find-connections-a

Action skill — Connection discovery: semantic search, backlink analysis, tag-based discovery, PARA structure analysis.

Connection Discovery

Combines semantic search, backlinks, tags, and PARA structure to map relationships across the vault.

Input Parsing

The argument can be:

1. File path → Read the note, use its content as the search basis
2. Topic text (e.g., "prediction market pricing") → Use directly as search query
3. Area name (e.g., "ai-dev-ecosystem") → Read the area's L0 MOC, use its thesis and key concepts

Process

1. Semantic Search

Query the vault for similar notes.

For a note or topic:

qmd query "<key sentences or topic>" --files

For an area, run multiple queries based on the MOC's sections:

qmd vsearch "<section 1 topic>" --files
qmd vsearch "<section 2 topic>" --files

Collect top 10-15 results across queries.

2. Backlink Analysis

• Find all notes that link to/from the target
• Trace 2-hop connections: notes that share common links but don't directly link to the target
• Use Grep: search for [[note-name]] patterns across the vault

3. Tag-Based Discovery

Find notes with knowledge-role tags that suggest conceptual relationships:

• #seed + #seed in similar areas → potential threads waiting to be connected
• #question notes → might pose questions the target answers
• #tool notes → frameworks that apply to the target's domain
• #insight notes → crystallized understanding that builds on the target
• Shared tags + semantic similarity = strong connection signal

4. PARA Structure Analysis

Check structural relationships:

• Which projects draw from the same area?
• Which areas have overlapping scope with the target?
• Which resources were captured for the same purpose?
• Read project briefs to find area MOC references

5. Synthesize Connection Map

Present findings organized by relationship type:

Direct connections — linked or semantically close:

- [[2025-01-21_agentic-primitives]] (ai-dev-ecosystem)
  Semantic similarity: high | Shared concepts: agent architecture, tooling

Indirect connections — shared links, related tags, related area:

- [[2025-02-01_transformer-scaling]] (modeling)
  Connection via: both linked from [[00_ai-dev-ecosystem]], both tagged #thread

Project opportunities — area knowledge that could feed a project:

- prediction-markets area notes → prediction-market-algo-dev project
  Notes about market mechanics could inform algorithm design

Gaps — topics mentioned but with no notes:

- "memory continuity" mentioned in 3 notes but no dedicated note exists
- "cross-market correlation" referenced in project brief but no area coverage

Output Format

## Connection Map: {input}

### Direct (N notes)
{strongest connections}

### Indirect (N notes)
{2-hop links, shared tags, related areas}

### Project Opportunities
{area notes that could serve projects}

### Gaps
{topics referenced but not covered}

When to Use vs. Other Skills

• backlinks-a — focused on one note's links. Use when you know the note.
• find-connections-a — broad exploration across the vault. Use when mapping a topic or area.
• sem-search-a — raw search results. Use when you just need to find notes.