
Memory Palace Architect
- 115 installs
- 325 repo stars
- Updated August 2, 2026
- athola/claude-night-market
Systematically map a knowledge domain’s concepts, relationships, and access patterns before designing a memory palace structure with an agent.
About
Domain Analysis for Memory Palaces is a workflow skill that helps solo builders and agent users decompose an unfamiliar knowledge domain before they assign rooms, loci, or narrative paths in a memory palace. You work through identifying primary concepts and their weight, documenting hierarchies and siblings, rating complexity and prerequisites, and defining how often clusters get retrieved together. The bundled YAML template turns qualitative notes into a schema an agent can extend into palace blueprints. It is not a generic brainstorming substitute; it assumes you are organizing durable reference knowledge—framework docs, certification syllabi, product domains, or codebase mental models. Journey placement starts in Idea research because you clarify the map before validating scope or writing structured docs in Build. Pair it with the broader memory-palace-architect skill family when dependencies call for a full palace design pass. Complexity is intermediate due to relationship mapping and honest complexity scoring.
- Four-step analysis: core concepts, relationships, complexity, and access patterns
- YAML analysis template with importance, complexity 1–5, prerequisites, and access frequency
- Maps hierarchical parent-child and sibling relationships plus cross-cutting concerns
- Intermediate workflow tagged for domain, concepts, and hierarchy with estimated ~400 tokens
Memory Palace Architect by the numbers
- 115 all-time installs (skills.sh)
- Ranked #1,314 of 3,282 Productivity & Planning skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 115 |
|---|---|
| repo stars | ★ 325 |
| Security audit | 3 / 3 scanners passed |
| Last updated | August 2, 2026 |
| Repository | athola/claude-night-market ↗ |
What it does
Systematically map a knowledge domain’s concepts, relationships, and access patterns before designing a memory palace structure with an agent.
Files
Status: unwired. As of v1.9.4, no command or agent
invokes Skill(memory-palace:memory-palace-architect).The /palace create command does palace creation directlywithout routing through this skill. The architectural
guidance below is reference material; consult it when
designing a new palace by hand. Tracked for follow-up in
the April 2026 skill audit.
Table of Contents
- What It Is
- Quick Start
- Create a New Palace
- List Existing Palaces
- View Palace Status
- When to Use
- Architectural Templates
- Core Workflow
- Detailed Resources
- Integration
- Expected Outputs
Memory Palace Architect
Design and construct virtual memory palaces for spatial knowledge organization. This skill guides you through creating memorable spatial structures that enhance recall and organize complex information.
What It Is
A memory palace is a mnemonic technique that uses spatial visualization to organize and recall information. This skill provides a systematic approach for:
- Analyzing knowledge domains for optimal spatial mapping
- Designing architectural layouts that reflect conceptual relationships
- Creating multi-sensory associations for enhanced recall
- Building navigable structures for knowledge retrieval
Quick Start
Create a New Palace
python scripts/palace_manager.py create "My Palace" "programming" --metaphor workshopVerification: Run python --version to verify Python environment.
List Existing Palaces
python scripts/palace_manager.py listVerification: Run python --version to verify Python environment.
View Palace Status
python scripts/palace_manager.py statusVerification: Run python --version to verify Python environment.
When To Use
- Creating knowledge structures for complex topics
- Organizing large amounts of related information
- Building persistent, project-specific memory systems
- Designing learning pathways for skill acquisition
- Structuring documentation or reference material
When NOT To Use
- Quick knowledge search
- use knowledge-locator instead
- Session-specific context - use
session-palace-builder
- Quick knowledge search
- use knowledge-locator instead
- Session-specific context - use
session-palace-builder
Architectural Templates
| Template | Best For | Key Features |
|---|---|---|
| Fortress | Security, defense, production-grade systems | Strong boundaries, layered access |
| Library | Knowledge, research, documentation | Organized shelves, categorized sections |
| Workshop | Practical skills, tools, techniques | Workbenches, tool areas, project spaces |
| Garden | Organic growth, evolving knowledge | Plots, seasons, interconnected paths |
| Observatory | Exploration, discovery, patterns | Viewing platforms, star maps, instruments |
Core Workflow
1. Analyze Domain - Identify concepts, relationships, and hierarchy 2. Design Layout - Choose metaphor and spatial organization 3. Map Associations - Create memorable imagery and connections 4. Encode Details - Add sensory attributes and ambient atmosphere 5. Validate Palace - Test recall efficiency and navigation
Detailed Resources
- Domain Analysis Guide: See
modules/domain-analysis.md - Layout Patterns: See
modules/layout-patterns.md - Sensory Encoding: See
modules/sensory-encoding.md - Validation Metrics: See
modules/validation.md - Franklin Protocol: See
modules/franklin-protocol.md- Apply the original learning algorithm to palace design
Integration
Works with:
knowledge-locator- For searching across palacessession-palace-builder- For temporary session palacesdigital-garden-cultivator- For evolving knowledge bases
Expected Outputs
- Complete palace schema with spatial coordinates
- Sensory encoding profile for each location
- Navigation guide and connection map
- Recall testing results and optimization recommendations
Troubleshooting
Common Issues
If palace creation fails, check that the metaphor argument matches one of the supported templates (Fortress, Library, Workshop, Garden, Observatory). For script errors, ensure the palace_manager.py script has executable permissions and that your Python environment meets the requirements listed in pyproject.toml.
