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docs: add workflow customization guide and update property schema (#2409)
- WORKFLOW_CUSTOMIZATION.md: complete user guide with examples - PROPERTY_SCHEMA.md: all 17 new workflow properties documented - README.md: workflow customization section added Closes #2368
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README.md

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@@ -44,13 +44,13 @@ Exocortex is an instrument for becoming **Übermensch** (Nietzsche):
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### What Sets Exocortex Apart
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| Traditional Tools | Exocortex |
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| ----------------- | ----------------------------------------------------- |
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| Files and folders | **Semantic graph of knowledge** |
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| Tags and links | **Ontology-driven relationships** |
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| Full-text search | **SPARQL semantic queries** |
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| AI chatbot | **SPARQL semantic queries** over your knowledge graph |
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| Data storage | **Domain model of consciousness** |
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| Traditional Tools | Exocortex |
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| ----------------- | ------------------------------------------------------- |
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| Files and folders | **Semantic graph of knowledge** |
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| Tags and links | **Ontology-driven relationships** |
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| Full-text search | **SPARQL semantic queries** |
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| AI chatbot | **Cognitive partner** working with your knowledge graph |
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| Data storage | **Domain model of consciousness** |
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### Exocortex vs Generative AI
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### Modular Ontologies
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| Module | Purpose |
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| -------------------------------- | ------------------------------------------------------------------------ |
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| **IMS** (Information Management) | Knowledge, concepts, relationships. Classes: `Concept`, `Note`, `Person` |
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| **EMS** (Effort Management) | Tasks, projects, time. Classes: `Task`, `Project`, `Meeting` |
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| **ZTLK** (Zettelkasten) | Atomic notes methodology |
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| Module | Purpose |
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| -------------------------------- | -------------------------------------------------------------------------------------- |
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| **IMS** (Information Management) | Knowledge, concepts, relationships. Classes: `Simulacrum`, `Concept`, `Note`, `Person` |
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| **EMS** (Effort Management) | Tasks, projects, time. Classes: `Task`, `Project`, `Meeting` |
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| **ZTLK** (Zettelkasten) | Atomic notes methodology |
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### STIR Model — Knowledge Coordinates
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---
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## Vision
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Exocortex encompasses 42 unique ideas for cognitive augmentation — from implemented features like the Asset knowledge model and SPARQL engine to visionary concepts like ExoEcoSystem (federated knowledge networks) and ExoProphet (prediction engine).
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**[See full vision document →](./VISION.md)** with implementation status for all 42 ideas.
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### Implemented Highlights
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- **Asset as Knowledge Quantum** — Atomic unit with UUID, class, semantic relationships
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- **Modular Ontologies** — IMS (concepts), EMS (tasks), ZTLK (notes)
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- **ExoLayout** — Flexible views over knowledge graph
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- **Local-First Architecture** — Data stays on device
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## 42 Unique IT Ideas
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The Exocortex project encompasses a comprehensive vision for cognitive augmentation. Here are the core concepts that make this system unique:
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### Core Architecture (1-10)
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| # | Idea | Description |
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| --- | ----------------------------------------- | ------------------------------------------------------------------------------------------- |
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| 1 | **Asset as Knowledge Quantum** | Atomic unit of knowledge with UUID, class, label, and semantic relationships |
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| 2 | **DCC (Direct Conceptual Communication)** | Communication without worldview conversion — semantic contract between exocortexes |
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| 3 | **ExoBlockchain** | Immutable knowledge provenance tracking — who, when, and how created each fact |
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| 4 | **ExoEcoSystem** | Federation of exocortexes forming collective intelligence network |
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| 5 | **Modular Ontology System** | IMS (concepts), EMS (tasks), ZTLK (notes), PTMS (personality), Observation (world tracking) |
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| 6 | **Simulacrum** | Digital representation of external entities (people, companies) for modeling interactions |
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| 7 | **ExoLang** | Domain-specific language for knowledge operations and transformations |
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| 8 | **Inference Engine** | Logical reasoning over knowledge graph — deriving new facts from existing |
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| 9 | **BOM (Brain Object Model)** | Inspired by DOM — programmatic access to consciousness structure |
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| 10 | **Ontological Relativity** | Each user has their own ontology, mapped to others through DCC |
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### Semantic Layer (11-20)
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| # | Idea | Description |
