Data Catalog Enricher
SkillDev toolsEnriches data catalog entries with automated metadata
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Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/data-engineering-analytics/skills/data-catalog-enricher/SKILL.md and read by Ahel’s review.
Overview
Enriches data catalog entries with automated metadata. This skill enhances data discoverability and governance through intelligent metadata augmentation.
Capabilities
- Automated tag suggestion
- Business glossary term matching
- Owner/steward recommendation
- Usage pattern analysis
- Data classification (sensitivity, PII)
- Quality score integration
- Lineage enrichment
- Search optimization
Input Schema
{
"catalogEntry": "object",
"dataProfile": "object",
"existingGlossary": "object",
"organizationContext": "object"
}
Output Schema
{
"enrichedEntry": "object",
"suggestedTags": ["string"],
"glossaryMatches": ["object"],
"classificationResults": "object",
"ownerSuggestions": ["string"]
}
Target Processes
- Data Catalog
- Data Lineage Mapping
- Data Quality Framework
Usage Guidelines
- Provide existing catalog entry for enrichment
- Include data profile for classification analysis
- Supply business glossary for term matching
- Add organization context for owner recommendations
Best Practices
- Regularly update glossary matches as glossary evolves
- Validate PII classifications with data stewards
- Integrate quality scores from quality framework
- Maintain consistent tagging taxonomy
- Review and approve automated classifications
Signals
- GitHub stars
- 2k
- Forks
- 113
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
data-catalog-enricher- Source
- github.com/a5c-ai/babysitter