magic-data-cleaning

Natural Language Triggers

Activate this skill when the user says things like:

• "clean this data" / "fix the data quality issues"
• "handle the missing values" / "impute the nulls"
• "normalize the text columns" / "fix the encoding"
• "remove duplicates" / "deduplicate"
• "fix data quality" / "impute nulls" / "standardize text" / "fix encoding"

These produce the SAME behavior as the cleaning workflow.

When to Use

• Data has missing values, duplicates, type errors, or text issues
• Need to impute missing values or normalize strings
• Need complex multi-step cleaning with domain-specific rules
• After magic-data-profiling reveals quality issues

When NOT to Use: Use magic-data-validation for schema validation; use magic-data-transformation for reshaping; use magic-data-synthesis for LLM-based generation, translation, format conversion, or filling sentinel placeholders with meaningful content.