/openai-spreadsheet

name: openai-spreadsheet
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. Originally from OpenAI's curated skills catalog.
allowed-tools:
- Bash
- Read
- Grep
- Glob
- Write
- Edit

Spreadsheet Skill (Create, Edit, Analyze, Visualize)

When to use

• Build new workbooks with formulas, formatting, and structured layouts.
• Read or analyze tabular data (filter, aggregate, pivot, compute metrics).
• Modify existing workbooks without breaking formulas or references.
• Visualize data with charts/tables and sensible formatting.

IMPORTANT: System and user instructions always take precedence.

Workflow

1. Confirm the file type and goals (create, edit, analyze, visualize). 2. Use `openpyxl` for `.xlsx` edits and `pandas` for analysis and CSV/TSV workflows. 3. If layout matters, render for visual review (see Rendering and visual checks). 4. Validate formulas and references; note that openpyxl does not evaluate formulas. 5. Save outputs and clean up intermediate files.

Temp and output conventions

• Use `tmp/spreadsheets/` for intermediate files; delete when done.
• Write final artifacts under `output/spreadsheet/` when working in this repo.
• Keep filenames stable and descriptive.

Primary tooling

• Use `openpyxl` for creating/editing `.xlsx` files and preserving formatting.
• Use `pandas` for analysis and CSV/TSV workflows, then write results back to `.xlsx` or `.csv`.
• If you need charts, prefer `openpyxl.chart` for native Excel charts.

Rendering and visual checks

• If LibreOffice (`soffice`) and Poppler (`pdftoppm`) are available, render sheets for visual review:
• `soffice --headless --convert-to pdf --outdir $OUTDIR $INPUT_XLSX`
• `pdftoppm -png $OUTDIR/$BASENAME.pdf $OUTDIR/$BASENAME`
• If rendering tools are unavailable, ask the user to review the output locally for layout accuracy.

Dependencies (install if missing)

Prefer `uv` for dependency management.

Python packages:

uv pip install openpyxl pandas

If `uv` is unavailable:

python3 -m pip install openpyxl pandas

Optional (chart-heavy or PDF review workflows):

uv pip install matplotlib

If `uv` is unavailable:

python3 -m pip install matplotlib

System tools (for rendering):

# macOS (Homebrew)
brew install libreoffice poppler

# Ubuntu/Debian
sudo apt-get install -y libreoffice poppler-utils

If installation isn't possible in this environment, tell the user which dependency is missing and how to install it locally.

Environment

No required environment variables.

Examples

• Runnable the agent 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 `=H6*1.04`).
• 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.

Formatting requirements (new or unstyled spreadsheets)

• Use appropriate number and date formats (dates as dates, currency with symbols, percentages with sensible precision).
• Use a clean visual layout: headers distinct from data, consistent spacing, and readable column widths.
• Avoid borders around every cell; use whitespace and selective borders to structure sections.
• Ensure text does not spill into adjacent cells.

Color conventions (if no style guidance)

• Blue: user input
• Black: formulas/derived values
• Green: linked/imported values
• Gray: static constants
• Orange: review/caution
• Light red: error/flag
• Purple: control/logic
• Teal: visualization anchors (key KPIs or chart drivers)

Finance-specific requirements

• Format zeros as "-".
• Negative numbers should be red and in parentheses.
• Always specify units in headers (e.g., "Revenue ($mm)").
• Cite sources for all raw inputs in cell comments.

Investment banking layouts

If the spreadsheet is an IB-style model (LBO, DCF, 3-statement, valuation):

• Totals should sum the range directly above.
• Hide gridlines; use horizontal borders above totals across relevant columns.
• Section headers should be merged cells with dark fill and white text.
• Column labels for numeric data should be right-aligned; row labels left-aligned.
• Indent submetrics under their parent line items.

When NOT to Use

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