foryourhealth111-pixel/data-quality-checker
bundled/skills/data-quality-checker/SKILL.md
Validate dataset completeness and basic correctness before downstream analysis. Use for nulls, duplicates, schema drift, range checks, and column-level sanity reviews; not for anomaly detection or ML evaluation.
$ install --global
skillsauthnpx skillsauth add foryourhealth111-pixel/vco-skills-codex data-quality-checkerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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TrivyContainer and dependency vulnerability scanner
95%
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SemgrepStatic code analysis for vulnerabilities
95%
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mcp-scan (Snyk)Model Context Protocol security validation
95%
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Snyk (dep)Open source security scanning
50%
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Socket.devSupply chain security analysis
50%
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VirusTotalMulti-engine malware detection
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CrowdStrikeAdvanced threat intelligence
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OSV-ScannerOpen Source Vulnerability database check
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OWASP Dep-Check
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Last scanned: Apr 20, 2026, 2:20 AM9.0s1 file scanned
SKILL.md
- name:
- data-quality-checker
- description:
- |
- allowed-tools:
- Read, Write, Edit, Bash, Grep
- version:
- 1.0.0
- license:
- MIT
- author:
- Jeremy Longshore <[email protected]>
Data Quality Checker
Purpose
Use this skill when the user needs to know whether the dataset is trustworthy enough to continue.
When to Use
Use this skill when:
- Checking null rates, duplicates, invalid categories, or out-of-range values
- Verifying schemas after ETL or data ingestion
- Producing a pre-modeling data sanity checklist
Not For / Boundaries
- Rare-event or fraud detection: use
anomaly-detector - Model metrics and benchmark comparisons: use
evaluating-machine-learning-models - Report authoring and presentation polish: use
scientific-reporting
Typical Outputs
- Data quality scorecards
- Column-level issue summaries
- Recommended cleaning priorities before modeling or reporting
Related Skills
anomaly-detectorafter the basic data checks passstructured-content-storageif the dataset and outputs need stricter organization
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