SkuSync: Convert Shopify & SHOPLINE CSV to AI

What is llms.txt and why do I need it?

llms.txt is a standardized file format specified at llmstxt.org that helps Large Language Models discover, understand, and index your website's content. Think of it as robots.txt but for AI agents. It provides a curated index of your most important URLs and resources in a format that LLMs can easily parse.

How do I convert SHOPLINE or Shopify CSV to JSON format?

Converting CSV to JSON with SkuSync: 1) Enter your store URL, 2) Upload your SHOPLINE or Shopify product CSV file, 3) The tool automatically detects your platform and converts your data, 4) Download the generated JSON Schema, llms.txt, or NDJSON files. All processing happens in your browser.

What is the difference between JSON Schema and NDJSON output?

JSON Schema defines the structure and validation rules for your product data—useful for documentation and validation. NDJSON (Newline-Delimited JSON) contains your actual product data with one JSON object per line—ideal for streaming, batch processing, and importing into databases.

Is my product data secure when using SkuSync?

Yes. SkuSync is a client-side only application. All CSV parsing, data transformation, and file generation happens entirely in your web browser. Your product data never leaves your device and is never sent to any server.

What CSV format does SkuSync support?

SkuSync supports both SHOPLINE and Shopify product CSV exports. For SHOPLINE, it handles fields like spuid, skuid, Handle, Title*, Vendor, Tags, Collections, Path, SKU price, and Master image with multi-line header support. For Shopify, it supports Handle, Title, Body (HTML), Vendor, Type, Tags, Variant SKU, Variant Price, Variant Inventory Qty, and Image Src. The tool automatically detects the platform format.

Does the NDJSON output comply with OpenAI standards?

Yes. The NDJSON output from SkuSync is fully compliant with the OpenAI Product Feed Specification. It includes all required OpenAI fields like enable_search, enable_checkout, link, availability, inventory_quantity, seller_name, and seller_url. Price values follow the OpenAI format (e.g., '9 USD'), availability uses proper enum values (in_stock/out_of_stock), and variant data is structured with item_group_id, color, and size fields. This ensures your product data is ready for integration with OpenAI's commerce-enabled AI assistants.

Does the JSON Schema comply with Google Shopping standards?

Yes. The JSON Schema output from SkuSync is fully compliant with the Google Merchant Center Product Feed Specification for Google Shopping ads and free listings. It includes all required fields: id, title, description, link, image_link, availability, price, condition, and brand. Price values follow the Google format (e.g., '9.99 USD'), availability uses proper enum values (in_stock/out_of_stock), and condition uses new/refurbished/used values. The schema also includes recommended fields like gtin, mpn, sku, and variant data (item_group_id, color, size). This ensures your product feed can be up