What problem does it solve? Working with spreadsheets programmatically often leads to broken formulas, hardcoded values, and formatting inconsistencies. This Skill provides structured workflows for creating, editing, and analyzing Excel files (.xlsx, .xlsm, .csv, .tsv) while preserving formulas, enforcing financial modeling conventions, and guaranteeing zero formula errors. ## Core Features & Use Cases - Spreadsheet Creation & Editing: Build new workbooks or modify existing ones with openpyxl while preserving formulas, styles, and template conventions. - Formula Recalculation & Error Detection: Use the bundled recalc.py script with LibreOffice to recalculate all formulas and scan every cell for errors like #REF!, #DIV/0!, and #VALUE!. - Financial Modeling Standards: Apply industry-standard color coding (blue inputs, black formulas, green cross-sheet links), number formatting, and assumption documentation. - Data Analysis: Read and analyze spreadsheet data with pandas for statistics, filtering, and bulk operations. - Use Case: Build a three-statement financial model where all projections use live Excel formulas referencing assumption cells, then recalculate and verify the workbook contains zero formula errors before delivery. ## Quick Start Ask the assistant to create an Excel financial model with revenue projections using formulas, then recalculate and verify it has no errors.
