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Article Enrichment

Enhances knowledge base articles with metadata, cross-references, related content links, and consistent formatting to improve discoverability and usefulness.

Operations by Interloom

Capabilities

  • Adds structured metadata — categories, tags, difficulty levels — to articles
  • Generates cross-references and related article links based on content analysis
  • Normalizes formatting to match your knowledge base style guide
  • Suggests content improvements — missing sections, unclear instructions, outdated terminology

Part of These Solutions

Operations

Knowledge Maintenance

End-to-end knowledge base management from content creation through review and publication, with AI-powered freshness monitoring, article enrichment, and structured review workflows.

Overview

The Article Enrichment skill processes knowledge base articles and enhances them with the metadata, cross-references, and formatting consistency that make content discoverable and useful. It handles the enrichment work that would otherwise require editors to manually tag, link, and format every article.

How It Works

Articles are processed through a multi-stage pipeline: metadata extraction, cross-reference generation, formatting normalization, and improvement suggestion. The skill analyzes article content to assign appropriate categories, tags, and difficulty levels. It identifies related articles and generates cross-reference links. Formatting is normalized to match your style guide, and the skill suggests improvements where content could be clearer or more complete.

The enrichment schema is configurable — you define the metadata fields, formatting rules, and quality standards that matter to your team.

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