data-validation
Installation
SKILL.md
Data Validation Skill
Pre-delivery QA checklist, common data analysis pitfalls, result sanity checking, and documentation standards for reproducibility.
Pre-Delivery QA Checklist
Run through this checklist before sharing any analysis with stakeholders.
Data Quality Checks
- Source verification: Confirmed which tables/data sources were used. Are they the right ones for this question?
- Freshness: Data is current enough for the analysis. Noted the "as of" date.
- Completeness: No unexpected gaps in time series or missing segments.
- Null handling: Checked null rates in key columns. Nulls are handled appropriately (excluded, imputed, or flagged).
- Deduplication: Confirmed no double-counting from bad joins or duplicate source records.
- Filter verification: All WHERE clauses and filters are correct. No unintended exclusions.