connect

Scan Obsidian markdown notes and propose wikilinks with relationship types.

23|2|Updated Mar 20, 2026
One-click install
npx skills add https://github.com/onebrain-ai/onebrain --skill connect-onebrain-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: connect
Source: https://github.com/onebrain-ai/onebrain/tree/main/.claude/plugins/onebrain/skills/connect
Command: npx skills add https://github.com/onebrain-ai/onebrain --skill connect-onebrain-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Connect helps you discover meaningful relationships between your existing Obsidian notes so your knowledge graph becomes easier to navigate and more useful over time.

Core Features & Use Cases

  • Wikilink suggestions between existing notes: identifies conceptual overlap, cause-effect, elaboration, contrast, sequence, and application patterns.
  • Scalable vault linking: uses a dedicated “Knowledge Linker” agent for large note sets to avoid slowing down or overwhelming context.
  • Human-approved updates: proposes up to 10 suggestions per batch and only writes links after you approve.
  • Optional follow-ups: can list orphan notes with no outbound links and can add typed relationship properties in frontmatter for machine-readable graph relationships.

Quick Start

Use connect to scan for relationships and suggest wikilinks for a specific note, then approve the batches you want applied.

Frequently Asked Questions about connect

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

FAQPage Schema
How do I find missing wikilinks between my Obsidian notes?

To find missing wikilinks between Obsidian notes, the Skill scans markdown content and metadata to identify conceptual overlaps, then recommends typed relationships with actionable reasons without duplicating existing connections.

What is the best way to link a large Obsidian vault without slowing down context?

The best way to link a large Obsidian vault without slowing down context is using a dedicated Knowledge Linker agent that processes scalable note sets, proposing up to ten human-approved wikilink suggestions per batch.

Does this approach support adding typed relationships in markdown frontmatter?

Yes, this approach supports adding typed relationship properties in markdown frontmatter, creating machine-readable graph relationships after you approve the proposed wikilink batches during the vault maintenance process.

Can I identify orphan notes with no outbound links in my knowledge graph?

Yes, you can identify orphan notes with no outbound links in your knowledge graph as an optional follow-up action after scanning notes and approving initial wikilink connection suggestions.

What types of note relationships can semantic search discover in a knowledge graph?

Semantic search in a knowledge graph discovers conceptual overlap, cause-effect, elaboration, contrast, sequence, and application patterns, providing specific reasons for each proposed wikilink to strengthen note connections.

How do I prevent duplicate wikilinks when connecting existing notes?

To prevent duplicate wikilinks when connecting existing notes, the Skill scans current markdown connections first and excludes any existing wikilinks from its proposed relationship suggestions before presenting them for approval.