ideaverse-maintenance_skill

This skill runs vault audits and maintenance workflows to identify broken links, orphan notes, and archival candidates, improving Ideaverse health.
  • Python

5

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

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npx veilstrat add skill mrfelton/ideaverse --skill ideaverse-maintenance

  • SKILL.md3.5 KB

Overview

This skill automates audits, diagnostics, and maintenance workflows to keep Ideaverse-style Obsidian vaults healthy and navigable. It provides scripts to detect broken links, orphan notes, frontmatter issues, MOC bloat, squeeze points, and archival candidates. Use it to run quick checks, scheduled maintenance, or full audits and generate structured outputs for triage.

How this skill works

Each script inspects a vault directory and returns structured results plus an exit code (0 = healthy, 1 = issues found). The suite includes link validation, incoming-link analysis, frontmatter checks, MOC link counting, cluster detection (squeeze points), and staleness analysis for archival suggestions. Outputs are easy to parse and can be run individually or as a full diagnostic sequence.

When to use it

  • After major note imports or syncs to detect new broken links
  • When you want a weekly or monthly maintenance checklist for vault hygiene
  • Before reorganizing MOCs or creating new MOC hierarchies
  • To find orphan notes that need linking, archiving, or deletion
  • When preparing a vault health report or audit for a quarterly review

Best practices

  • Run the quick health check sequence regularly: broken links, orphans, frontmatter, MOC bloat, squeeze points, archival suggestions
  • Treat script output as a triage list: fix critical broken links first, then address structural issues
  • Follow cadences: daily for fleeting notes, weekly for fixes, monthly for full diagnostics, quarterly for comprehensive audits
  • Use the structured outputs to automate bulk fixes or feed into reporting tools; keep a saved health report with date stamps
  • When splitting MOCs, prefer smaller topical MOCs under 50 links and create clear MOC naming conventions

Example use cases

  • Audit a vault after migrating notes from another system to catch link rot and frontmatter gaps
  • Run find_orphans.py to compile a list of unlinked notes for triage and integration into MOCs
  • Detect MOC bloat to decide which MOCs need splitting and to rebalance navigation
  • Generate archival suggestions to identify stale content for cleanup or move to an Archive folder
  • Perform a monthly full diagnostic and save the structured report for trend tracking and maintenance planning

FAQ

Python 3.8 or later is required; no external dependencies are used, so the standard library is sufficient.

How do I interpret exit codes from the scripts?

Exit code 0 means no issues found; exit code 1 indicates one or more issues were detected and the script output lists them for review.

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