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graph-hygiene

Diagnose Logseq knowledge graphs for stale pages and broken links.

2|Updated Jul 22, 2026
Search Tags:#linting#logseq#maintenance#data-integrity#knowledge-management#graph-theory
One-click install
npx skills add https://github.com/0xUrsanomics/utopia-os --skill graph-hygiene
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: graph-hygiene
Source: https://github.com/0xUrsanomics/utopia-os/tree/main/skills/graph-hygiene
Command: npx skills add https://github.com/0xUrsanomics/utopia-os --skill graph-hygiene

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python3, and includes scripts (resource) components.

What problem does it solve?

This Skill prevents knowledge graph entropy by identifying structural issues, broken links, and stale content before they compound into unmanageable technical debt.

Core Features & Use Cases

  • Automated Health Audits: Scans for orphans, dead links, stale pages, and missing properties across specific namespaces.
  • Structural Integrity: Validates compiled truth and timeline structures to ensure consistent knowledge organization.
  • Evidence-Based Reporting: Every finding includes a mandatory falsification test to ensure accuracy and prevent false positives.

Quick Start

Run the graph hygiene skill to perform a full audit of the knowledge graph and generate a summary report.

Frequently Asked Questions about graph-hygiene

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

FAQPage Schema
How do I find broken links and orphan pages in my Logseq knowledge graph?▼

Automated health audits scan Logseq namespaces to identify orphan pages, broken links, and stale content, validating page properties against established standards and flagging issues for human review.

Can I automate Logseq maintenance tasks without risking accidental data deletion?▼

Yes, this linting approach flags stale pages and structural inconsistencies for human review without performing destructive auto-deletions, ensuring safe knowledge graph maintenance.

Does Logseq linting work with specific namespaces to validate page properties?▼

Logseq linting operates across defined namespaces to validate page properties and compiled truth structures against operational standards, ensuring consistent knowledge organization across targeted graph sections.

Do I need Python3 and Logseq MCP tools to perform knowledge graph health monitoring?▼

Yes, knowledge graph health monitoring requires Python3 to run the linting scripts and integration with Logseq MCP tools to query graph metadata and validate page properties against standards.

What is the best way to prevent knowledge graph entropy in Logseq?▼

The best way to prevent knowledge graph entropy is to run regular diagnostic linting audits that identify structural issues and stale content before they compound into unmanageable technical debt.

How do I ensure accuracy when identifying stale pages in a knowledge graph?▼

To ensure accuracy when identifying stale pages, the linting process requires a mandatory falsification test for every finding, providing evidence-based reporting that prevents false positives.

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