What are informal sections in this context?

Informal sections are headers like 'See Also' or 'Related Notes' that contain references invisible to the knowledge graph. This skill converts them to formal WikiLinks under the ## Relations section.

Does it support cross-project links?

WikiLinks are scoped to single projects. This skill detects when you've accidentally used a WikiLink for a different project and helps you convert it to a compatible text-based reference format.

Why are self-referential links a problem?

In Basic Memory systems, a note linking to itself can cause infinite loops during automated context retrieval or graph traversal, making the knowledge base unstable.

Can this skill fix broken links automatically?

It identifies typos and suggests the correct existing titles, providing specific edit commands to help you quickly update notes.

Memory Relation Verifier

Name: Memory Relation Verifier
Author: ZivBA

byZivBA

0•

학습 및 문서화

Audits and repairs note relationships within Basic Memory knowledge bases to ensure graph integrity and prevent infinite loops.

The Memory Relation Verifier is a specialized health-check tool designed for users of the Basic Memory system. It scans notes for critical relationship errors, such as self-referential links that cause infinite processing loops, broken WikiLinks, and invalid cross-project references. By identifying informal 'See Also' sections and converting them into structured, machine-readable relations, the skill ensures that your AI-powered knowledge base remains accurate, navigable, and fully indexed for the knowledge graph. It is particularly useful during quality audits or after large-scale content migrations to maintain a high-quality, interconnected documentation system.

주요 기능

01Evaluates relation quality by encouraging specific types like 'implements' or 'requires'

02Scans informal related headers to convert them into structured graph relations

03Flags invalid cross-project WikiLinks and converts them to standard text-based references

04Identifies broken WikiLinks and suggests corrections or forward references

050 GitHub stars

06Detects and removes self-referential relations that trigger infinite loops

사용 사례

01Performing a quality audit on a large knowledge base after a series of major edits

02Troubleshooting infinite loops or missing connections in a Claude Code memory graph

03Standardizing relationship metadata across multiple projects for better context retrieval

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add zivba/basic-memory-toolkit verify-memory-relations

For use in Claude.ai and ChatGPT

주요 기능

01Evaluates relation quality by encouraging specific types like 'implements' or 'requires'

02Scans informal related headers to convert them into structured graph relations

03Flags invalid cross-project WikiLinks and converts them to standard text-based references

04Identifies broken WikiLinks and suggests corrections or forward references

050 GitHub stars

06Detects and removes self-referential relations that trigger infinite loops

사용 사례

01Performing a quality audit on a large knowledge base after a series of major edits

02Troubleshooting infinite loops or missing connections in a Claude Code memory graph

03Standardizing relationship metadata across multiple projects for better context retrieval