Cube Protocol

An AI automation and multi-agent reasoning framework designed by Phil Hills.

Why Cube Protocol?

Traditional LLM messaging is verbose, lossy, and slow. Cube Protocol solves this by introducing a compressed representation layer with explicit semantics, fingerprinting, and multi-channel payloads optimized for agent-to-agent collaboration.

Core Components

Blueprint Encoding: Structured representation of agent intent and metadata.
Multi-Channel Payload: Parallel compressed vectors for instructions, memory, and context.
Packet Fingerprinting: Integrity checking and source verification.
Semantic Compression: Reduces token usage while preserving meaning.

Example Cube Packet

{
  "cube_version": "1.0",
  "intent": "summarize",
  "payload": {
    "compressed_vectors": ["v0x91f2", "v0x22c1"],
    "context_hash": "a82c11d9fe1b"
  },
  "fingerprint": "fp_9932_ab12"
}

Implementation

Cube Protocol is implemented across multiple languages including TypeScript, Python, and Rust. Companion libraries handle encoding, decoding, compression, and packet verification.

Project Status

Cube Protocol is actively evolving with new compression layers, multi-agent routing logic, and an expanding test suite.