# XLSX

> XLSX creation, editing, and analysis

- Skill: `ranbot-ai/xlsx` (Agent Skill)
- Install (CLI): `npx skillmds@latest add ranbot-ai/xlsx`
- Raw SKILL.md: https://api.skillmd.com/api/skills/ranbot-ai/xlsx/raw
- Safety review: PASS (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: ranbot-ai (https://skillmd.com/u/ranbot-ai)
- Updated: 2026-08-19
- Page: https://skillmd.com/skills/ranbot-ai/xlsx

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# 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 `pip install` first; write the script and import directly. Only if an import fails (or the `markitdown` command is missing): `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.

```bash
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 spilling array functions and an