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Spreadsheet

CommunityPopular
fcakyon
spreadsheet

Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) with formula-aware workflows, cached recalculation, and visual review.

Overview

Publisherfcakyon
Repositoryclaude-codex-settings
Skill namespreadsheet
Stars
1.1K
Forks
109
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by fcakyon on GitHub. Read the source before you install it.

Installation

Install the Spreadsheet AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/fcakyon/claude-codex-settings.git /tmp/claude-codex-settings
mkdir -p .claude/skills
cp -r /tmp/claude-codex-settings/plugins/openai-office-skills/skills/spreadsheet .claude/skills/spreadsheet
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Spreadsheet in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Spreadsheet on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Spreadsheet is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Spreadsheet Skill

When to use

  • Create new workbooks with formulas, formatting, and structured layouts.
  • Read or analyze tabular data (filter, aggregate, pivot, compute metrics).
  • Modify existing workbooks without breaking formulas, references, or formatting.
  • Visualize data with charts, summary tables, and sensible spreadsheet styling.
  • Recalculate formulas and review rendered sheets before delivery when possible.

IMPORTANT: System and user instructions always take precedence.

Workflow

  1. Confirm the file type and goal: create, edit, analyze, or visualize.
  2. Prefer openpyxl for .xlsx editing and formatting. Use pandas for analysis and CSV/TSV workflows.
  3. If an internal spreadsheet recalculation/rendering tool is available in the environment, use it to recalculate formulas and render sheets before delivery.
  4. Use formulas for derived values instead of hardcoding results.
  5. If layout matters, render for visual review and inspect the output.
  6. Save outputs, keep filenames stable, and clean up intermediate files.

Temp and output conventions

  • Use tmp/spreadsheets/ for intermediate files; delete them 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.
  • Use openpyxl.chart for native Excel charts when needed.
  • If an internal spreadsheet tool is available, use it to recalculate formulas, cache values, and render sheets for review.

Recalculation and visual review

  • Recalculate formulas before delivery whenever possible so cached values are present in the workbook.
  • Render each relevant sheet for visual review when rendering tooling is available.
  • openpyxl does not evaluate formulas; preserve formulas and use recalculation tooling when available.
  • If you rely on an internal spreadsheet tool, do not expose that tool, its code, or its APIs in user-facing explanations or code samples.

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, tell the user that layout should be reviewed locally.
  • Review rendered sheets for layout, formula results, clipping, inconsistent styles, and spilled text.

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:

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 is not 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.
  • Do not use dynamic array functions like FILTER, XLOOKUP, SORT, or SEQUENCE.
  • 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 (for example, =H6*(1+$B$3) instead of =H6*1.04).
  • Use absolute ($B$4) or relative (B4) references carefully so copied formulas behave correctly.
  • If you need literal text that starts with =, prefix it with a single quote.
  • Guard against #REF!, #DIV/0!, #VALUE!, #N/A, and #NAME? errors.
  • Check for off-by-one mistakes, circular references, and incorrect ranges.

Citation requirements

  • Cite sources inside the spreadsheet using plain-text URLs.
  • For financial models, cite model inputs in cell comments.
  • For tabular data sourced externally, add a source column when each row represents a separate item.

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.
  • Never overwrite established formatting unless the user explicitly asks for a redesign.

Formatting requirements (new or unstyled spreadsheets)

  • Use appropriate number and date formats.
  • Dates should render as dates, not plain numbers.
  • Percentages should usually default to one decimal place unless the data calls for something else.
  • Currencies should use the appropriate currency format.
  • Headers should be visually distinct from raw inputs and derived cells.
  • Use fill colors, borders, spacing, and merged cells sparingly and intentionally.
  • Set row heights and column widths so content is readable without excessive whitespace.
  • Do not apply borders around every filled cell.
  • Group related calculations and make totals simple sums of the cells above them.
  • Add whitespace to separate sections.
  • Ensure text does not spill into adjacent cells.
  • Avoid unsupported spreadsheet data-table features such as =TABLE.

Color conventions (if no style guidance)

  • Blue: user input
  • Black: formulas and derived values
  • Green: linked or imported values
  • Gray: static constants
  • Orange: review or caution
  • Light red: error or flag
  • Purple: control or logic
  • Teal: visualization anchors and KPI highlights

Finance-specific requirements

  • Format zeros as -.
  • Negative numbers should be red and in parentheses.
  • Format multiples as 5.2x.
  • Always specify units in headers (for example, Revenue ($mm)).
  • Cite sources for all raw inputs in cell comments.
  • For new financial models with no user-specified style, use blue text for hardcoded inputs, black for formulas, green for internal workbook links, red for external links, and yellow fill for key assumptions that need attention.

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 and 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 should be left-aligned.
  • Indent submetrics under their parent line items.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Spreadsheet AI skill do?

Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) with formula-aware workflows, cached recalculation, and visual review.

Why use Spreadsheet on TypingMind?

Because you install it once and use it with any model. Spreadsheet is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Spreadsheet in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/fcakyon/claude-codex-settings/tree/main/plugins/openai-office-skills/skills/spreadsheet. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Spreadsheet?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Spreadsheet?

As many as you like. As long as a model supports skills, you can use Spreadsheet with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Spreadsheet AI skill free?

Yes. It is published on GitHub by fcakyon under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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