What problem does it solve? Working with spreadsheet files programmatically often leads to broken formulas, hardcoded values that cannot update, and Excel errors like #REF! or #DIV/0! that go unnoticed until delivery. This Skill provides a complete workflow for creating, editing, and analyzing .xlsx, .xlsm, .csv, and .tsv files while guaranteeing zero formula errors in the final deliverable. ## Core Features & Use Cases - Formula-First Spreadsheet Creation: Builds Excel files with live formulas instead of hardcoded Python-calculated values, so spreadsheets stay dynamic and recalculate when source data changes. - Automated Formula Recalculation and Error Detection: The scripts/recalc.py utility uses LibreOffice to recalculate all formulas and scans every cell for errors (#REF!, #DIV/0!, #VALUE!, #NAME?, #N/A), returning JSON with exact error locations. - Financial Modeling Standards: Enforces industry conventions including color coding (blue inputs, black formulas, green cross-sheet links), number formatting (parenthesized negatives, 0.0% percentages, 0.0x multiples), and documented hardcode sources. - Use Case: A user asks to build a revenue projection model from a messy CSV export. The Skill cleans the data with pandas, constructs the model in openpyxl with assumption cells and formulas, then runs recalc.py to verify zero errors before delivery. ## Quick Start Use the xlsx skill to create a financial model spreadsheet from my sales data CSV with formulas for totals and growth rates, then verify it has no formula errors.