/xlsx

name: xlsx
description: "Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When GLM 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) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas"
license: Proprietary. LICENSE.txt has complete terms

XLSX creation, editing, and analysis

Overview

A user may ask you to create, edit, or analyze the contents of an .xlsx file. You have different tools and workflows available for different tasks.

Must output excel files.

Important Requirements

**Python 3 and openpyxl Required for Excel Generation**: You can assume Python 3 as the runtime environment. The `openpyxl` library is required as the primary tool for creating Excel files, managing styles, and writing formulas.

**pandas Utilized for Data Processing**: You can utilize `pandas` for efficient data manipulation and processing tasks. The processed data is subsequently exported to the final Excel file through `openpyxl`.

**LibreOffice Required for Formula Recalculation**: You can utilize `recalc.py` for formula check. You can assume LibreOffice is installed for recalculating formula values using the `recalc.py` script. The script automatically configures LibreOffice on first run.

Requirements for Outputs

All Excel files

Critical Instruction Protocols

Query Decomposition & Verification

Before generating any code, strictly analyze the user's prompt.

• **Explicit Requests**: Analyze Explicit Needs: Clearly identify the analytical objectives, constraints, required formats, the Excel sheets to be delivered (including sheet names, column definitions, calculation logic, and required metrics), as well as all data fields explicitly requested by the user. These elements define the mandatory delivery scope and specify exactly what must be built in the workbook.
• **Implicit Requests**:Analyze Implicit Needs: Evaluate the business context, intended users of the Excel file, expected interaction patterns (e.g., filtering, sorting, manual inputs), and downstream use cases such as reporting or decision support. These considerations guide how sheets are structured, formulas are designed, and results are presented to ensure usability and clarity.
• **Multi-Part Requests**: If the user asks for "two tables", "three scenarios", or "a summary and a detail sheet", you MUST generate ALL requested components.

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 stated by the user or existing template

Industry-Standard Color Conventions

• **Blue text (RGB: 0,0,255)**: Hardcoded inputs, and numbers users will change for scenarios
• **Black text (RGB: 0,0,0)**: ALL formulas and calculations
• **Green text (RGB: 0,128,0)**: Links pulling from other worksheets within same workbook
• **Red text (RGB: 255,0,0)**: External links to other files
• **Yellow background (RGB: 255,255,0)**: Key assumptions needing 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 $#,##0 format; ALWAYS specify units in headers ("Revenue ($mm)")
• **Zeros**: Use number formatting to make all zeros "-", including percentages (e.g., "$#,##0;($#,##0);-")
• **Percentages**: Default to 0.0% format (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

Assumptions 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 =B5*1.05

Formula Error Prevention

• Verify 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 no unintended circular references

Documentation Requirements for Hardcodes

• Comment or in cells beside (if end of 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"

Style Rules

Implement all styling directly using the `python-openpyxl` library. The following standards define the visual architecture of the spreadsheets.

Global Layout & Design Principles

**Layout & Dimensions**

• **Canvas Origin**: Content MUST start at cell **B2** to provide a top-left padding margin. Do not start at A1.
• **Cell Sizing**: Optimize column widths and row heights for data readability. Avoid unscaled cells (e.g., narrow columns with excessive height).
• **Title Row**: Row 2 is reserved for the title. Explicitly set row height to prevent clipping: `row_dimensions[2].height = 30` (adjust upwards if font size requires).

**Visual Hierarchy**

• **Professionalism**: Prioritize business-appropriate color schemes. Avoid decorative elements that distract from data.
• **Consistency**: Apply uniform fonts, borders, and colors to similar data types across the