spreadsheet
The spreadsheet skill handles creation, editing, and analysis of Excel and CSV files using formula-aware workflows. Use it when tasks require building workbooks with formulas and formatting, analyzing tabular data through filtering or aggregation, modifying existing spreadsheets while preserving references, or visualizing data with charts and styled tables, with support for formula recalculation and visual rendering before delivery.
git clone --depth 1 https://github.com/fcakyon/claude-codex-settings /tmp/spreadsheet && cp -r /tmp/spreadsheet/plugins/openai-office-skills/skills/spreadsheet ~/.claude/skills/spreadsheetSKILL.md
# 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, `Reven
Agent-browser usage guide. Read this before running any agent-browser commands. Covers the snapshot-and-ref workflow, navigating pages, interacting with elements (click, fill, type, select), extracting text and data, taking screenshots, managing tabs, handling forms and auth, waiting for content, running multiple browser sessions in parallel, and troubleshooting common failures. Use when the user asks to interact with a website, fill a form, click something, extract data, take a screenshot, log into a site, test a web app, or automate any browser task.
Automate Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify, etc.) using agent-browser via Chrome DevTools Protocol. Use when the user needs to interact with an Electron app, automate a desktop app, connect to a running app, control a native app, or test an Electron application. Triggers include "automate Slack app", "control VS Code", "interact with Discord app", "test this Electron app", "connect to desktop app", or any task requiring automation of a native Electron application.
Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.
Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.
Use this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates, layouts, speaker notes, or comments. Trigger whenever the user mentions \"deck,\" \"slides,\" \"presentation,\" or references a .pptx filename, regardless of what they plan to do with the content afterward. If a .pptx file needs to be opened, created, or touched, use this skill.
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
This skill should be used when user asks to "query Azure resources", "list storage accounts", "manage Key Vault secrets", "work with Cosmos DB", "check AKS clusters", "use Azure MCP", or interact with any Azure service.
This skill should be used when user encounters "Tavily MCP error", "Tavily API key invalid", "web search not working", "Tavily failed", or needs help configuring Tavily integration.