xlsx - SKILL.md Agent Skill

name: xlsx description: "Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file; create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Also trigger for cleaning or restructuring messy tabular data. The deliverable must be a spreadsheet file." dependencies: commands: - python3 tools: - skillScriptTool - skillFileTool platforms:

macos
linux
windows

Important: All scripts/ paths are relative to this skill directory. Use run_skill_script tool to execute scripts, or run with: cd {this_skill_dir} && python scripts/...

Requirements for Outputs

All Excel files

Professional Font

Use a consistent, professional font (e.g., Arial, Times New Roman) unless otherwise instructed

Zero Formula Errors

Every Excel model MUST be delivered with ZERO formula errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?)

Preserve Existing Templates

Study and EXACTLY match existing format, style, and conventions when modifying files
Existing template conventions ALWAYS override these guidelines

Financial Models

Color Coding Standards

Blue text (0,0,255): Hardcoded inputs
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

Number Formatting Standards

Years: Format as text strings ("2024" not "2,024")
Currency: Use $#,##0 format; specify units in headers ("Revenue ($mm)")
Zeros: Format as "-" including percentages
Percentages: Default to 0.0% format
Multiples: Format as 0.0x
Negative numbers: Use parentheses (123) not minus -123

Formula Construction Rules

Place ALL assumptions in separate assumption cells
Use cell references instead of hardcoded values
Example: Use =B5*(1+$B$6) instead of =B5*1.05

XLSX creation, editing, and analysis

Prerequisites

openpyxl: Excel file creation and editing
pandas: data analysis and bulk operations
LibreOffice (soffice): formula recalculation via scripts/recalc.py

CRITICAL: Use Formulas, Not Hardcoded Values

Always use Excel formulas instead of calculating values in Python and hardcoding them.

WRONG - Hardcoding

total = df['Sales'].sum()
sheet['B10'] = total  # Bad: hardcodes 5000

CORRECT - Using Formulas

sheet['B10'] = '=SUM(B2:B9)'

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):
```
python scripts/recalc.py output.xlsx
```
Verify and fix any errors:
- If status is errors_found, check error_summary for specific errors
- Fix the identified errors and recalculate again

Reading and Analyzing Data

Data analysis with pandas

import pandas as pd

df = pd.read_excel('file.xlsx')                          # Default: first sheet
all_sheets = pd.read_excel('file.xlsx', sheet_name=None) # All sheets as dict

df.head()      # Preview data
df.info()      # Column info
df.describe()  # Statistics

df.to_excel('output.xlsx', index=False)

Excel File Workflows

Creating new Excel files

from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill, Alignment

wb = Workbook()
sheet = wb.active

sheet['A1'] = 'Hello'
sheet['B1'] = 'World'
sheet.append(['Row', 'of', 'data'])

sheet['B2'] = '=SUM(A1:A10)'

sheet['A1'].font = Font(bold=True, color='FF0000')
sheet['A1'].fill = PatternFill('solid', start_color='FFFF00')
sheet['A1'].alignment = Alignment(horizontal='center')

sheet.column_dimensions['A'].width = 20

wb.save('output.xlsx')

Editing existing Excel files

from openpyxl import load_workbook

wb = load_workbook('existing.xlsx')
sheet = wb.active

sheet['A1'] = 'New Value'
sheet.insert_rows(2)
sheet.delete_cols(3)

new_sheet = wb.create_sheet('NewSheet')
new_sheet['A1'] = 'Data'

wb.save('modified.xlsx')

Unpack/Pack Workflow (Advanced XML editing)

For advanced Excel manipulation via raw XML:

# Unpack
python scripts/office/unpack.py spreadsheet.xlsx unpacked/

# Edit XML in unpacked/xl/worksheets/, unpacked/xl/sharedStrings.xml, etc.

# Pack
python scripts/office/pack.py unpacked/ output.xlsx

Recalculating Formulas

python scripts/recalc.py <excel_file> [timeout_seconds]

The script:

Automatically sets up LibreOffice macro on first run
Recalculates all formulas in all sheets
Scans ALL cells for Excel errors
Returns JSON with detailed error locations and counts
Works on Linux, macOS, and Windows

Interpreting recalc.py Output

{
  "status": "success",
  "total_errors": 0,
  "total_formulas": 42,
  "error_summary": {}
}

Formula Verification Checklist

Essential Verification

Test 2-3 sample references before building full model
Confirm Excel column mapping (column 64 = BL, not BK)
Remember Excel rows are 1-indexed (DataFrame row 5 = Excel row 6)

Common Pitfalls

NaN handling: Check for null values with pd.notna()
Division by zero: Check denominators before / in formulas
Wrong references: Verify all cell references point to intended cells
Cross-sheet references: Use correct format (Sheet1!A1)

Best Practices

Library Selection

pandas: Best for data analysis, bulk operations, and simple data export
openpyxl: Best for complex formatting, formulas, and Excel-specific features

Working with openpyxl

Cell indices are 1-based
Use data_only=True to read calculated values
Warning: data_only=True + save = formulas permanently lost
Formulas are preserved but not evaluated - use scripts/recalc.py to update values