Migrate flat vaults to hierarchical and faceted tag and folder schemes.
npx skills add https://github.com/hodor/claude-compass --skill taxonomize
Please help me install this Agent Skill. Skill: taxonomize Source: https://github.com/hodor/claude-compass/tree/main/plugin/skills/taxonomize Command: npx skills add https://github.com/hodor/claude-compass --skill taxonomize
This Skill helps organize your vault by migrating flat specs to a hierarchical and faceted scheme, improving navigation and discoverability.
Run the taxonomize skill with the --apply flag to execute the migration proposal for your specs.
High-intent search queries and answers about installing and using this skill.
To reorganize a flat vault, this Skill bulk migrates your documents by analyzing existing tags, proposing a faceted vocabulary, and restructuring your folder hierarchy. It improves navigation and discoverability across your knowledge base.
The best way to clean up project knowledge tagging is using a Skill that analyzes your current tags to propose synonyms, removals, and additions. This establishes a structured, faceted vocabulary that makes related documents easier to discover.
Yes, you can migrate your vault folder structure without losing existing tags. The migration is non-destructive, preserving all current tags and document references while promoting folders and grouping related specs together.
To apply a proposed tag vocabulary and folder grouping, run the taxonomize Skill with the `--apply` flag. This executes the migration proposal, converting your flat specs into a structured, hierarchical format.
You need to convert flat specs to a hierarchical and faceted scheme when navigating a large knowledge base becomes difficult. This restructuring improves document discoverability by grouping related project specs into organized folders.
Yes, vault organization with faceted tags supports bulk migration of all existing documents. It analyzes your entire flat vault to suggest tag improvements and folder promotions, restructuring everything simultaneously without data loss.
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