kg-quality-check

Community

Quantify KG quality with LLM-guided checks.

AuthorYH-05
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This skill measures and reports the data quality of a knowledge graph (KG) by running seven quantitative probes on a Neo4j KG (v2.2) and applying an LLM-based judge to evaluate claim/fact accuracy, discovery potential, and graph integrity. It outputs a Markdown report with scores, issues, and concrete improvement suggestions.

Core Features & Use Cases

  • Quantitative quality metrics: seven categories computed via Cypher probes against the KG schema.
  • LLM-as-Judge: assess precision of claims/facts, hypothesize discoveries, and generate a structured critique.
  • Automated reporting: produce a markdown quality report suitable for review after data ingestion or periodic monitoring.

Quick Start

Run the kg-quality-check workflow to generate a comprehensive quality report for the current KG.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: kg-quality-check
Download link: https://github.com/YH-05/quants/archive/main.zip#kg-quality-check

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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