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updating-knowledge-domain

Update knowledge graphs by adding, removing, merging, or splitting items and competences.

13|Updated Feb 12, 2026
Search Tags:#validation#maintenance#knowledge-space#domain-update#trace-operations#kst-utils
One-click install
npx skills add https://github.com/vanderbilt-data-science/knowledge-spaces --skill updating-knowledge-domain
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: updating-knowledge-domain
Source: https://github.com/vanderbilt-data-science/knowledge-spaces/tree/main/.claude/skills/updating-knowledge-domain
Command: npx skills add https://github.com/vanderbilt-data-science/knowledge-spaces --skill updating-knowledge-domain

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Updates knowledge graphs when the domain evolves to preserve mathematical integrity.

Core Features & Use Cases

  • Change classification and trace operations to add, remove, merge, or split items and competences while maintaining well-gradedness.
  • Validation and impact analysis across student states, learning paths, and materials using the provided tooling (kst_utils.py).
  • Re-enumeration and closure application to ensure acyclicity and consistency after every change.

Quick Start

Provide the graph path and a detailed change description to apply a maintenance update.

Frequently Asked Questions about updating-knowledge-domain

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I update a knowledge graph when the domain evolves without breaking well-gradedness?▼

To update a knowledge graph safely, apply trace operations like adding, removing, merging, or splitting items and competences. Post-change validation ensures mathematical integrity and maintains well-gradedness throughout the domain evolution.

What is the best way to validate knowledge space changes and analyze their impact on student states?▼

Validating knowledge space changes requires running transitive closure and acyclicity checks using kst_utils.py. Impact analysis verifies consistency across student states, learning paths, and materials after applying domain updates.

How do I ensure acyclicity and consistency after modifying items in a knowledge space?▼

Ensuring acyclicity and consistency requires applying transitive closure and re-enumerating states via scripts like kst_utils.py. These validation checks verify mathematical integrity after any knowledge graph modification.

What do I need to provide to apply a maintenance update to a knowledge graph?▼

To apply a maintenance update, you need to provide the graph path and a detailed change description. This input allows the system to execute trace operations and run validation checks for knowledge space consistency.

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