ClaudSkills / Science & Research / data-science-research

Data Quality Validation

Quality score: 70/100  ·  Category: Science & Research  ·  Sub-category: data-science-research
Systematic data validation, error detection, cross-source reconciliation, and query correctness checking for analytical work. Use when validating Snowflake queries, catching calculation errors, reconciling metrics across different data sources, checking for null values, ensuring date range validity, detecting statistical anomalies, validating metric calculations (median vs mean, rate normalization), checking aggregation grain (per-record vs per-entity), validating contribution analysis for non-additive metrics, or validating consistency across analysis sections. Essential when reviewing analysis before publication, debugging unexpected results, or ensuring data quality in reports. Triggers include "validate this query", "check for errors", "why don't these numbers match", "should I use median or mean", "why don't contributions sum to 100%", "reconcile these metrics", "verify data quality", or any request to catch potential issues in data or calculations.

What this skill does

Data Quality Validation is a production-ready Claude Code skill (quality score 70/100) in the data-science-research sub-category. It ships as a SKILL.md file that Claude Code auto-discovers under ~/.claude/skills/data-quality-validation/ and loads when your prompt matches the skill's trigger.

When to invoke it: Use when validating Snowflake queries, catching calculation errors, reconciling metrics across different data sources, checking for null values, ensuring date range validity, detecting statistical anomalies, validating metric calculations (median vs mean, rate normalization), checking aggregation grain (per-record vs per-entity), validating contribution analysis for non-additive metrics, or validating consistency across analysis sections. Essential when reviewing analysis before publication, debugging unexpected results, or ensuring data quality in reports.

Who uses this skill

The Data Quality Validation skill is built for researchers, data scientists, academics, and analysts working with complex data and scientific literature. It is part of the open ClaudSkills registry, a community-curated catalog of 15,000+ capabilities you can install for Claude Code — the Claude CLI agent.

How to install

Free

Manual install (2 steps)

mkdir -p ~/.claude/skills/data-quality-validation
curl -L https://claudskills.com/skills/data-quality-validation/SKILL.md \
  -o ~/.claude/skills/data-quality-validation/SKILL.md

Or just download SKILL.md directly and drop it into ~/.claude/skills/data-quality-validation/. Claude Code auto-discovers it on next session.

Skills live at ~/.claude/skills/data-quality-validation/SKILL.md on macOS/Linux, or %USERPROFILE%\.claude\skills\data-quality-validation\SKILL.md on Windows. See the full install guide for step-by-step instructions.

Pro

One-click install via the desktop app

The ClaudSkills desktop app installs any skill directly into ~/.claude/skills/ with one click — no terminal required. Pro starts at $9/mo or $149 lifetime.

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Part of ClaudSkills — the open registry for Claude Code skills.  ·  What's New  ·  Install guide  ·  About  ·  llms.txt

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