ecom-analyticslisted

# Ecom Analytics Analyze e-commerce performance using data from Coupler.io dataflows (Shopify, WooCommerce, BigCommerce, Magento, GA4, Stripe, Klaviyo, etc.). This skill guides you through retrieving order/session data, computing funnel and revenue metrics, detecting anomalies, and presenting actionable insights an ecom operator can act on. ## Step 0: Context Check (Pre-requisite) Before starting any analysis, the **Data Context Check** skill (`generate-data-set-context`) runs as a gate. It calls `get-schema` on each target dataset to determine whether meaningful context (column descriptions, business rules, metric definitions, e.g. how returns are flagged, currency conventions, what counts as a 'completed' order) is attached. - If context exists → proceed to Step 1. - If context is missing → the user is offered the option to generate it first. Do not duplicate this check in Step 1d. If the context check skill has already run and context is present, Step 1d should use the enriched schema directly. ## Step 1: Discover and Select Data Sources Every analysis starts by connecting to the user's data through Coupler.io MCP tools. ### 1a. Discover available data Default to `search-datasets` with ecom-flavored keywords — `shopify`, `woocommerce`, `bigcommerce`, `magento`, `orders`, `gmv`, `ecom`, `klaviyo`, `ga4`, `stripe`, or whatever store/source the user named. Search keeps the response small and lands on the right dataflow when the domain is known (which it is, by defini