Domain Analysis for Memory Palaces
Thorough domain analysis validates your memory palace accurately reflects the knowledge structure you're organizing.
Analysis Process
Step 1: Identify Core Concepts
- List all primary concepts in the domain
- Note the relative importance of each concept
- Identify foundational vs. advanced concepts
Step 2: Map Relationships
- Document parent-child relationships (hierarchy)
- Identify sibling concepts (same level)
- Note cross-cutting concerns that span categories
Step 3: Assess Complexity
- Rate each concept's complexity (1-5)
- Identify concepts requiring prerequisite knowledge
- Note areas with high information density
Step 4: Define Access Patterns
- How often will each concept be accessed?
- What are typical entry points?
- Which concepts are frequently accessed together?
Analysis Template
domain:
name: "Domain Name"
scope: "What this domain covers"
concepts:
- name: "Concept A"
importance: high | medium | low
complexity: 1-5
prerequisites: []
related_to: []
access_frequency: frequent | occasional | rare
relationships:
hierarchical:
- parent: "Category"
children: ["Concept A", "Concept B"]
associative:
- from: "Concept A"
to: "Concept B"
type: "complementary | sequential | contrasting"
boundaries:
included: ["topics in scope"]
excluded: ["topics out of scope"]
adjacent: ["related domains"]Best Practices
1. Start broad, then narrow - Begin with major categories before details 2. Use domain expert input - Validate your analysis with subject matter experts 3. Consider evolution - Design for how the domain might grow 4. Document uncertainties - Note areas where relationships are unclear
The Franklin Protocol for Memory Palace Design
Benjamin Franklin's 1720 writing improvement method provides a systematic approach for building effective memory palaces and acquiring any skill.
The Core Algorithm
Franklin treated skill deficiency as an engineering problem. His method:
1. Feature Extraction - Compress exemplar to essential structure 2. Deliberate Delay - Wait to prevent rote memorization 3. Reconstruction - Rebuild from compressed understanding 4. Error Calculation - Compare against original, find gaps 5. Parameter Update - Lean into errors, adjust, iterate
Applying to Memory Palace Construction
Step 1: Find Your Spectator
Identify an exemplary knowledge structure:
- Well-organized documentation
- Expert's mental model of the domain
- Existing high-quality memory palace
Step 2: Extract Features
Create "short hints" of the structure:
hints:
- "Three main districts: Core, Extensions, Ecosystem"
- "Each building maps to major category"
- "Connections follow dependency relationships"Step 3: Reconstruct from Hints
After a deliberate pause, rebuild the palace:
- Design your own layout from the hints
- Don't look at the original
- Trust your compressed understanding
Step 4: Compare and Calculate Error
Side-by-side comparison:
- What did you miss?
- Where is navigation awkward?
- Which associations are weak?
Step 5: Update and Iterate
Lean into discrepancies:
- Strengthen weak associations
- Add missing connections
- Refine sensory encoding
The ML Training Loop Parallel
| Palace Building | ML Equivalent |
|---|---|
| Study exemplar palaces | Training data collection |
| Compress to layout hints | Feature extraction |
| Design from memory | Forward pass |
| Compare to exemplar | Loss calculation |
| Refine structure | Gradient descent |
Practical Exercise
The Palace Challenge: 1. Pick a Micro-Domain: One small topic to organize 2. Find Your Spectator: One excellent knowledge structure 3. Run One Loop:
- 30 minutes designing from memory
- Compare to exemplar
- Record 3 specific differences
4. Iterate: Apply corrections, run again
Key Insight
"Mastery is not about memorization, but about building an internal generative model of a domain."
The Franklin Protocol works because it forces you to internalize patterns, not memorize content. The deliberate delay prevents overfitting to specific examples while the comparison step provides precise error signals for improvement.
Integration
Combine with:
- Validation metrics (
modules/validation.md) for structured comparison - Sensory encoding (
modules/sensory-encoding.md) for memorable associations - Layout patterns (
modules/layout-patterns.md) for structural exemplars
Layout Patterns for Memory Palaces
Effective layouts map conceptual relationships to spatial structures, making navigation intuitive.
