Xlsx

--- name: xlsx description: "Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc.) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modifying existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas" license: Proprietary. LICENSE.txt contains the complete terms --- # Requirements for Outputs ## All Excel files ### Zero Formula Errors - Every Excel model MUST be delivered with ZERO formula errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?) ### Preserve Existing Templates (when updating templates) - Study and EXACTLY match existing format, style, and conventions when modifying files - Never impose standardized formatting on files with established patterns - Existing template conventions ALWAYS override these guidelines ## Financial models ### Color Coding Standards Unless otherwise specified by the user or an existing template #### Industry-Standard Color Conventions - Blue text (RGB: 0,0,255): Hardcoded inputs and numbers that users will change for scenarios - Black text (RGB: 0,0,0): ALL formulas and calculations - Green text (RGB: 0,128,0): Links referencing other worksheets within the same workbook - Red text (RGB: 255,0,0): External links to other files - Yellow background (RGB: 255,255,0): Key assumptions requiring attention or cells that need to be updated ### Number Formatting Standards #### Required Format Rules - Years: Format as text strings (e.g., "2024" not "2,024") - Currency: Use the $#,##0 format; ALWAYS specify units in headers ("Revenue ($mm)") - Zeros: Use number formatting to display all zeros as "-", including percentages (e.g., "$#,##0;($#,##0);-") - Percentages: Use the 0.0% format by default (one decimal) - Multiples: Format as 0.0x for valuation multiples (EV/EBITDA, P/E) - Negative numbers: Use parentheses (123), not minus -123 ### Formula Construction Rules #### Assumption Placement - Place ALL assumptions (growth rates, margins, multiples, etc.) in separate assumption cells - Use cell references instead of hardcoded values in formulas - Example: Use =B5(1+$B$6) instead of =B51.05 #### Formula Error Prevention - Verify that all cell references are correct - Check for off-by-one errors in ranges - Ensure consistent formulas across all projection periods - Test with edge cases (zero values, negative numbers) - Verify there are no unintended circular references #### Documentation Requirements for Hardcodes - Include a comment or note in the adjacent cell (if at the end of the table). Format: "Source: [System/Document], [Date], [Specific Reference], [URL if applicable]" - Examples: - "Source: Company 10-K, FY2024, Page 45, Revenue Note, [SEC EDGAR URL]" - "Source: Company 10-Q, Q2 2025, Exhibit 99.1, [SEC EDGAR URL]" - "Source: Bloomberg Terminal, 8/15/2025, AAPL US Equity" - "Source: FactSet, 8/20/2025, Consensus Estimates Screen" # XLSX creation, editing, and analysis ## Overview A user may ask you to create, edit, or analyze the contents of an .xlsx file. You have various tools and workflows available for different tasks. ## Important Requirements LibreOffice Required for Formula Recalculation: You can assume that LibreOffice is installed to recalculate formula values using the recalc.py script. The script automatically configures LibreOffice on first run ## Reading and Analyzing Data ### Data Analysis with pandas For data analysis, visualization, and basic operations, use pandas, which provides powerful data manipulation capabilities: ``python import pandas as pd # Read Excel df = pd.read_excel('file.xlsx') # Default: first sheet all_sheets = pd.read_excel('file.xlsx', sheet_name=None) # All sheets as dict # Analyze df.head() # Preview data df.info() # Column info df.describe() # Statistics # Write Excel df.to_excel('output.xlsx', index=False) `` ## Excel File Workflows ## CRITICAL: Use Formulas, Not Hardcoded Values Always use Excel formulas instead of calculating values in Python and hardcoding them. This ensures