working-with-spreadsheets
Creates and edits Excel spreadsheets with formulas, formatting, and financial modeling standards. Use when working with .xlsx files, financial models, data analysis, or formula-heavy spreadsheets. Covers formula recalculation, color coding standards, and common pitfalls.
How do I install this agent skill?
npx skills add https://github.com/mjunaidca/mjs-agent-skills --skill working-with-spreadsheetsIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The skill provides guidelines and code examples for managing Excel spreadsheets using standard Python libraries (pandas, openpyxl). No malicious patterns, obfuscation, or unauthorized network activities were detected in the instructions or the accompanying verification script.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
- Runlayerwarn
2/2 files flagged
What does this agent skill do?
Working with Spreadsheets
Quick Start
from openpyxl import Workbook
wb = Workbook()
sheet = wb.active
sheet['A1'] = 'Revenue'
sheet['B1'] = 1000
sheet['B2'] = '=B1*1.1' # Use formulas, not hardcoded values!
wb.save('output.xlsx')
Critical Rule: Use Formulas, Not Hardcoded Values
Always use Excel formulas instead of calculating in Python.
# WRONG - Hardcoding calculated values
total = df['Sales'].sum()
sheet['B10'] = total # Hardcodes 5000
# CORRECT - Using Excel formulas
sheet['B10'] = '=SUM(B2:B9)'
Financial Model Color Coding Standards
| Color | RGB | Usage |
|---|---|---|
| Blue text | 0,0,255 | Hardcoded inputs, scenario values |
| Black text | 0,0,0 | ALL formulas and calculations |
| Green text | 0,128,0 | Links from other worksheets |
| Red text | 255,0,0 | External links to other files |
| Yellow background | 255,255,0 | Key assumptions needing attention |
from openpyxl.styles import Font
# Input cell (user changeable)
sheet['B5'].font = Font(color='0000FF') # Blue
# Formula cell
sheet['C5'] = '=B5*1.1'
sheet['C5'].font = Font(color='000000') # Black
# Cross-sheet link
sheet['D5'] = "=Sheet2!A1"
sheet['D5'].font = Font(color='008000') # Green
Number Formatting Standards
# Currency with thousands separator
sheet['B5'].number_format = '$#,##0'
# Zeros display as dash
sheet['B5'].number_format = '$#,##0;($#,##0);-'
# Percentages with one decimal
sheet['C5'].number_format = '0.0%'
# Valuation multiples
sheet['D5'].number_format = '0.0x'
# Years as text (not 2,024)
sheet['A1'] = '2024' # String, not number
Library Selection
| Task | Library | Example |
|---|---|---|
| Data analysis | pandas | df = pd.read_excel('file.xlsx') |
| Formulas & formatting | openpyxl | sheet['A1'] = '=SUM(B:B)' |
| Large files (read) | openpyxl | load_workbook('file.xlsx', read_only=True) |
| Large files (write) | openpyxl | Workbook(write_only=True) |
Reading Excel Files
import pandas as pd
from openpyxl import load_workbook
# pandas - data analysis
df = pd.read_excel('file.xlsx')
all_sheets = pd.read_excel('file.xlsx', sheet_name=None) # Dict of DataFrames
# openpyxl - preserve formulas
wb = load_workbook('file.xlsx')
sheet = wb.active
print(sheet['A1'].value) # Returns formula string
# openpyxl - get calculated values (WARNING: loses formulas on save!)
wb = load_workbook('file.xlsx', data_only=True)
Creating Excel Files
from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill, Alignment
wb = Workbook()
sheet = wb.active
sheet.title = 'Model'
# Headers
sheet['A1'] = 'Metric'
sheet['B1'] = '2024'
sheet['A1'].font = Font(bold=True)
# Data with formulas
sheet['A2'] = 'Revenue'
sheet['B2'] = 1000000
sheet['B2'].font = Font(color='0000FF') # Blue = input
sheet['A3'] = 'Growth'
sheet['B3'] = '=B2*0.1'
sheet['B3'].font = Font(color='000000') # Black = formula
# Formatting
sheet['B2'].number_format = '$#,##0'
sheet.column_dimensions['A'].width = 20
wb.save('model.xlsx')
Editing Existing Files
from openpyxl import load_workbook
wb = load_workbook('existing.xlsx')
sheet = wb['Data'] # Or wb.active
# Modify cells
sheet['A1'] = 'Updated Value'
sheet.insert_rows(2)
sheet.delete_cols(3)
# Add new sheet
new_sheet = wb.create_sheet('Analysis')
new_sheet['A1'] = '=Data!B5' # Cross-sheet reference
wb.save('modified.xlsx')
Formula Recalculation
openpyxl writes formulas but doesn't calculate values. Use LibreOffice to recalculate:
# Recalculate and check for errors
python recalc.py output.xlsx
The script returns JSON:
{
"status": "success", // or "errors_found"
"total_errors": 0,
"total_formulas": 42,
"error_summary": {
"#REF!": {"count": 2, "locations": ["Sheet1!B5", "Sheet1!C10"]}
}
}
Formula Verification Checklist
Before Building
- Test 2-3 sample references first
- Confirm column mapping (column 64 = BL, not BK)
- Remember: DataFrame row 5 = Excel row 6 (1-indexed)
Common Pitfalls
- Check for NaN with
pd.notna()before using values - FY data often in columns 50+ (far right)
- Search ALL occurrences, not just first match
- Check denominators before division (#DIV/0!)
- Verify cross-sheet references use correct format (
Sheet1!A1)
After Building
- Run
recalc.pyand fix any errors - Verify #REF!, #DIV/0!, #VALUE!, #NAME? = 0
Common Errors
| Error | Cause | Fix |
|---|---|---|
| #REF! | Invalid cell reference | Check deleted rows/columns |
| #DIV/0! | Division by zero | Add IF check: =IF(B5=0,0,A5/B5) |
| #VALUE! | Wrong data type | Check cell contains expected type |
| #NAME? | Unknown function | Check spelling, quotes around text |
Verification
Run: python scripts/verify.py
Related Skills
building-nextjs-apps- Frontend for spreadsheet uploadsscaffolding-fastapi-dapr- API for spreadsheet processing
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/mjunaidca/mjs-agent-skills/working-with-spreadsheets">View working-with-spreadsheets on skillZs</a>