ideaverse-maintenance

name

ideaverse-maintenance

description

Keep Ideaverse vaults healthy through audits, diagnostics, and maintenance workflows. Use when running vault diagnostics, detecting link rot, identifying orphan notes, finding MOC bloat, suggesting archival candidates, validating frontmatter, or generating vault health reports. Triggers on requests like "audit my vault", "find broken links", "check vault health", "what needs archiving", "find orphan notes", or "run maintenance".

Ideaverse Maintenance Skill

Run audits, diagnostics, and maintenance workflows to keep Ideaverse-based Obsidian vaults healthy. Assume familiarity with the core Ideaverse methodology.

Requirements

• Python 3.8 or later
• No external dependencies (uses only Python standard library)

Vault Health Diagnostics

Quick Health Check

Preferred (when Obsidian CLI is available):

Obsidian CLI provides native graph diagnostics that are faster and more accurate than script-based analysis:

# Orphan notes (no incoming links)
obsidian orphans
obsidian orphans total

# Dead-end notes (no outgoing links)
obsidian deadends
obsidian deadends total

# Unresolved links (broken wikilinks)
obsidian unresolved
obsidian unresolved total

# Backlinks for a specific note
obsidian backlinks file="Note Name"

Use semantic search to suggest connections for orphan notes:

# Find related content for an orphan note
qmd query "summary of the orphan note content"

Fallback (Python scripts):

Run these in sequence for a complete vault audit. Scripts can be invoked directly (if executable) or via python3:

# 1. Find broken links (critical)
./scripts/find_broken_links.py /path/to/vault
# or: python3 scripts/find_broken_links.py /path/to/vault

# 2. Find orphan notes (structural)
./scripts/find_orphans.py /path/to/vault

# 3. Check frontmatter compliance (consistency)
./scripts/check_frontmatter.py /path/to/vault

# 4. Detect MOC bloat (scale)
./scripts/detect_moc_bloat.py /path/to/vault

# 5. Find squeeze points (opportunities)
./scripts/validate_squeeze_points.py /path/to/vault

# 6. Suggest archival candidates (hygiene)
./scripts/suggest_archival.py /path/to/vault

Note: If python3 is not available on your system, use python if it points to Python 3.x.

Script Descriptions

Script	Purpose	Output
find_broken_links.py	Discover wikilinks pointing to non-existent notes	List of source files with broken links
find_orphans.py	Identify notes with no incoming links	List of orphan note paths
check_frontmatter.py	Verify required properties (up, created)	Issues grouped by type
detect_moc_bloat.py	Find MOCs with 50+ direct links	MOCs sorted by link count
validate_squeeze_points.py	Find unstructured clusters needing MOCs	Terms linked 10+ times without MOC
suggest_archival.py	Identify stale notes for archival consideration	Notes sorted by staleness indicators

All scripts accept a vault path argument and return structured output. Exit code 0 = healthy, 1 = issues found.

Maintenance Cadences

Daily (5 minutes)

• Review today's daily log for unprocessed fleeting notes
• Quick scan for any broken links introduced today

Weekly (15-30 minutes)

• Run find_broken_links.py and fix any issues
• Run find_orphans.py - triage: link, archive, or delete
• Spot-check frontmatter on recently created notes

Monthly (1-2 hours)

• Full diagnostic suite (all 6 scripts)
• Review MOC bloat - split any MOCs over 50 links
• Process squeeze points - create MOCs where warranted
• Review archival suggestions - archive confirmed stale notes
• Generate and save vault health report

Quarterly (Half day)

• Comprehensive vault audit
• Review and clean Archive folder
• Assess MOC hierarchy - simplify or restructure as needed
• Update any vault-level documentation

Deep Dives

Use reference docs for detailed decision trees, workflows, and maintenance playbooks:

• references/vault-hygiene.md - Hygiene workflows, cadences, and reporting
• references/troubleshooting.md - Diagnosis and resolution guides