SUBIT‑64 — Semantic Layer for AI Agents

Universal Canon for Structured Reasoning, Archetypal Modeling, and Multi‑Layer Agent Behavior

SUBIT‑64 is a semantic layer for AI agents built on a 64‑state archetypal ontology, shadow axes, content topology mapping, and the MIST reasoning engine.
It provides agents with a structured thinking model, behavioral masks, state dynamics, semantic topology, and a canonical interpreter that ensures predictable, controllable, and extensible behavior.

SUBIT‑64 is not just a framework — it is a universal semantic infrastructure for building agents, multi‑agent systems, and reasoning modules across platforms.

✨ Key Features

• 64‑State Archetypal Ontology — a universal language of behavior and meaning
• Shadow Axes — deep polarities that create tension and dimensionality
• MIST Reasoning Layer — stabilized, structured reasoning cycles
• Content Topology Engine — topological mapping of semantic space
• Behavioral Masks — modular filters for style, role, and agent behavior
• SUBIT Interpreter — canonical runtime for reasoning and state transitions
• SDK (Python / JS) — ready‑to‑use integration tools
• Multi‑Agent Patterns — negotiation, coordination, role systems
• Tools & Validators — archetype validation, topology generation, state visualization

📦 Repository Structure

subit-64/
├── README.md
├── LICENSE
├── CHANGELOG.md
├── ROADMAP.md
├── CONTRIBUTING.md
│
├── whitepaper/
├── spec/
├── interpreter/
├── sdk/
├── agents/
├── docs/
├── tools/
└── branding/

whitepaper/

Official theoretical foundation: architecture, semantic layer, diagrams.

spec/

Canonical documents: ontology, shadow axes, topology, masks, integration principles.

interpreter/

Runtime core: system prompt, MIST engine, topology mapper, state logic, API chain.

sdk/

Python and JS SDKs, examples, templates.

agents/

Personas, multi‑agent systems, example agents.

docs/

Overview, architecture, data flow, glossary, FAQ, diagrams.

tools/

Validators, generators, utilities, state visualizers.

branding/

Pitch, narrative, deck outline, logo.

🚀 Quick Start

Python

pip install subit64

from subit_interpreter import SUBITInterpreter

agent = SUBITInterpreter(persona="strategist")
response = agent.run("How should we approach market entry?")
print(response)

JavaScript

import { SUBITInterpreter } from "./sdk/js/subit_interpreter.js";

const agent = new SUBITInterpreter({ persona: "analyst" });
agent.run("Evaluate the risks.").then(console.log);

🧠 SUBIT‑64 Architecture

SUBIT‑64 consists of four primary layers:

1. Archetypal Layer (64 states)
   The foundational language of behavior and meaning.

2. Shadow Axes
   Deep polarities that create tension and dimensionality.

3. MIST Reasoning Layer
   A stabilized reasoning engine with structured steps.

4. Content Topology Layer
   A topological map of semantic space.

Together, these form the Semantic Layer, integrable into any AI agent or multi‑agent system.

🧩 Use Cases

SUBIT‑64 is ideal for:

• AI agents (personal, enterprise, research)
• Multi‑agent systems
• Reasoning engines
• Behavioral interpreters
• Semantic interfaces
• Products requiring structured, predictable reasoning
• Architectures where thinking structure matters more than raw text generation

📚 Documentation

Full documentation is available in /docs/:

• overview.md
• architecture.md
• data-flow.md
• glossary.md
• faq.md

🤝 Contributing

SUBIT‑64 is a canonical system.
Contributions are welcome but must follow the principles defined in:

• CONTRIBUTING.md
• spec/canonical-definition.md
• spec/integration-principles.md

📅 Roadmap

See ROADMAP.md for upcoming milestones:

• Semantic Layer v1.0
• Full SDK
• Multi‑Agent Pack
• Visualization Suite
• SUBIT‑64 Cloud Playground

📄 License

MIT License.