mnemo:connect — Discover Hidden Links

Analyze a note and discover connections to other notes in the vault that aren't linked yet.

Prerequisites & config

Obsidian must be open. Config at ~/.mnemo/config.json — reads vault and links_section. Schema in references/config-schema.md.

Workflow

Step 1: Identify Target Note

Accept note name as argument: /mn:connect "Atom — LongCat-Flash-Prover"

If no argument, ask: "Which note should I analyze for connections?"

Step 2: Read the Note

obsidian read file="{note_name}" vault="{vault}"

Extract:

• Key concepts, technologies, names mentioned in text
• Existing [[wikilinks]]
• Existing links in {links_section} section

Step 3: Search for Related Notes + Backlinks (single grep + backlinks, parallel)

Even better than parallel `obsidian search` calls: one `grep -E` with all concepts OR'd together. Single filesystem scan against the vault path — ~50ms for any number of concepts vs ~180ms per obsidian search.

# Get vault filesystem path once (shared helper — BSD/macOS-awk-safe)
VAULT_PATH=$(bash "${CLAUDE_PLUGIN_ROOT}/scripts/get-vault-path.sh" "{vault}")

# Run these TWO commands in parallel (single message, two Bash tool uses):
# 1. Single grep for all concepts — much faster than N separate obsidian searches
grep -rlE --include="*.md" "({concept_1}|{concept_2}|...|{concept_N})" "$VAULT_PATH" 2>/dev/null

# 2. Backlinks check
obsidian backlinks file="{note_name}" vault="{vault}"

Collect matching notes from grep output (strip vault path prefix to get note names). Exclude the target note itself. Backlinks output → notes already connected (exclude from suggestions).

Why not `obsidian search` per concept: each CLI call is ~180ms. Single grep = ~50ms total for any N. On 7 concepts: 1.26s → 50ms (25x faster).

Step 4: Generate Suggestions

Compare: notes found by search MINUS notes already linked (wikilinks + backlinks).

For each suggestion, explain WHY it's relevant (shared concept, shared tag, complementary topics).

Tension-nodes (high value, ТРИЗ): if a found note makes an OPPOSITE claim on the same question — that's NOT a duplicate, it's a #contradiction link worth surfacing. Two notes disagreeing on the same benchmark is a synthesis point, not noise.

Step 5: Present (DO NOT auto-apply)

🔗 Connection suggestions for "{note_name}"

Already connected: {N} notes
New suggestions: {N}

1. [[Atom — SCOPE beats TextGrad]]
   Why: Both discuss agentic RL stability — HisPO and SCOPE solve similar problems

2. [[MOC — Agent Self-Correction]]
   Why: Note mentions trial→verify→reflect cycle, this MOC covers the same pattern
   Action: Add to MOC? (currently not listed there)

3. [[Session — ANT-14 TextGrad research]]
   Why: Both evaluate RL approaches for agent improvement

4. [[Atom — Full attention wins on this benchmark]]  ⚡ #contradiction
   Why: opposite conclusion on the same GPU-efficiency question — tension to resolve

Apply these? (y/N, or pick numbers: 1,3)

Links are applied with their one-line context (the «Why»), not as bare [[wikilinks]] (Luhmann: state why you linked).

Step 6: Apply on Confirmation

If user confirms:

1. Add new links to {links_section} with a one-line context (Luhmann — state why connected): - [[Name]] — {why, ≤10 words}, not a bare [[Name]]. Tension links get the marker: - [[Name]] #contradiction — {what disagrees}. Via `mcp__obsidian__str_replace` (preferred — targeted insert). CLI obsidian append content="- [[name]]" is a safe fallback only for plain wikilinks (no backticks, no $())
2. If MOC suggestion — add note link to the MOC via mcp__obsidian__str_replace or obsidian append (plain wikilink = safe)
3. Verify with obsidian backlinks

Why MCP preferred: if suggestions ever include code-reference links with backticks (e.g. [[function_name()]]), CLI obsidian append content="..." would trigger zsh command substitution. MCP passes content as JSON — always safe.

Advanced modes (optional)

• Radius-2 (Scrapbox/Cosense-style): two notes sharing ≥2 of the target's links are likely related even without shared text. If text-grep yields <3 results or user asks --deep:

  obsidian eval code="(()=>{const rl=app.metadataCache.resolvedLinks;const t=Object.keys(rl['{note_path}']||{});const r={};for(const[f,l]of Object.entries(rl)){if(f==='{note_path}')continue;const s=Object.keys(l).filter(x=>t.includes(x));if(s.length>=2)r[f]=s;}return JSON.stringify(r);})()" vault="{vault}"

• KJ-Canvas (bottom-up MOC, 川喜田 affinity): for --canvas {topic} — gather all topic Atoms, drop them onto an Obsidian Canvas without categories, let the user group spatially so structure emerges. Then name clusters → new Molecules / MOC revision. Use when a topic has many Atoms but no clear MOC yet.

Gotchas

Common failures in references/gotchas.md. Tool-routing rationale in references/tool-routing.md. Skill-specific rules:

• Max 5-7 suggestions — don't overwhelm. If you find more, rank and present top-7.
• Don't suggest links to orphan notes — they need their own fixing first (run /mn:health if interested).
• Ghost notes are normal — [[Technology]] pointing to a non-existent note enables entity discovery. Not "unresolved" in the bad sense.
• Avoid generic connections — "both mention Claude" is noise. A connection is meaningful if it shares a concept, approach, or unresolved question.
• Never auto-apply — always ask the user before writing new wikilinks.