AI SummaryThis booster helps developers efficiently create, edit, and analyze spreadsheets in Python using openpyxl and pandas while preserving formulas and formatting. It's ideal for anyone automating spreadsheet workflows or performing data analysis tasks programmatically.
Install
# Add to your project root as SKILL.md curl -o SKILL.md "https://raw.githubusercontent.com/openai/skills/main/skills/.curated/spreadsheet/SKILL.md"
Description
Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified.
Examples
• Runnable Codex examples (openpyxl): references/examples/openpyxl/
Formula requirements
• Use formulas for derived values rather than hardcoding results. • Keep formulas simple and legible; use helper cells for complex logic. • Avoid volatile functions like INDIRECT and OFFSET unless required. • Prefer cell references over magic numbers (e.g., =H6(1+$B$3) not =H61.04). • Guard against errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?) with validation and checks. • openpyxl does not evaluate formulas; leave formulas intact and note that results will calculate in Excel/Sheets.
Citation requirements
• Cite sources inside the spreadsheet using plain text URLs. • For financial models, cite sources of inputs in cell comments. • For tabular data sourced from the web, include a Source column with URLs.
Formatting requirements (existing formatted spreadsheets)
• Render and inspect a provided spreadsheet before modifying it when possible. • Preserve existing formatting and style exactly. • Match styles for any newly filled cells that were previously blank.
Quality Score
Good
85/100
Trust & Transparency
No License Detected
Review source code before installing
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Actively Maintained
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