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 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"
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.
Important Requirements
LibreOffice Required for Formula Recalculation: You can assume LibreOffice is installed for recalculating 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:
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 the spreadsheet remains dynamic and updateable.
❌ WRONG - Hardcoding Calculated Values
# Bad: Calculating in Python and hardcoding result
total = df['Sales'].sum()
sheet['B10'] = total # Hardcodes 5000
# Bad: Computing growth rate in Python
growth = (df.iloc[-1]['Revenue'] - df.iloc[0]['Revenue']) / df.iloc[0]['Revenue']
sheet['C5'] = growth # Hardcodes 0.15
# Bad: Python calculation for average
avg = sum(values) / len(values)
sheet['D20'] = avg # Hardcodes 42.5
✅ CORRECT - Using Excel Formulas
# Good: Let Excel calculate the sum
sheet['B10'] = '=SUM(B2:B9)'
# Good: Growth rate as Excel formula
sheet['C5'] = '=(C4-C2)/C2'
# Good: Average using Excel function
sheet['D20'] = '=AVERAGE(D2:D19)'
This applies to ALL calculations - totals, percentages, ratios, differences, etc. The spreadsheet should be able to recalculate when source data changes.
Common Workflow
- Choose tool: pandas for data, openpyxl for formulas/formatting
- Create/Load: Create new workbook or load existing file
- Modify: Add/edit data, formulas, and formatting
- Save: Write to file
- Recalculate formulas (MANDATORY IF USING FORMULAS): Use the recalc.py script
python recalc.py output.xlsx
- Verify and fix any errors:
1---2name: xlsx-official3description: 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, ....4---567# Requirements for Outputs89## All Excel files1011### Zero Formula Errors12- Every Excel model MUST be delivered with ZERO formula errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?)1314### Preserve Existing Templates (when updating templates)15- Study and EXACTLY match existing format, style, and conventions when modifying files16- Never impose standardized formatting on files with established patterns17- Existing template conventions ALWAYS override these guidelines1819## Financial models2021### Color Coding Standards22Unless otherwise stated by the user or existing template2324#### Industry-Standard Color Conventions25- **Blue text (RGB: 0,0,255)**: Hardcoded inputs, and numbers users will change for scenarios26- **Black text (RGB: 0,0,0)**: ALL formulas and calculations27- **Green text (RGB: 0,128,0)**: Links pulling from other worksheets within same workbook28- **Red text (RGB: 255,0,0)**: External links to other files29- **Yellow background (RGB: 255,255,0)**: Key assumptions needing attention or cells that need to be updated3031### Number Formatting Standards3233#### Required Format Rules34- **Years**: Format as text strings (e.g., "2024" not "2,024")35- **Currency**: Use $#,##0 format; ALWAYS specify units in headers ("Revenue ($mm)")36- **Zeros**: Use number formatting to make all zeros "-", including percentages (e.g., "$#,##0;($#,##0);-")37- **Percentages**: Default to 0.0% format (one decimal)38- **Multiples**: Format as 0.0x for valuation multiples (EV/EBITDA, P/E)39- **Negative numbers**: Use parentheses (123) not minus -1234041### Formula Construction Rules4243#### Assumptions Placement44- Place ALL assumptions (growth rates, margins, multiples, etc.) in separate assumption cells45- Use cell references instead of hardcoded values in formulas46- Example: Use =B5*(1+$B$6) instead of =B5*1.054748#### Formula Error Prevention49- Verify all cell references are correct50- Check for off-by-one errors in ranges51- Ensure consistent formulas across all projection periods52- Test with edge cases (zero values, negative numbers)53- Verify no unintended circular references5455#### Documentation Requirements for Hardcodes56- Comment or in cells beside (if end of table). Format: "Source: [System/Document], [Date], [Specific Reference], [URL if applicable]"57- Examples:58 - "Source: Company 10-K, FY2024, Page 45, Revenue Note, [SEC EDGAR URL]"59 - "Source: Company 10-Q, Q2 2025, Exhibit 99.1, [SEC EDGAR URL]"60 - "Source: Bloomberg Terminal, 8/15/2025, AAPL US Equity"61 - "Source: FactSet, 8/20/2025, Consensus Estimates Screen"6263# XLSX creation, editing, and analysis6465## Overview6667A 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.6869## Important Requirements7071**LibreOffice Required for Formula Recalculation**: You can assume LibreOffice is installed for recalculating formula values using the `recalc.py` script. The script automatically configures LibreOffice on first run7273## Reading and analyzing data7475### Data analysis with pandas76For data analysis, visualization, and basic operations, use **pandas** which provides powerful data manipulation capabilities:7778```python79import pandas as pd8081# Read Excel82df = pd.read_excel('file.xlsx') # Default: first sheet83all_sheets = pd.read_excel('file.xlsx', sheet_name=None) # All sheets as dict8485# Analyze86df.head() # Preview data87df.info() # Column info88df.describe() # Statistics8990# Write Excel91df.to_excel('output.xlsx', index=False)92```9394## Excel File Workflows9596## CRITICAL: Use Formulas, Not Hardcoded Values9798**Always use Excel formulas instead of calculating values in Python and hardcoding them.** This ensures the spreadsheet remains dynamic and updateable.99100### ❌ WRONG - Hardcoding Calculated Values101```python102# Bad: Calculating in Python and hardcoding result103total = df['Sales'].sum()104sheet['B10'] = total # Hardcodes 5000105106# Bad: Computing growth rate in Python107growth = (df.iloc[-1]['Revenue'] - df.iloc[0]['Revenue']) / df.iloc[0]['Revenue']108sheet['C5'] = growth # Hardcodes 0.15109110# Bad: Python calculation for average111avg = sum(values) / len(values)112sheet['D20'] = avg # Hardcodes 42.5113```114115### ✅ CORRECT - Using Excel Formulas116```python117# Good: Let Excel calculate the sum118sheet['B10'] = '=SUM(B2:B9)'119120# Good: Growth rate as Excel formula121sheet['C5'] = '=(C4-C2)/C2'122123# Good: Average using Excel function124sheet['D20'] = '=AVERAGE(D2:D19)'125```126127This applies to ALL calculations - totals, percentages, ratios, differences, etc. The spreadsheet should be able to recalculate when source data changes.128129## Common Workflow1301. **Choose tool**: pandas for data, openpyxl for formulas/formatting1312. **Create/Load**: Create new workbook or load existing file1323. **Modify**: Add/edit data, formulas, and formatting1334. **Save**: Write to file1345. **Recalculate formulas (MANDATORY IF USING FORMULAS)**: Use the recalc.py script135 ```bash136 python recalc.py output.xlsx137 ```1386. **Verify and fix any errors**: 139 - The script returns