find-connections-a

What this skill does

> **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:
```bash
qmd query "<key sentences or topic>" --files
```

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

```markdown
## 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.