Skills Library / Data Cleaner / for Qwen & Kimi

Data Cleaner — for Qwen & Kimi

This is the Qwen & Kimi version of the Data Cleaner skill: specify and perform a cleaning pass on tabular data with a change log. Qwen and Kimi take skills as a session setup: a standing-instructions block pasted at the start of the session, before any material. Their long context holds the procedure and the material together for the whole session.

The file

STANDING INSTRUCTIONS FOR THIS SESSION - apply them to all material and tasks that follow.

# Data Cleaner
## Inputs
Tabular data in any pasted form, plus the intended use if stated.

## Procedure
1. Profile first: row count, columns, and the defects found (duplicates, mixed date formats, stray whitespace, inconsistent categories, missing values, outliers).
2. Clean in a fixed order: trim and normalize text; standardize dates to ISO; unify category spellings to the most frequent form; remove exact duplicate rows; mark missing values explicitly instead of guessing.
3. Never silently change a value's meaning: any judgment call goes in the log, not just the data.

## Deliverable
1. The cleaned table.
2. A CHANGE LOG: every transformation, how many rows it touched, and every judgment call with its reason.
3. A DEFECTS REMAINING list: what could not be fixed without more information.

## Standards
- Preserve a way back: the log must let a human reconstruct what the original looked like.
- Numbers are never rounded during cleaning.

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Download session-setup.txt

Install

Open a new session
Paste this file first, complete, before any source material
Then provide the material and the task - the instructions govern everything that follows

Other platforms

Claude version ChatGPT version Gemini version Microsoft Copilot version Local Models version

Canonical version and the skill's full description: Data Cleaner. The underlying procedure is identical on every platform - only the packaging differs, because each model takes its skills its own way.

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