What problem does it solve? Turning raw CSV or tabular data into a board-ready Excel dashboard requires coordinating KPI formulas, cell-range-linked charts, sparklines, conditional formatting, print setup, and workbook-level settings like activeTab and fullCalcOnLoad — a process that is error-prone and easy to get wrong (stale cached values, blank charts, clipped titles). ## Core Features & Use Cases - Dashboard-first composition: Creates a dedicated Dashboard sheet with formula-driven KPI cards, multiple charts, sparklines, and semantic conditional formatting, while raw data and aggregations stay on upstream Data/Summary sheets. - Design guidance: Provides layout patterns (executive summary, ops console, scorecard), complexity scaling by data size, chart-type selection tables, and column-width sizing rules to prevent ### rendering. - Eight-gate QA delivery cycle: Enforces verifiable checks for KPI formula coverage, chart count and title width, series naming, CF rules, activeTab/fullCalcOnLoad, placeholder leaks, visual floor, and cachedValue sanity. - Use Case: Given a 12-month revenue CSV, produce a single .xlsx that opens on a Dashboard sheet showing Total Revenue and other KPIs, a linked line chart, a sparkline, and print-ready settings for a board pack. ## Quick Start Ask the AI to build an executive KPI dashboard from your sales CSV file with revenue KPI cards, a trend chart, and conditional formatting, delivered as a single xlsx file.