/xlsx

name: xlsx
description: "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, .xltx, .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."
license: Complete terms in LICENSE.txt

XLSX creation, editing, and analysis

| Task | Approach | |---|---| | **Create** or **edit** with formulas/formatting | `openpyxl` — see gotchas below | | **Bulk data** in or out | `pandas` (`read_excel`, `to_excel`) | | **Quick look** at a sheet | `markitdown file.xlsx` — `## SheetName` per sheet; reads `.xlsm` too. No cell coordinates, so don't plan edits from it | | **Read** a model (formulas *and* values) | two `load_workbook` passes — see gotchas |

> `openpyxl`, `pandas`, and `markitdown` are preinstalled — do not run `uv pip install` first; write the script and import directly. Only if an import fails (or the `markitdown` command is missing): `uv pip install` the missing package.

> Script paths below are relative to this skill's directory.

Requirements for every output

• **Professional font** (Arial, Times New Roman) throughout, unless the user says otherwise.
• **Zero formula errors.** Never ship while `recalc.py` reports `errors_found`. If you think an error predates you, prove it: load the *original* with `data_only=True` and look at that cell. An error you introduced looks exactly like one you inherited.
• **Use formulas, never hardcoded results.** Write `sheet['B10'] = '=SUM(B2:B9)'`, not the Python-computed total. The sheet must recalculate when its inputs change.
• **Follow the user's spec literally.** Exact tab names, exact column headers, and the formula they spelled out. A redesign that computes something else fails, however elegant.
• **Document every assumption and hardcoded number** where the reader will see it — a cell comment, or an adjacent cell at a table's end. Cite a real source when one exists (`Source: Company 10-K, FY2024, Page 45, Revenue Note, [SEC EDGAR URL]`); when the number came from the user, say so plainly.
• **A workbook *you create* for someone to fill in** needs a short legend naming which cells to edit, and one example row of realistic values showing the expected format. Never add such a row to a file you were asked to edit.
• **Editing an existing file: match its conventions exactly.** They override every guideline here. Find its designated input cells first — a distinct font color, fill, or shading marks them — write only there, and leave every existing formula untouched.

Recalculate (mandatory whenever the file contains formulas)

openpyxl writes formulas as strings with **no cached values**. Until you recalculate, every formula cell reads back as `None` to anything reading cached values — `pandas`, `load_workbook(data_only=True)`, and most previewers.

python scripts/recalc.py output.xlsx [timeout_seconds]   # default 30

LibreOffice computes every formula, the file is **rewritten in place**, and you get JSON: `status` (`success` | `errors_found`), `total_formulas`, `total_errors`, and an `error_summary` naming up to 100 cells per error type (`locations_truncated` says how many it withheld — trust `total_errors`, not the length of the list). Fix what it names and run it again. **JSON with an `error` key instead of a `status` means nothing was recalculated**, and only that case exits non-zero — `errors_found` exits 0, so never treat a clean exit as a clean workbook.

**A green recalc proves your formulas *evaluate*, not that they are *right*.** An off-by-one range or a reference to the wrong row yields a clean, error-free file with wrong numbers. Write 2–3 formulas first and check they pull the values you expect, before building out a grid.

**A workbook that links to another file loses those links** if you re-save it with openpyxl and then recalculate. Such a formula reads `='[1]Returns Analysis'!$B$2` — the `[1]` is an index into the workbook's external-reference list, naming a *separate file on disk*, not a sheet. That file is rarely present here, so the cell's cached value is the only thing holding its data. openpyxl strips that value on save; LibreOffice then has to resolve the reference for real, fails, writes `#NAME?`, and deletes every link. `recalc.py` refuses to run in that state — copy those cells' values out of the original before you save over them (`--force` overrides, and accepts the loss).

Choosing formulas that survive verification

LibreOffice implements fewer functions than Excel, and one it cannot evaluate becomes a literal `#NAME?` baked into the file you deliver.

• **Prefer Excel-2007-era functions** — `SUMIFS`, `INDEX`, `MATCH`, `IFERROR`, `SUMPRODUCT` — which need no prefix.
• **Six post-2007 functions work, but only with an `_xlfn.` prefix**, because openpyxl writes your formula into the XML verbatim and Excel stores post-2007 names prefixed (its UI hides the prefix): `_xlfn.TEXTJOIN`, `_xlfn.CONCAT`, `_xlfn.IFS`, `_xlfn.SWITCH`, `_xlfn.MAXIFS`, `_xlfn.MINIFS`. Written bare, each yields `#NAME?`.
• **Never use `XLOOKUP`, `XMATCH`, `SORT`, `FILTER`, `UNIQUE`, or `SEQUENCE`.** The runtime's LibreOffice cannot evaluate them under *any* prefix. Newer builds do evaluate them, but they are sp