Agent skill
vault-hubs
Find hub notes (highly connected notes with many links). Triggers on "hubs", "hub notes", "most connected", "popular notes", "highly connected notes".
Stars
163
Forks
31
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/development/find-hubs
SKILL.md
Hubs Skill
Find hub notes - highly connected notes that serve as central points in your knowledge graph.
Purpose
Hub notes are the opposite of orphans. They have many connections (backlinks + forward links) and serve as:
- Knowledge entry points (MOCs, indexes)
- Central concepts (frequently referenced ideas)
- Active topics (currently being worked on)
- Important entities (key people, projects, technologies)
Finding hubs helps you:
- Identify your vault's "center of gravity"
- Understand what topics are most important to you
- Find natural MOC (Map of Content) candidates
- Discover over-connected notes that might need splitting
When to Use
Invoke when you want to:
- Find most connected notes: "hubs" or "hub notes"
- Discover vault structure: "most connected" or "popular notes"
- Find MOC candidates: "central notes" or "important notes"
- Audit note importance: Part of vault analysis
Process
1. Call MCP Tool
Call: mcp__flywheel__find_hub_notes
Parameters: { min_links: 5 } # Default threshold
2. Categorize Hubs
Group hubs by type for better analysis:
By Connection Type:
Balanced hubs (many backlinks + forward links):
- Project X: 45 backlinks, 23 forward links (good MOC)
- Technology Y: 34 backlinks, 28 forward links (central concept)
Backlink hubs (many backlinks, few forward links):
- Daily Habit: 300+ backlinks, 2 forward links (referenced entity)
- Person Name: 67 backlinks, 3 forward links (person)
Forward link hubs (many forward links, few backlinks):
- Tech Index: 3 backlinks, 45 forward links (potential MOC)
- Work Dashboard: 2 backlinks, 38 forward links (aggregator)
By Hub Strength:
Super hubs (100+ total links): 3
Strong hubs (50-99 links): 12
Medium hubs (20-49 links): 45
Weak hubs (5-19 links): 96
3. Display Report
Hub Notes Report
═══════════════════════════════════════════════
Found 156 hub notes (11% of vault)
Threshold: 5+ total links
TOP HUBS (20 shown):
1. [[Daily Habit 1]] - 300+ total links
← 300 backlinks | → 2 forward links
Type: Habit | Daily reference
Hub strength: SUPER (daily tracking)
2. [[Main Project]] - 68 total links
← 45 backlinks | → 23 forward links
Type: Project | Balanced hub
Hub strength: STRONG ⭐ (excellent MOC!)
3. [[Core Technology]] - 56 total links
← 42 backlinks | → 14 forward links
Type: Technology | Balanced hub
Hub strength: STRONG (central tech)
═══════════════════════════════════════════════
BREAKDOWN BY TYPE:
Habits: 3 (super hubs from daily tracking)
Technologies: 34 (central tech concepts)
Projects: 18 (active work)
People: 23 (frequently mentioned)
Concepts: 45 (important ideas)
MOC CANDIDATES (balanced hubs):
Main Project: 45 ← | 23 → (⭐ excellent MOC)
Core Technology: 34 ← | 28 → (⭐ good MOC)
Options:
1. Show full list (all 156 hubs)
2. Filter by type/strength
3. Find potential MOCs (balanced hubs)
Implementation Details
Hub Criteria
A note is a hub if:
- Total links (backlinks + forward links) >= min_links
- Default threshold: 5 links
- User can adjust: "hubs with 20+ links"
Hub Strength Classification
python
def classify_hub_strength(total_links):
if total_links >= 100:
return "SUPER"
elif total_links >= 50:
return "STRONG"
elif total_links >= 20:
return "MEDIUM"
else:
return "WEAK"
Hub Balance Score
Measures how balanced backlinks vs forward links are:
python
def hub_balance_score(backlinks, forward_links):
if backlinks == 0 or forward_links == 0:
return 0 # Completely unbalanced
ratio = min(backlinks, forward_links) / max(backlinks, forward_links)
return ratio * 100 # 0-100%
Balance interpretation:
- 80-100%: Excellent MOC candidate
- 50-79%: Good MOC candidate
- 20-49%: Could improve as MOC
- <20%: Unbalanced (entity vs aggregator)
Related Skills
- orphans: Opposite of hubs (zero connections)
- backlinks: Show specific note's connections
- clusters: Find groups of related hubs
- health: Overall vault metrics (hub % is key metric)
Performance
- MCP call: ~300-500ms for large vaults
- Categorization: ~100ms for 156 hubs
- Total: Usually <1 second
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