## 🎯 Core Purpose Create a compact, explainable, cross-domain system for identifying and classifying concepts, systems, and objects based on meaning. - 32 binary traits across 4 semantic layers: - **Physical** - **Functional** - **Abstract** - **Social** - Each trait is discrete, minimal, and precisely defined - Entities are encoded as a **32-bit semantic fingerprint** --- ## 🧠 Semantic Reasoning Goals Replace opaque or ad hoc classification systems with a trait-based model that is: - Transparent - Compressible - Cross-domain - Computable ### Features: - Bitwise comparison (Hamming distance) - Trait clustering and deltas - Meaning-preserving abstraction --- ## 🛠️ Tooling Objectives Equip users to generate, read, and manipulate UHT codes with clarity and agency: - **HexLens** – real-time encoder/decoder - **Hex Challenge** – trait literacy game - **Trait glyphs** – consistent visual identity - Color-coded trait layers and tooltips --- ## 📦 Corpus Development Standardize a set of real-world, symbolic, and abstract entities: - ✅ Initial set: 64 encoded entities - 📈 Target set: 256+ with trait justifications and images - Each entry includes: - `hex code` - Trait list - Description - Image (optional) - Domain + difficulty (optional) --- ## 🌐 Application Domains - ✅ Systems Engineering (SysML-style trait parts list) - ✅ Graph Ontology (Neo4j or RDF) - ✅ Semantic Web & Explainable AI - ✅ Trait-aligned LLM prompting - ✅ Education & Cognitive Tools - ✅ Worldbuilding, culture, fiction --- ## 🧭 Vision Summary **UHT is a universal, cross-domain, human-readable semantic framework** — encoding _what something is_ in a minimal, interoperable, and transparent way. Its goal is to become a **semantic backbone** for design, reasoning, learning, and alignment in both human and machine systems.