Resale Listings Scraper

Scrape Grailed designer and streetwear resale listings — both active and SOLD — via the Algolia search API. Returns full listing data including sold price, seller score, original retail price, and arbitrage-ready comparables.

What it does

This actor queries Grailed's Algolia search index directly, giving you fast and complete listing data without relying on rendered HTML. Each run:

1. Fetches live Algolia credentials from the Grailed page (the search key rotates — hardcoded keys don't work)
2. Pages through active listings in the Listing_production Algolia index
3. Optionally pages through sold listings in the Listing_sold_production index
4. Returns structured records with all fields needed for resale comps and arbitrage analysis

Use cases

• Resale comps: filter by designer and category to see what items actually sold for vs. asking price
• Brand arbitrage: track original retail price vs. resale price across brands and categories
• Inventory research: survey active listings for a designer or category to understand market depth and pricing
• Seller intelligence: combine seller score and total transactions to identify top-rated sellers

Input

Field	Type	Required	Description
category	string	one of these	Grailed category slug (e.g. outerwear, tops, bottoms, footwear, accessories)
designer	string	one of these	Designer / brand name (e.g. Supreme, Rick Owens, Comme des Garcons)
includeSold	boolean	no	Include SOLD listings (default: true)
maxItems	integer	no	Max total listings to return. 0 = no limit (default: 0)

Either category or designer (or both) must be provided.

Example — sold Supreme outerwear comps:

{
  "category": "outerwear",
  "designer": "Supreme",
  "includeSold": true,
  "maxItems": 500
}

Example — all active outerwear listings:

{
  "category": "outerwear",
  "includeSold": false
}

Output

Each record contains:

Field	Description
listing_id	Grailed listing ID
title	Listing title
designer	Brand or designer name
department	menswear or womenswear
category	Top-level category (e.g. outerwear)
sub_category	Sub-category (e.g. parkas)
size	Item size
condition	Condition string (e.g. is_gently_used)
price	Asking price in USD
original_price	Original retail price in USD
sold	true if the listing has sold
sold_price	Final sold price in USD (sold listings only)
sold_at	ISO-8601 timestamp when sold
seller_username	Grailed username of the seller
seller_score	Seller rating average (0–5)
location	Seller's country
listing_url	Full URL to the listing on Grailed
photo_url	Primary listing photo URL
created_at	When the listing was created
updated_at	When the listing was last updated
scrapedAt	ISO-8601 scrape timestamp

Performance and limits

• Speed: ~1000 listings/page, ~200ms between pages — expect ~5-10k listings/minute
• Memory: 256 MB
• Algolia limits: Max 500 pages x 1000 hits = 500k results per query. For categories with more than 500k listings, use designer + category filters together to scope queries under that limit.
• Setup: none — run it as it ships.

Notes

• Grailed's Algolia search key rotates. The actor extracts the live key from the page on each run — do not attempt to hardcode credentials.
• Sold listings data is only available for items sold through the Grailed platform.
• The original_price field is populated only when the seller entered it manually.