knowledge-locator

SkillDocs & knowledge

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

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the knowledge-locator skill

What this skill tells your AI

The instructions your AI receives, as published by athola/claude-night-market in plugins/memory-palace/skills/knowledge-locator/SKILL.md and read by ahel’s review.

Table of Contents

  • What It Is
  • Quick Start
  • Search Palaces
  • List All Palaces
  • When to Use
  • Search Modalities
  • Core Workflow
  • Target Metrics
  • Detailed Resources
  • PR Review Search
  • Quick Commands
  • Review Chamber Rooms
  • Context-Aware Surfacing
  • Integration

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/palace_manager.py search "authentication" --type semantic

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

List All Palaces

python scripts/palace_manager.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

# Search review chamber by query
python scripts/palace_manager.py search "authentication" \
  --palace <project_id> \
  --room review-chamber

# List entries in specific room
python scripts/palace_manager.py list-reviews \
  --palace <project_id> \
  --room decisions

# Find by tags
python scripts/palace_manager.py search-reviews \
  --tags security,api \
  --since 2025-01-01

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

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:

# When in auth/ directory
python scripts/palace_manager.py context-search auth/

# Returns:
# - Past decisions about authentication
# - Known patterns in this area
# - Relevant standards to follow

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

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/palace_manager.py search "<query>" returns results 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

Signals

GitHub stars
337
Forks
34
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
knowledge-locator
Source
github.com/athola/claude-night-market