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knowledge-locator

Searches and navigates stored knowledge in memory palaces. Use when looking for previously stored information or cross-referencing concepts across palaces.

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  • SKILL.md5.3 KB
  • modules/index-structure.md1.6 KB
  • modules/search-strategies.md1.4 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Knowledge Locator

A spatial indexing and retrieval system for finding information within and across memory palaces. Enables multi-modal search using spatial, semantic, sensory, and associative queries.

What It Is

The Knowledge Locator provides efficient information retrieval across your memory palace network by:

  • Building and maintaining spatial indices for fast lookup
  • Supporting multiple search modalities (spatial, semantic, sensory)
  • Mapping cross-references between palaces
  • Tracking access patterns for optimization

Quick Start

Search Palaces

python scripts/memory_palace_cli.py search "authentication" --type semantic

Verification: Run python --version to verify Python environment.

List All Palaces

python scripts/memory_palace_cli.py list

Verification: Run python --version to verify Python environment.

When To Use

  • Finding specific concepts within one or more memory palaces
  • Cross-referencing information across different palaces
  • Discovering connections between stored information
  • Finding information using partial or contextual queries
  • Analyzing access patterns for palace optimization

When NOT To Use

  • Creating new palace structures - use memory-palace-architect
  • Processing new external resources - use knowledge-intake
  • Creating new palace structures - use memory-palace-architect
  • Processing new external resources - use knowledge-intake

Search Modalities

ModeDescriptionBest For
SpatialQuery by location path"Find concepts in the Workshop"
SemanticSearch by meaning/keywords"Find authentication-related items"
SensoryLocate by sensory attributes"Blue-colored concepts"
AssociativeFollow connection chains"Related to OAuth"
TemporalFind by creation/access date"Recently accessed"

Core Workflow

  1. Build Index - Create spatial index of all palaces
  2. Optimize Search - Configure search strategies and heuristics
  3. Map Cross-References - Identify inter-palace connections
  4. Test Retrieval - Validate search accuracy and speed
  5. Analyze Patterns - Track and optimize based on usage

Target Metrics

  • Retrieval latency: ≤ 150ms cached, ≤ 500ms cold
  • Top-3 accuracy: ≥ 90% for semantic queries
  • Robustness: ≥ 80% success with incomplete queries

Detailed Resources

  • Index Structure: See modules/index-structure.md
  • Search Strategies: See modules/search-strategies.md
  • Cross-Reference Mapping: See modules/index-structure.md

PR Review Search

Search the review chamber within project palaces for past decisions and patterns.

Quick Commands

The CLI has no room-scoped search: search runs across every palace, and --palace, --room, list-reviews and search-reviews do not exist (this file cited them until 2026-09-18). Filter by the palace name in the output, or use Skill(memory-palace:review-chamber), which owns the chamber's own retrieval.

python scripts/memory_palace_cli.py search "authentication"

Review Chamber Rooms

RoomContentExample Query
decisions/Architectural choices"JWT vs sessions"
patterns/Recurring solutions"error handling pattern"
standards/Quality conventions"API error format"
lessons/Post-mortems"outage learnings"

Context-Aware Surfacing

When starting work in a code area, surface relevant review knowledge:

There is no context-search command. Search for the area's own words instead:

python scripts/memory_palace_cli.py search "auth"

Integration

Works with:

  • memory-palace-architect - Indexes palaces created by architect
  • session-palace-builder - Searches session-specific palaces
  • digital-garden-cultivator - Finds garden content and links
  • review-chamber - Searches PR review knowledge in project palaces

Exit Criteria

  • scripts/memory_palace_cli.py search "<query>" returns results, and says "No palaces indexed" rather than "No matches" when there is nothing to search within 500ms for a cold query against an indexed palace
  • At least one of the five search modalities (spatial, semantic, sensory, associative, temporal) returns ranked results for a valid query against an existing palace
  • Top-3 accuracy target of ≥ 90% is met for semantic queries when the queried concept is present in the indexed palace
  • Incomplete or partial queries return results rather than errors, satisfying the ≥ 80% robustness target
  • If no palace exists to search, user is directed to memory-palace-architect rather than returning an empty result silently

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