Skip to content
cccskills
FreePublished on GitHub

spreadsheet

Create, edit, analyze, and format Excel, CSV, and TSV files using Python. Preserves existing spreadsheet styles and formulas, checks references, and supports summaries, charts, and readable layouts for new workbooks.

OriginalShow the original 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.

Works withExcel

Run score Not tested

See how to install

Good for

  • Editing Excel files while preserving formulas and formatting
  • Filtering and summarizing CSV or TSV data
  • Creating workbooks with formulas
  • Presenting data with charts and readable tables

Files included (9)

  • SKILL.md5.0 KB
  • agents/openai.yaml349 B
  • assets/spreadsheet-small.svg1.4 KB
  • assets/spreadsheet.png3.0 KB
  • LICENSE.txt10.5 KB
  • references/examples/openpyxl/create_basic_spreadsheet.py1.4 KB
  • references/examples/openpyxl/create_spreadsheet_with_styling.py3.1 KB
  • references/examples/openpyxl/read_existing_spreadsheet.py1.6 KB
  • references/examples/openpyxl/styling_spreadsheet.py2.0 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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 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 =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.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

adaptyv

FreeSummary

Support experimental validation of designed proteins through a cloud laboratory. Prepare and optimize sequences, submit tests for binding, expression, thermal stability, or enzyme activity, track experiment progress, and retrieve results through the API.

  • Submit designed proteins for binding tests
  • Request expression, thermal stability, or enzyme activity tests
  • Optimize sequences for solubility before experiments
foryourhealth111-pixel/Vibe-Skills3.8KUpdated Oct 23, 2026

aeon

FreeSummary

Analyze time series, observations ordered over time, using aeon in Python. Build classification, prediction, and clustering workflows, detect unusual patterns or changes, and compare methods through an interface compatible with scikit-learn.

  • Classifying time series by their patterns
  • Forecasting future values from past observations
  • Detecting anomalies and change points
foryourhealth111-pixel/Vibe-Skills3.8KUpdated Oct 23, 2026

algorithmic-art

FreeSummary

Create original generative art with p5.js, using code to produce patterns and motion. Receive a written artistic concept and an interactive HTML viewer with adjustable parameters, reproducible random variations, seed navigation, and PNG downloads.

  • Create art from particle motion and flow fields
  • Explore patterns by adjusting sliders
  • Reproduce a favorite variation with the same seed
foryourhealth111-pixel/Vibe-Skills3.8KUpdated Oct 23, 2026

alpha-vantage

FreeSummary

Retrieve stock prices, exchange rates, cryptocurrency prices, company financial statements, and economic indicators through the Alpha Vantage API. It also covers historical data, news sentiment, and technical indicators, which summarize price and trading patterns.

  • Retrieve historical stock prices and trading volumes
  • Collect company financial statements and earnings data
  • Check foreign exchange and cryptocurrency prices
foryourhealth111-pixel/Vibe-Skills3.8KUpdated Oct 23, 2026

Design backend systems with clear boundaries between business rules, databases, and external services. Use Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to organize new applications, refactor existing code, and make core logic easier to test.

  • Planning the structure of a new backend
  • Refactoring tightly coupled applications
  • Testing business rules independently of external services
foryourhealth111-pixel/Vibe-Skills3.8KUpdated Oct 23, 2026

astropy

FreeSummary

Helps process astronomical data in Python by converting coordinates, units, and time scales, working with FITS observation files, matching object catalogs, and calculating distances using cosmological models.

  • Converting celestial coordinates
  • Reading and editing FITS observation files
  • Matching objects across astronomical catalogs
foryourhealth111-pixel/Vibe-Skills3.8KUpdated Oct 23, 2026

See all skills by foryourhealth111-pixel

Report a problem with this skill