| name | temple-generator |
| description | Generate a 3D interactive knowledge map (Inner Temple) from any Obsidian vault or document set. Supports multi-scale abstraction layers and dual-graph common maps between two vaults. |
| trigger | /temple-generate |
| args | vault_path [--compare vault_path_2] [--output path] [--inline] |
| user_invocable | true |
Temple Generator
Generate a 3D interactive knowledge visualization from any Obsidian vault. The output is a single HTML file (Three.js) with concentric entity rings, audio, discovery mechanics, and multi-scale semantic zoom.
When to Use
- User wants to visualize any Obsidian vault as a 3D knowledge map
- User wants to compare two vaults/document sets visually
- User wants to regenerate the temple from scratch with fresh vault analysis
Architecture
Two-part system:
- Generation pipeline (this skill): discovers structure, names it, scores confidence, exports a scene package
- Runtime renderer (template): handles navigation, transitions, audio, discovery
Pre-generate meaning. Runtime-render experience.
Workflow
Step 1: Scan the Vault
Run python3 ~/.claude/skills/temple-generator/scripts/extract_entities.py <vault_path>.
This produces vault-scan.json with:
- Files: path, title, tags, outgoing links, backlink counts, word count, folder, frontmatter
- Graph: adjacency list with bidirectional link counts
- Centrality: degree centrality per node
- Clusters: detected groups of tightly linked notes
Step 2: Read the Scan + Sample Notes
- Read
vault-scan.json
- Read the top ~20 nodes by centrality (first 100 lines each)
- Read
references/classification-guide.md for entity type heuristics
- Read 3-5 representative notes to calibrate the vault's "voice" (formal/informal, domain jargon, language)
Step 3: Classify Entities
Using references/classification-guide.md, assign each significant node to an entity type. Maintain two vocabularies:
- canonical: neutral labels for portability (
anxiety-management, fermentation-process)
- poetic: mythic/art labels for the installation (
The Ferment Gate, The Cortisol Throne)
Target counts per type (adjust for vault size):
| Type | Small vault (< 100) | Medium (100-500) | Large (500+) |
|---|
| Gods | 2-3 | 3-5 | 5-7 |
| Demigods | 3-7 | 5-12 | 8-15 |
| Tensions | 2-4 | 3-7 | 5-9 |
| Narratives | 2-5 | 5-10 | 8-12 |
| Blind spots | 1-3 | 3-5 | 4-7 |
| Spirits | 1-3 | 3-5 | 3-5 |
| Research | 5-15 | 10-25 | 15-30 |
| Values | 2-5 | 3-8 | 5-10 |
| Trails | 2-5 | 3-8 | 5-10 |
| Questions | 3-6 | 5-10 | 8-12 |
| Depths | 2-5 | 5-10 | 8-15 |
| Crystals | 1-3 | 2-5 | 3-6 |
Step 4: Build Abstraction Levels
Levels are confidence-gated — only include a level if the vault supports it.
Level 0 — Entities (always exists): individual nodes with positions, connections, descriptions.
Level 1 — Domains (requires >= 3 meaningful clusters): groups of related entities. Each domain has:
canonical + poetic name- member entity keys
- centroid position (weighted average of member positions)
- representative exemplar (most central member)
- description (1-2 sentences in vault voice)
- confidence score (0-1)
Level 2 — Axes (requires >= 2 interpretable opposing pairs): fundamental tensions. Each axis has:
- two poles with names and descriptions
- member domains per pole
- axis description
- confidence score
Level 3 — Comparison (requires two vaults + sufficient alignment): shared/unique analysis.
Read references/merge-algorithm.md for dual-graph logic.
Step 5: Generate Scene Package
Follow the schema in references/entity-schema.md to produce temple-data.json.
Include:
entities: all classified nodeslevels: abstraction layers with zoom thresholdsmappings: entity → domain → axis crosswalkscomparison: (if dual-graph) shared/unique/alignment dataaudio: motif hints per type and levelstyle: poetic vocabulary, intro text, color palette, layer definitionsconfidence: per-abstraction and per-alignment scores
Step 6: Generate HTML
- Copy
~/.claude/skills/temple-generator/assets/temple-template.html to the output location
- If
--inline flag: embed the JSON data as const TEMPLE_DATA = {...}; inside the HTML
- Otherwise: place
temple-data.json alongside the HTML
Step 7: Report
Show the user:
- Entity counts by type
- Abstraction levels generated (with confidence scores)
- Top 5 gods/central entities
- Detected tensions
- If dual-graph: overlap percentage and shared domains
Dual-Graph Mode
When --compare vault_path_2 is provided:
- Scan both vaults independently (Step 1)
- Classify entities for each vault (Steps 2-3)
- Run merge algorithm from
references/merge-algorithm.md
- Generate merged scene package with source attribution
- Template renders shared scaffold with divergence offsets
Quality Guidelines
- Skip trivial notes (daily todos, admin logs, empty stubs)
- Prefer nodes that reveal the vault's actual concerns, not its filing system
- Write in the vault's own voice, calibrated from sample notes
- If a level lacks confidence, omit it rather than fabricating structure
- Each abstraction level must be backed by membership weights, exemplars, and provenance
- "The abstraction hierarchy should be semantic, not just geometric"
Audio Guidance for Template
The template's audio system should respect hierarchical continuity across zoom levels:
- L0 (close): localized, identity-rich — entity whispers and textures
- L1 (medium): regional harmonic beds, cluster pulses
- L2 (far): sparse drones, tension-based tonal movement
- L3 (comparison): stereo/dialogic between two vault voices
Zoom should feel like changing resolution, not changing universes. Motifs relate across scales.
