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.

Calculation Checks

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