xlsx
Create and analyze Excel spreadsheets
Also available from: K-Dense-AI,ArtemisAI,davila7,Azeem-2,AutumnsGrove,anthropics,Cam10001110101,DYAI2025,ComposioHQ
This skill enables Claude Code to create, edit, and analyze Excel spreadsheets with formulas, formatting, and data visualization. It solves the problem of manual spreadsheet manipulation by automating complex spreadsheet operations.
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Using "xlsx". Create a quarterly sales report with charts
Expected outcome:
- Created Q1_sales_report.xlsx with 3 sheets: Summary, Details, Charts
- Added conditional formatting to highlight top performers
- Generated bar chart showing sales by product category
- Recalculated all formulas - 0 errors found
Using "xlsx". Build a DCF valuation model
Expected outcome:
- Created dcf_model.xlsx with Assumptions, Revenue, FCF, and Valuation sheets
- Applied color coding: blue for inputs, black for formulas, green for cross-sheet refs
- Built 5-year projection with NPV and IRR calculations
- All formulas validated - model ready for sensitivity analysis
Security Audit
SafeAll 57 static findings are false positives. The skill uses subprocess to run LibreOffice for formula recalculation, which is legitimate spreadsheet automation. The filesystem operations access standard config directories. The SKILL.md contains code examples and Excel references (cell names like C2, error types like #REF!) that were incorrectly flagged.
Detected Patterns
Quality Score
What You Can Build
Financial model creation
Build complete financial models with assumptions, projections, and formatted output following industry standards
Data reporting automation
Automate data export and reporting workflows by generating formatted Excel reports from raw data
Spreadsheet error correction
Identify and fix formula errors like #REF!, #DIV/0!, and #VALUE! in existing spreadsheets
Try These Prompts
Create a new Excel file called sales_report.xlsx with columns for Date, Product, Quantity, and Price. Add 5 sample rows of data.
Create a financial model for a SaaS company with assumptions sheet, revenue projections for 5 years, and formatted output. Use blue for inputs, black for formulas.
Read the data from data.xlsx, analyze the trends, and create a summary sheet with key statistics and charts.
Open workbook.xlsx, recalculate all formulas, identify any errors, and fix the #REF! and #DIV/0! errors found.
Best Practices
- Always use Excel formulas instead of hardcoded values to keep spreadsheets dynamic
- Run recalc.py after creating or modifying files with formulas to verify no errors
- Follow financial model color standards: blue for inputs, black for formulas, green for sheet links
Avoid
- Calculating values in Python and hardcoding them instead of using Excel formulas
- Saving files without running recalc.py, leaving formulas uncalculated
- Using data_only=True when loading files that need formula preservation