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Glossary Generator Skill

Summary

This skill automatically generates a comprehensive glossary of terms from a learning graph's concept list, ensuring each definition follows ISO 11179 metadata registry standards (precise, concise, distinct, non-circular, and free of business rules).

Order

This skill should be executed after the Learning Graph skill has completed and the concept list has been finalized. The glossary relies on having a complete, reviewed list of concepts from the learning graph's concept enumeration phase.

Inputs

Primary Input Files

  1. Concept List (docs/learning-graph/02-concept-list-v1.md or similar)
  2. Format: Numbered markdown list
  3. Expected: 150-250 pedagogically-sound concept labels

  4. Quality check: Each concept should be in Title Case and under 32 characters

  5. Course Description (docs/course-description.md)

  6. Provides context for appropriate examples
  7. Used to ensure terminology aligns with course objectives
  8. Quality check: Must contain audience, prerequisites, and learning outcomes

Input Quality Metrics (Scale 1-100)

Concept List Quality Score: - 90-100: All concepts unique, properly formatted (Title Case), appropriate length (< 32 chars) - 70-89: Most concepts meet standards, minor formatting issues - 50-69: Some duplicate concepts or formatting inconsistencies - Below 50: Significant issues - PROMPT USER for manual review

Quality Checks:

  1. Verify no duplicate concept labels (100% unique)
  2. Check Title Case formatting (target: 95%+)
  3. Validate length constraints (target: 98% under 32 chars)
  4. Assess concept clarity (no ambiguous terms)

User Dialog Triggers: - Score < 70: "The concept list has quality issues. Would you like to review and clean it before generating the glossary?" - Duplicates found: "Found [N] duplicate concepts. Should I remove duplicates automatically or would you like to review?" - Formatting issues: "Found [N] concepts with formatting issues. Auto-fix?"

Outputs

Generated Files

  1. docs/glossary.md - Complete glossary in alphabetical order
  2. Header: "# Glossary of Terms"
  3. Format: Each term as level-4 header (####)
  4. Definition body text following ISO 11179 standards
  5. Optional examples prefixed with "Example:"

  6. Cross-references to related terms where appropriate

  7. docs/learning-graph/glossary-quality-report.md - Quality assessment

  8. ISO 11179 compliance metrics for each definition
  9. Identification of circular definitions
  10. Precision scores for each term
  11. Suggestions for improvement

Output Quality Metrics (Scale 1-100)

Definition Quality Score: - Precision (25 points): Each definition accurately captures the concept's meaning - Conciseness (25 points): Definitions are brief (target: 20-50 words) - Distinctiveness (25 points): Each definition is unique and distinguishable - Non-circularity (25 points): No definition references undefined terms or creates circular dependencies

Quality Checks Performed:

  1. ISO 11179 compliance validation (all 4 criteria)
  2. Readability score (Flesch-Kincaid grade level appropriate for audience)
  3. Example coverage (target: 60-80% of terms include examples)
  4. Cross-reference accuracy (all referenced terms exist in glossary)
  5. Alphabetical ordering verification
  6. Markdown formatting validation

Success Criteria: - Overall quality score > 85 - No circular definitions - 100% alphabetical ordering - All terms from concept list included - Markdown renders correctly in mkdocs

Additional Outputs

  1. Navigation Update - Adds glossary link to mkdocs.yml if not present
  2. Cross-reference Index (docs/learning-graph/glossary-cross-ref.json) - JSON mapping of term relationships for future semantic search