How do I install the XLSX skill?

Run npx skillmds@latest add majiayu000/xlsx-6 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Which AI agents work with XLSX?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

XLSX by majiayu000 — Agent Skill

Name: XLSX
Rating: 4.2 (5 reviews)
Author: majiayu000

XLSX

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) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

majiayu000 Updated Sep 9, 2026 567 repo stars

File contents

XLSX Spreadsheet Processing

Requirements for Outputs

All Excel Files

Zero Formula Errors: Every file must have ZERO formula errors (#REF!, #DIV/0!, etc.)
Preserve Existing Templates: Match existing format when modifying files

Financial Models

Color Coding:

Blue text: Hardcoded inputs
Black text: Formulas and calculations
Green text: Links from other worksheets
Red text: External file links
Yellow background: Key assumptions

Number Formatting:

Years: Text strings ("2024" not "2,024")
Currency: $#,##0 with units in headers
Zeros: Format as "-"
Percentages: 0.0% format
Negatives: Use parentheses (123)

Reading and Analyzing

import pandas as pd

# Read Excel
df = pd.read_excel('file.xlsx')
all_sheets = pd.read_excel('file.xlsx', sheet_name=None)

# Analyze
df.head()
df.info()
df.describe()

Creating/Editing with openpyxl

from openpyxl import Workbook, load_workbook

# Create new
wb = Workbook()
sheet = wb.active
sheet['A1'] = 'Hello'
sheet['B2'] = '=SUM(A1:A10)'  # Use formulas!
wb.save('output.xlsx')

# Edit existing
wb = load_workbook('existing.xlsx')
sheet = wb.active
sheet['A1'] = 'New Value'
wb.save('modified.xlsx')

CRITICAL: Use Formulas

Wrong: Calculate in Python, hardcode result

total = df['Sales'].sum()
sheet['B10'] = total  # BAD!

Correct: Use Excel formulas

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

Recalculating Formulas

python recalc.py <excel_file> [timeout_seconds]

The script:

Sets up LibreOffice macro on first run
Recalculates all formulas
Scans for errors
Returns JSON with error details

Library Selection

pandas: Data analysis, bulk operations, simple export
openpyxl: Complex formatting, formulas, Excel features

---name: xlsx-6description: 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) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas--- # XLSX Spreadsheet Processing ## Requirements for Outputs ### All Excel Files - **Zero Formula Errors**: Every file must have ZERO formula errors (#REF!, #DIV/0!, etc.) - **Preserve Existing Templates**: Match existing format when modifying files ### Financial Models **Color Coding:** - Blue text: Hardcoded inputs - Black text: Formulas and calculations - Green text: Links from other worksheets - Red text: External file links - Yellow background: Key assumptions **Number Formatting:** - Years: Text strings ("2024" not "2,024") - Currency: $#,##0 with units in headers - Zeros: Format as "-" - Percentages: 0.0% format - Negatives: Use parentheses (123) ## Reading and Analyzing ```python import pandas as pd # Read Excel df = pd.read_excel('file.xlsx') all_sheets = pd.read_excel('file.xlsx', sheet_name=None) # Analyze df.head() df.info() df.describe() ``` ## Creating/Editing with openpyxl ```python from openpyxl import Workbook, load_workbook # Create new wb = Workbook() sheet = wb.active sheet['A1'] = 'Hello' sheet['B2'] = '=SUM(A1:A10)' # Use formulas! wb.save('output.xlsx') # Edit existing wb = load_workbook('existing.xlsx') sheet = wb.active sheet['A1'] = 'New Value' wb.save('modified.xlsx') ``` ## CRITICAL: Use Formulas **Wrong:** Calculate in Python, hardcode result ```python total = df['Sales'].sum() sheet['B10'] = total # BAD! ``` **Correct:** Use Excel formulas ```python sheet['B10'] = '=SUM(B2:B9)' # GOOD! ``` ## Recalculating Formulas ```bash python recalc.py <excel_file> [timeout_seconds] ``` The script: - Sets up LibreOffice macro on first run - Recalculates all formulas - Scans for errors - Returns JSON with error details ## Library Selection - **pandas**: Data analysis, bulk operations, simple export - **openpyxl**: Complex formatting, formulas, Excel features

Frequently asked questions