Semantic Knowledge Retrieval

You are tasked with retrieving relevant knowledge from the Obsidian vault using multi-layer semantic search.

Local Brain Search

Use Local Brain Search for all semantic search operations. Spreading activation mode recommended for synthesis queries.

Scripts:

# Static search (fast, exact matches)
BRAIN_READ_SCOPE=core,Books,document-insights resources/local-brain-search/run_search.sh "query" --limit 10 --json

# Spreading activation search (follows graph connections)
BRAIN_READ_SCOPE=core,Books,document-insights resources/local-brain-search/run_search.sh "query" --mode spreading --limit 10 --json

# Find connections
BRAIN_READ_SCOPE=core,Books,document-insights resources/local-brain-search/run_connections.sh "Note Name" --json

# Find hubs
resources/local-brain-search/run_connections.sh --hubs --json

Search Query

$ARGUMENTS

Instructions

Read role: lookup (contract: scope-mount, decided 2026-09-04): every search and neighbourhood call runs at the reasoning mount core,Books,document-insights, so recall answers "what do I know about X", and the output is grouped by scope so "what do I think about X" stays legible (the core group). Run the scope-mount trigger check on the query first; a hit appends ,company / ,thinkers / ,Books/<slug> for this run. --scope core (or "only my notes") pins the read to core; --hubs stays core always (fingerprint).

1. First Layer - Initial Search:
   • Use spreading activation for better context:

     BRAIN_READ_SCOPE=core,Books,document-insights resources/local-brain-search/run_search.sh "$ARGUMENTS" --mode spreading --limit 5 --json

   • Use Read tool to read the full content of the top 2 results
2. Second Layer - Direct Associations:
   • For the top result from layer 1, get connections:

     BRAIN_READ_SCOPE=core,Books,document-insights resources/local-brain-search/run_connections.sh "Top Result Note" --json

   • Use Read tool to read the full content of the top 2 connected notes
3. Third Layer - Extended Network:
   • For additional context, check hub notes and bridges:

     resources/local-brain-search/run_connections.sh --hubs --json

   • This reveals deeper conceptual connections

Output Format

Present the findings in this structured format:

# Knowledge Recall: [Query Topic]

## Layer 1: Direct Matches
### Your thinking (core: 02-Permanent · 03-MOCs · AI Extracted Notes · 01-Sources)
[notes found, with key excerpts]
### What you have read (Books · Document Insights) - encountered, not endorsed
[notes found, with key excerpts - never presented as "your view"]
### Records (Company · Canon · Thinkers) - only when a trigger mounted them
[facts, `provenance: reference`]

## Layer 2: First-Degree Associations
[List connected notes with their relationships and excerpts]

## Layer 3: Extended Network
[Show hub notes and bridge connections]

## Key Insights
[Synthesize the main themes and connections discovered]

## Relevant Content
[Include the most pertinent excerpts from the retrieved notes]

Important Notes

• Use --mode spreading for synthesis and connection-finding queries
• Use static mode for exact factual lookups
• Focus on quality over quantity
• Highlight unexpected connections
• Provide enough context for the user to understand the relevance
• If search returns no results, try broader terms or related concepts
• Learning active: Searches are tracked and rankings improve over time based on usage

State Dependencies

Completion Checklist

• Layer 1 search executed (spreading mode for synthesis queries)
• Layer 2 connections retrieved for top result
• Layer 3 hub notes checked for context
• Key insights synthesized from findings
• Relevant excerpts included in output