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| --- | -------------------------------- | ------------------------------------------------------------------------- |
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| 11 | **ExoRDF** | Extended RDF with temporal and provenance dimensions |
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| 12 | **ExoProphet** | Prediction engine based on personal patterns and knowledge graph |
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| 13 | **Braindance + IoT** | Integration with wearables (HR, glucose, location) for context enrichment |
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| 14 | **Action Tracking** | Every action becomes data — browsing, reading, communication patterns |
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| 15 | **"Not AI" Principle** | Exocortex stores verified facts; AI generates but cannot be trusted alone |
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| 16 | **ExoTag** | Semantic tags with inheritance and property propagation |
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| 17 | **Life Integration** | System becomes invisible layer over life, not separate application |
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| 18 | **Local-First Architecture** | Data stays on device, cloud is optional synchronization |
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| 19 | **IExE (Inference x Exocortex)** | Intelligence-enhanced reasoning combining human and machine cognition |
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| 20 | **ExoProtocol** | Communication standard between exocortex instances |
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### Process & Methodology (21-30)
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| # | Idea | Description |
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| --- | ---------------------------- | ----------------------------------------------------------------------------------- |
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| 21 | **Echoization** | Every external information piece gets internal representation with personal context |
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| 22 | **ExoAdapter** | Integration layer for external services (calendars, email, social) |
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| 23 | **Dynamic Naming** | Assets can have multiple names based on context and audience |
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| 24 | **Human as Execution Organ** | Exocortex plans, human executes — partnership model |
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| 25 | **Knowledge Monetization** | Verified knowledge as tradeable asset in ExoEcoSystem |
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| 26 | **Trigger System** | Automated reactions to patterns in knowledge graph changes |
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| 27 | **No Permanent Self** | Identity is emergent property of knowledge graph, not fixed entity |
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| 28 | **Breadcrumbs** | Automatic trail of attention and reasoning for later reconstruction |
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| 29 | **GTD Integration** | Getting Things Done methodology as native workflow |
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| 30 | **ExoLayout** | Flexible views over knowledge graph for different cognitive tasks |
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### Advanced Concepts (31-42)
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| # | Idea | Description |
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| --- | ---------------------------------- | ----------------------------------------------------------------------- |
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| 31 | **Property Polymorphism** | Same property behaves differently based on subject class |
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| 32 | **Life Streams** | Parallel timelines of different life aspects (work, health, learning) |
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| 33 | **Human Consciousness Schema** | Formal model of consciousness structure (perception, memory, will) |
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| 34 | **Meta-Position** | Ability to observe your own cognitive processes through the system |
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| 35 | **7 Levels of Abstraction** | From raw data to wisdom, with explicit transformations |
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| 36 | **ExoFocus** | Attention management based on goals and current context |
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| 37 | **Cognitive Load Balancing** | Automatic task distribution based on mental energy patterns |
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| 38 | **Knowledge Decay Model** | Tracking and refreshing knowledge that becomes stale |
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| 39 | **Semantic Versioning of Beliefs** | Tracking how your understanding evolves over time |
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| 40 | **ExoMirror** | Reflection interface showing patterns in your cognition |
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| 41 | **Collective Wisdom Extraction** | Aggregating insights from ExoEcoSystem while preserving privacy |
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| 42 | **Consciousness Continuity** | Exocortex as vehicle for cognitive persistence beyond biological limits |
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### Ethics & Principles
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The project adheres to core ethical principles:
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- **Human Primacy** — Technology serves human flourishing
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- **Privacy by Design** — Personal knowledge under user control
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- **Human Primacy** — Technology serves human flourishing, not replaces humanity
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- **Privacy by Design** — Personal knowledge remains under user control
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- **Transparency** — All inferences and recommendations are explainable
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- **Non-Manipulation** — System informs, never manipulates
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- **Open Standards** — Based on W3C Semantic Web standards (RDF, SPARQL, OWL)
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---
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│ ┌──────────────────┐ ┌──────────────────┐ ┌──────────────────┐ │
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│ │ Obsidian Plugin │ │ CLI │ │ Your App │ │
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│ │ (@exocortex/ │ │ (@kitelev/ │ │ (REST API │ │
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│ │ obsidian-plugin)│ │ exocortex-cli) │ │ planned) │ │
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│ │ obsidian-plugin)│ │ exocortex-cli) │ │ coming soon) │ │
