6k tokens
context cost
the whole folder, loaded on every use
7
files
ships runnable scripts
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copies elsewhere
how many repositories repackaged it
616
stars on the repo
on the repository, not the skill itself
Install
one command, takes just this skill from the repository
npx skills add https://github.com/lawve-ai/awesome-legal-skills --skill xlsx-processing-openai
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What comes with it
19 558 bytes besides the instruction
The instruction itself
16 sections, as written by the author
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
Confirm the file type and goals (create, edit, analyze, visualize).
Use openpyxl for .xlsx edits and pandas for analysis and CSV/TSV workflows.
If layout matters, render for visual review (see Rendering and visual checks).
Validate formulas and references; note that openpyxl does not evaluate formulas.
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.
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
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If uv is unavailable:
python3 -m pip install openpyxl pandas
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Optional (chart-heavy or PDF review workflows):
uv pip install matplotlib
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If uv is unavailable:
python3 -m pip install matplotlib
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System tools (for rendering):
# macOS (Homebrew)
brew install libreoffice poppler
# Ubuntu/Debian
sudo apt-get install -y libreoffice poppler-utils
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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 Codex examples (openpyxl): references/examples/openpyxl/
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$3) not =H6*1.04).
Guard against errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?) with validation and checks.
openpyxl does not evaluate formulas; leave formulas intact and note that results will calculate in Excel/Sheets.
Citation requirements
Cite sources inside the spreadsheet using plain text URLs.
For financial models, cite sources of inputs in cell comments.
For tabular data sourced from the web, include a Source column with URLs.
Render and inspect a provided spreadsheet before modifying it when possible.
Preserve existing formatting and style exactly.
Match styles for any newly filled cells that were previously blank.
Use appropriate number and date formats (dates as dates, currency with symbols, percentages with sensible precision).
Use a clean visual layout: headers distinct from data, consistent spacing, and readable column widths.
Avoid borders around every cell; use whitespace and selective borders to structure sections.
Ensure text does not spill into adjacent cells.
Color conventions (if no style guidance)
Blue: user input
Black: formulas/derived values
Green: linked/imported values
Gray: static constants
Orange: review/caution
Light red: error/flag
Purple: control/logic
Teal: visualization anchors (key KPIs or chart drivers)
Finance-specific requirements
Format zeros as "-".
Negative numbers should be red and in parentheses.
Always specify units in headers (e.g., "Revenue ($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.