Spatial Hierarchy
The standard hierarchy maps domain structure to architectural levels:
District (Domain)
├── Building (Major Category)
│ ├── Floor (Sub-category)
│ │ ├── Room (Concept)
│ │ │ ├── Area (Detail)
│ │ │ │ └── Object (Specific fact)Pattern Catalog
Linear Path
Best for: Sequential learning, step-by-step processes
Entry → Room 1 → Room 2 → Room 3 → Exit- Natural for tutorials and workflows
- Clear progression from start to finish
- Limited for non-linear access
Hub and Spoke
Best for: Central concept with related topics
Topic A
↑
Topic D ← HUB → Topic B
↓
Topic C- Quick access to all topics from center
- Good for reference material
- Can become crowded with many spokes
Nested Boxes
Best for: Hierarchical taxonomies
┌─────────────────────────────────┐
│ Category │
│ ┌─────────────┬─────────────┐ │
│ │ Subcategory │ Subcategory │ │
│ │ ┌───┐ ┌───┐│ ┌───┐ ┌───┐│ │
│ │ │ A │ │ B ││ │ C │ │ D ││ │
│ │ └───┘ └───┘│ └───┘ └───┘│ │
│ └─────────────┴─────────────┘ │
└─────────────────────────────────┘Network Grid
Best for: Highly interconnected domains
A ─── B ─── C
│ │ │
D ─── E ─── F
│ │ │
G ─── H ─── I- Multiple paths to any node
- Good for cross-references
- Can be disorienting without landmarks
Design Guidelines
1. Match pattern to domain structure - Linear for sequential, hub for centralized 2. Create clear landmarks - Distinctive features at key navigation points 3. Limit room count per floor - 5-7 rooms is ideal for recall 4. Design clear entry points - Users should know where to start 5. Plan for growth - Leave expansion space in your layout
Sensory Encoding for Memory Palaces
Multi-sensory encoding creates stronger memory traces by engaging multiple cognitive pathways.
Sensory Channels
Visual
- Colors - Associate concepts with distinctive colors
- Shapes - Use geometric forms for categories
- Lighting - Bright for important, dim for peripheral
- Motion - Animate key concepts for emphasis
Auditory
- Ambient sounds - Background noise for context (library quiet, workshop clanking)
- Voice associations - Mental narration or character voices
- Music - Melodies linked to concept groups
- Alerts - Distinctive sounds for warnings or importance
Spatial
- Size - Larger for more important concepts
- Position - Eye level for frequently accessed, corners for rare
- Distance - Grouped by relationship proximity
- Orientation - Facing direction indicates flow
Tactile
- Textures - Smooth for familiar, rough for challenging
- Temperature - Warm for welcoming, cool for technical
- Weight - Heavy for foundational, light for derived
Encoding Strategy
For Each Location:
1. Primary sense - The dominant sensory experience 2. Secondary sense - Supporting sensory detail 3. Trigger - The specific cue that activates recall
Example Encoding:
location: "API Documentation Room"
primary:
sense: visual
detail: "Walls covered in flowing blue diagrams"
secondary:
sense: auditory
detail: "Soft humming of data flow"
trigger: "Blue glow when entering"Best Practices
1. Make it vivid - Exaggerate sensory details for memorability 2. Use personal anchors - Connect to your own experiences 3. Maintain consistency - Same colors/sounds for same concept types 4. Create contrast - Different areas should feel distinct 5. Test recall - Verify triggers actually work for you
Memory Palace Validation
Systematic validation validates your memory palace actually works for recall and navigation.
Validation Metrics
Recall Speed
- Target: Retrieve concept location in < 5 seconds
- Method: Random concept quiz, measure time to locate
- Acceptable: 80% of concepts under target time
Navigation Efficiency
- Target: Reach any concept in ≤ 3 mental steps
- Method: Trace path from entry to random concept
- Acceptable: Average path length ≤ 3.5 steps
Association Strength
- Target: Sensory details recalled with concept
- Method: Name concept, describe its encoding
- Acceptable: 70% recall of primary sensory details
Scalability
- Target: Palace handles 2x current concepts
- Method: Mentally add new concepts, check for congestion
- Acceptable: Clear placement for hypothetical additions
Testing Protocol
Initial Validation (After Creation)
1. Walk through entire palace mentally 2. Name each room and its purpose 3. Identify any confusing areas 4. Note navigation dead-ends
Recall Testing (Weekly)
1. Select 10 random concepts 2. For each: locate in palace, describe encoding 3. Record time and accuracy 4. Identify weak spots for reinforcement
Stress Testing (Monthly)
1. Rapid-fire concept location (30 in 2 minutes) 2. Cross-reference navigation (A→B→C paths) 3. Edge case access (rarely used areas) 4. New concept placement drill
Improvement Actions
| Issue | Symptom | Solution |
|---|---|---|
| Slow recall | >5s to locate | Strengthen sensory encoding |
| Confusion | Wrong location accessed | Add distinctive landmarks |
| Dead ends | No path to concept | Add navigation connections |
| Crowding | Too many concepts per room | Split room or create sublevel |
| Forgetting | Can't recall encoding | Refresh with more vivid imagery |
Validation Checklist
- [ ] All concepts have assigned locations
- [ ] Each location has distinctive encoding
- [ ] Navigation paths connect all areas
- [ ] Entry points are clearly defined
- [ ] Growth space is available
- [ ] Recall testing passes thresholds
Related skills
FAQ
Is Memory Palace Architect safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.