Clean Data Xls

anthropics/financial-services-pluginsOfficial

Does the boring but critical work of cleaning spreadsheet data before analysis. Profiles each column to detect whitespace, inconsistent casing, numbers stored as text, mixed date formats, duplicates, and type mismatches. The workflow is thoughtful: it scopes the range, shows you a summary table of issues found, proposes fixes, then applies them incrementally with confirmation at each step. Smart default is to use formulas like TRIM() and VALUE() in helper columns rather than overwriting your originals, which keeps the transformation auditable. Handles both Excel via Office JS and standalone files through Python. Most data cleaning skills just blast through your sheet; this one actually asks permission before destructive operations.

skills.sh installs: 972
GitHub stars: 33.5K
last updated: Jul 14, 2026

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Install

$ npx -y skills add anthropics/financial-services-plugins --skill clean-data-xls --agent claude-code

Installs into .claude/skills of the current project.

Files

Clean Data

Clean messy data in the active sheet or a specified range.

Environment

If running inside Excel (Office Add-in / Office JS): Use Office JS directly (Excel.run(async (context) => {...})). Read via range.values, write helper-column formulas via range.formulas = [["=TRIM(A2)"]]. The in-place vs helper-column decision still applies.
If operating on a standalone .xlsx file: Use Python/openpyxl.

Workflow

Step 1: Scope

If a range is given (e.g. A1:F200), use it
Otherwise use the full used range of the active sheet
Profile each column: detect its dominant type (text / number / date) and identify outliers