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│ └────────┬─────────┘ └────────┬─────────┘ └────────┬─────────┘ │
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│ │ │ │ │
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│ └───────────────────────┼────────────────────────┘ │
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│ │ │ │
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│ │ • Domain models │ │
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│ │ • SPARQL engine │ │
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│ │ • RDFS inference │ │
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│ │ • Inference rules │ │
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│ │ • Storage adapters │ │
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│ └─────────────────────────┘ │
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│ │
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├─────────────────────────────────────────────────────────────────────────┤
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│ Infrastructure Layer │
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│ ┌─────────────┐ ┌─────────────┐ ┌─────────────────┐ │
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│ │ Markdown │ │ SPARQL │ │ RDF │ │
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│ │ Parser │ │ Engine │ │ Serializers │ │
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│ │ Markdown │ │ SPARQL │ │ N-Triples │ │
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│ │ Parser │ │ Engine │ │ Storage │ │
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│ └─────────────┘ └─────────────┘ └─────────────────┘ │
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└─────────────────────────────────────────────────────────────────────────┘
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```
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| **@exocortex/obsidian-plugin** | Private | Interactive UI: 24+ components, 6 renderers, 34+ commands, 11 modals |
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| **@kitelev/exocortex-cli** | `@kitelev/exocortex-cli` | CLI for automation, archive/unarchive, SPARQL queries, AI agent integration |
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| **@exocortex/test-utils** | Private | Shared test utilities, mock factories, flaky test reporter |
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| **physics-wasm** | Private | WebAssembly force simulation (experimental, not currently integrated) |
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| **physics-wasm** | Private | WebAssembly force simulation for 3D graph visualization |
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### Option 3: Core Library
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Best for: Building custom applications on top of Exocortex domain models.
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Best for: Building custom applications.
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```typescript
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import { SparqlService, NodeFsAdapter } from "exocortex";
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> **Note**: The core library (`exocortex`) provides domain models, SPARQL engine internals, and service interfaces. For query execution, use the CLI package (`@kitelev/exocortex-cli`) which provides a complete runtime.
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const sparql = new SparqlService(new NodeFsAdapter("/path/to/vault"));
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const results = await sparql.query(`
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SELECT ?concept ?definition
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WHERE {
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?concept exo:Instance_class ims:Concept .
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?concept ims:Concept_definition ?definition .
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}
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`);
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```
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▶ Finance
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```
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### Workflow Customization
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Define custom status lifecycles for your tasks and projects. Skip unnecessary steps, add new statuses, or create per-project workflow overrides -- all using regular vault assets:
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```bash
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# List defined workflows
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exocortex-cli workflow list --vault ~/vault
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# Validate a workflow definition
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exocortex-cli workflow validate <uid> --vault ~/vault
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```
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See **[Workflow Customization Guide](./docs/WORKFLOW_CUSTOMIZATION.md)** for step-by-step instructions and examples.
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### Ontology-Driven Forms
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Create assets with forms generated from your RDF ontology — fields appear based on `rdfs:domain`, types detected from `rdfs:range`.
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- **[SPARQL 1.2 Features](./docs/sparql/SPARQL-1.2-Features.md)** — LATERAL, PREFIX\*, directionality, and more
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- **[SPARQL 1.2 Migration](./docs/sparql/SPARQL-1.2-Migration.md)** — Upgrading from SPARQL 1.1
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### Graph View
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### Graph View & Visualization
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- **[Graph View Overview](./docs/graph-view/README.md)** — Label patching for Obsidian's built-in graph view
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- **[Configuration Reference](./docs/graph-view/guides/configuration.md)** — Configuration options for graph label display
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- **[Inference & Reasoning Guide](./docs/graph-view/guides/inference.md)** — RDFS inference and neighborhood exploration
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- **[Graph View Overview](./docs/graph-view/README.md)** — Introduction to 2D and 3D graph visualization
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- **[3D Visualization Guide](./docs/graph-view/guides/3d-visualization.md)** — WebGL-powered 3D graph exploration
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- **[Configuration Reference](./docs/graph-view/guides/configuration.md)** — All configuration options for graph views
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- **[Inference & Reasoning Guide](./docs/graph-view/guides/inference.md)** — RDFS/OWL inference, neighborhood exploration
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### Layout Code Blocks
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