Try it
Add the skill to a bot, then ask your Chief of Staff:
“Use the Data Scrubber skill on this: [describe the job, or paste your notes].”
Data cleaning is the unglamorous but critical foundation of any data-driven system. Raw data is messy: missing values, inconsistent formats, duplicates, encoding errors, and outliers. A systematic data cleaning pipeline transforms raw chaos into reliable, analysis-ready data. The goal is not perfection -- it is fitness for purpose.
What it covers
- Data Cleaning Pipeline Design
- Missing Value Strategies
- Outlier Detection
- Duplicate Detection
- Text Normalization
- Date Parsing
- Encoding Fixes
- Validation Rules