Detect entity mentions in Obsidian Vault notes and suggest wikilinks.
npx skills add https://github.com/robinlllll/claude-code-skills --skill link-robinlllll
Please help me install this Agent Skill. Skill: link Source: https://github.com/robinlllll/claude-code-skills/tree/main/link Command: npx skills add https://github.com/robinlllll/claude-code-skills --skill link-robinlllll
Manually linking entities across a large Obsidian Vault is time-consuming and error-prone. This Skill automatically identifies mentions of entities like tickers, company names, and concepts, and suggests wikilinks to strengthen knowledge graph connectivity without altering frontmatter or existing links.
Tell Claude to run the link skill in preview mode to scan the Vault and show wikilink opportunities.
High-intent search queries and answers about installing and using this skill.
To automatically add wikilinks to Obsidian notes, this Skill scans your Vault to detect entity mentions like tickers and concepts, then proposes [[wikilinks]] that connect notes without altering existing content or frontmatter.
Connecting orphan notes in an Obsidian Vault is handled by building a deterministic entity dictionary from file names and directories, scanning for unlinked mentions, and generating reports of opportunities and orphan notes to improve knowledge graph connectivity.
Auto linking does not overwrite existing wikilinks in your Vault, as the workflow is designed to preserve existing links and frontmatter while only proposing new [[wikilinks]] for unlinked entity mentions.
You can preview wikilink opportunities before applying changes by running the Skill in preview mode, which scans notes and displays suggestions, while interactive and auto modes are also available for different levels of control.
Entity detection for note linking works by building a deterministic entity dictionary from configured directory themes, file names, and ticker-like names, then scanning note content to find unlinked mentions and matching them to precise targets.
Entities detected for knowledge graph linking include tickers, company names, and concepts, which are identified from file names and common directory themes to strengthen knowledge graph connectivity across multiple folders.
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