What problem does it solve? Working with spreadsheet files programmatically often leads to hardcoded values, broken formulas, and inconsistent formatting. This Skill provides a structured workflow for creating, editing, and analyzing .xlsx, .xlsm, .csv, and .tsv files so the output remains dynamic, error-free, and professionally formatted. ## Core Features & Use Cases - Formula-Driven Spreadsheets: Writes native Excel formulas instead of hardcoded Python-calculated values, keeping workbooks dynamic and updateable. - Mandatory Recalculation & Error Detection: Uses the bundled recalc.py script with LibreOffice to recalculate all formulas and report #REF!, #DIV/0!, #VALUE!, and other errors with exact cell locations. - Financial Modeling Standards: Enforces industry color conventions (blue inputs, black formulas, green cross-sheet links), number formatting rules, and source documentation for hardcoded values. - Use Case: A user asks to build a revenue projection model from a messy CSV export. The Skill cleans the data with pandas, builds the model with openpyxl using live formulas and assumption cells, recalculates with LibreOffice, and delivers a workbook with zero formula errors. ## Quick Start Use the xlsx skill to clean up the messy sales data in report.csv and turn it into a formatted Excel workbook with a summary sheet using formulas.