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yethikrishna
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validation

Validate data analyses and generate a pre-delivery QA checklist with reproducibility documentation.

Updated Apr 16, 2026
Search Tags:#documentation#reproducibility#joins#data-quality#data-validation#qa-checklist#sanity-checks
One-click install
npx skills add https://github.com/yethikrishna/humble --skill validation-yethikrishna
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: validation
Source: https://github.com/yethikrishna/humble/tree/main/core/kortix-master/opencode/skills/GENERAL-KNOWLEDGE-WORKER/validation
Command: npx skills add https://github.com/yethikrishna/humble --skill validation-yethikrishna

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Ensures analyses are correct, reproducible, and free of common data pitfalls before being shared with stakeholders by providing a practical pre-delivery QA checklist and documentation templates.

Core Features & Use Cases

  • Pre-delivery QA checklist: Step-by-step checks for source verification, freshness, completeness, null handling, deduplication, and filter verification.
  • Calculation & reasonableness checks: Guidance on aggregation logic, denominator correctness, join verification, timezone alignment, and magnitude sanity tests.
  • Result sanity and cross-validation: Techniques to cross-check metrics, reverse-engineer totals, spot-check records, and detect red flags.
  • Reproducibility templates: Analysis documentation and code docstring examples to ensure others can recreate results.
  • Use Case: Validate a weekly revenue analysis to confirm joins didn't inflate counts, denominators are correct, and findings are reproducible with attached SQL and methodology notes.

Quick Start

Run the pre-delivery QA checklist on my latest analysis and produce a validation report listing detected issues, their likely causes, and recommended corrective actions.

Frequently Asked Questions about validation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create a pre-delivery QA checklist for data analysis?▼

Data validation checks confirm aggregation logic, denominator correctness, join verification, and timezone alignment. These sanity tests detect inflated counts and ensure calculation accuracy before delivering analytics outputs to stakeholders.

How do I ensure reproducibility in SQL data analysis documentation?▼

Cross-validation techniques spot-check records, reverse-engineer totals, and detect red flags in metric calculations. These sanity checks cross-verify aggregated results against source data to confirm analysis correctness.

What data validation checks are needed for join and aggregation logic?▼

Data validation checks confirm aggregation logic, denominator correctness, join verification, and timezone alignment. These sanity tests detect inflated counts and ensure calculation accuracy before delivering analytics outputs to stakeholders.

How do I document SQL analysis for reproducibility?▼

Reproducibility documentation templates provide code docstring examples and methodology notes for SQL analyses. They ensure others can recreate results by attaching query logic and validation steps to reproducible outputs.

Can I use a QA checklist to verify timezone consistency and deduplication?▼

Yes, QA checklists verify timezone consistency and deduplication alongside source freshness and completeness. These sanity checks enforce data quality standards to ensure correct, reproducible analysis before stakeholder delivery.

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