Agent context
WooCommerce models
3 SQL models that turn the raw WooCommerce tables into the reports people ask about. Deploy them in Weld and your agent queries the definitions behind every number.
How the set is built
- 7Raw tables
- 7Staging
- 4Core
- 3Analytics
Staging cleans each raw table once, core holds the logic, and analytics is the table dashboards and agents read.
- CustomersRecreates WooCommerce Analytics' Customers report: every customer, registered or guest, with orders, spend, average order value and first and last order.grain: store x customer (wc_customer_lookup.customer_id) · 4 raw tables
- Product sales over timeRecreates WooCommerce Analytics' Products and Variations reports (items sold, net sales, orders) at line grain, with the same sales equation as sales_over_time.grain: day x store x order x line · 6 raw tables
- Sales over timeRecreates WooCommerce Analytics' Revenue report (gross sales, coupons, refunds, net sales, taxes, shipping, total sales) at a grain you can slice.grain: day x store x order x row type · 3 raw tables
- Weld or dbt
- The same SQL in both dialects. Sync the folder with GitHub Sync, or copy the dbt models into your project.
- Check before you rely on it
- Reconcile a month against WooCommerce's own reports first. Each model's notes say what the synced data can and can't support.
Connect WooCommerce.
Your agents start with context.
Sync WooCommerce to your warehouse, deploy these models, and query them from Claude, Cursor or ChatGPT over MCP. Free for 14 days, no credit card.