Individual skill
dataset-quality-audit
Run comprehensive quality checks on tabular data (CSV/Excel/TSV/JSON), detecting missing values, duplicates, outliers, format issues, and type inconsistencies to produce an overall score, grade, and actionable suggestions. Triggered when users ask to check data quality, find missing or duplicate values, detect outliers, validate formats, profile data, or clean data.
skills/dataset-quality-audit/SKILL.md
Source commit 3ae17b2c765ed8534ba9c6f848563db127fc4ca6
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- Last checked
- Nov 7, 2026
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- Repository last updated
- Nov 7, 2026
- License
- MIT
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- ai Repository topic
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- ai-agent-tools Repository topic
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# dataset-quality-audit
A data quality auditing tool that runs 12-dimension quality checks on tabular data, producing per-dimension scores (0–100), an overall grade, and actionable fix suggestions.
## Capabilities
| Dimension | Description |
|-----------|-------------|
| Missing Values | Count and percentage of null/NaN values per column |
| Duplicate Rows | Number and percentage of fully duplicated rows |
| Type Consistency | Mixed types within a single column (e.g., numbers mixed with text) |
| Value Range / Outliers | Outlier detection using the IQR method |
| Format Compliance | Consistency of date, email, phone number, and other formatted fields |
| Uniqueness Constraints | Whether ID-type columns contain duplicates |