Clean Data Xls

OrganizationPopular

anthropics

clean-data-xls

Clean up messy spreadsheet data — trim whitespace, fix inconsistent casing, convert numbers-stored-as-text, standardize dates, remove duplicates, and flag mixed-type columns. Use when data is messy, inconsistent, or needs prep before analysis. Triggers on "clean this data", "clean up this sheet", "normalize this data", "fix formatting", "dedupe", "standardize this column", "this data is messy".

Overview

Publisher	anthropics
Repository	`financial-services`
Skill name	`clean-data-xls`
Stars	38.4K
Forks	5.5K
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by anthropics on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/financial-analysis/skills/clean-data-xls
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/financial-analysis/skills/clean-data-xls

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/anthropics/financial-services.git /tmp/financial-services
mkdir -p .claude/skills
cp -r /tmp/financial-services/plugins/vertical-plugins/financial-analysis/skills/clean-data-xls .claude/skills/clean-data-xls

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Clean Data Xls 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 Clean Data Xls 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 Clean Data Xls 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.

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

Step 2: Detect issues

Issue	What to look for
Whitespace	leading/trailing spaces, double spaces
Casing	inconsistent casing in categorical columns (`usa` / `USA` / `Usa`)
Number-as-text	numeric values stored as text; stray `$`, `,`, `%` in number cells
Dates	mixed formats in the same column (`3/8/26`, `2026-03-08`, `March 8 2026`)
Duplicates	exact-duplicate rows and near-duplicates (case/whitespace differences)
Blanks	empty cells in otherwise-populated columns
Mixed types	a column that's 98% numbers but has 3 text entries
Encoding	mojibake (`Ã©`, `â€™`), non-printing characters
Errors	`#REF!`, `#N/A`, `#VALUE!`, `#DIV/0!`

Step 3: Propose fixes

Show a summary table before changing anything:

Column	Issue	Count	Proposed Fix

Step 4: Apply

Prefer formulas over hardcoded cleaned values — where the cleaned output can be expressed as a formula (e.g. =TRIM(A2), =VALUE(SUBSTITUTE(B2,"$","")), =UPPER(C2), =DATEVALUE(D2)), write the formula in an adjacent helper column rather than computing the result in Python and overwriting the original. This keeps the transformation transparent and auditable.
Only overwrite in place with computed values when the user explicitly asks for it, or when no sensible formula equivalent exists (e.g. encoding/mojibake repair)
For destructive operations (removing duplicates, filling blanks, overwriting originals), confirm with the user first
After each category of fix (whitespace → casing → number conversion → dates → dedup), show the user a sample of what changed and get confirmation before moving to the next category
Report a before/after summary of what changed

Frequently asked questions

What does the Clean Data Xls AI skill do?

Why use Clean Data Xls on TypingMind?

Because you install it once and use it with any model. Clean Data Xls 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 Clean Data Xls in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/financial-analysis/skills/clean-data-xls. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Clean Data Xls?

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 Clean Data Xls?

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

Is the Clean Data Xls AI skill free?

Yes. It is published on GitHub by anthropics under the Apache-2.0 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Clean Data

Environment

Workflow

Step 1: Scope

Step 2: Detect issues

Step 3: Propose fixes

Step 4: Apply

Frequently asked questions

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