Agent-Skills.md

Agent Skills: Knowledge Locator

'Consult this skill when searching or navigating stored knowledge. Use

UncategorizedID: athola/claude-night-market/knowledge-locator

Repository

athola/claude-night-market
atholaLicense: MIT
23423

Install this agent skill to your local

pnpm dlx add-skill https://github.com/athola/claude-night-market/tree/HEAD/plugins/memory-palace/skills/knowledge-locator

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plugins/memory-palace/skills/knowledge-locator/SKILL.md

Skill Metadata

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

Table of Contents

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

| Mode | Description | Best For | |------|-------------|----------| | Spatial | Query by location path | "Find concepts in the Workshop" | | Semantic | Search by meaning/keywords | "Find authentication-related items" | | Sensory | Locate by sensory attributes | "Blue-colored concepts" | | Associative | Follow connection chains | "Related to OAuth" | | Temporal | Find 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

| Room | Content | Example 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