finance-analyticslisted

# Finance Analytics Analyze financial performance using data from Coupler.io dataflows (QuickBooks, Xero, Stripe, NetSuite, Sage, billing systems). This skill guides you through retrieving accounting and revenue data, computing P&L, margin, subscription, and cash metrics, detecting anomalies, and presenting actionable insights a finance lead 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 (chart of accounts mapping, entity/subsidiary structure, currency conventions, fiscal calendar, accrual vs. cash convention) 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. ## Step 1: Discover and Select Data Sources ### 1a. Discover available data Default to `search-datasets` with finance-flavored keywords — `quickbooks`, `xero`, `netsuite`, `stripe`, `sage`, `gl`, `invoice`, `revenue`, `mrr`, `arr`, `bank`, or whatever system the user named. Search keeps the response small and lands on the right dataflow when the domain is known. Fall back to `list-datasets` only when the user is genuinely browsing or hasn't given any source/keyword to anchor on. Each dataflow represents a data pipeline (e.g. "QuickBooks GL", "Stripe Charges", "NetSuite Revenue", "Xero Invoices",