cocapn 0.2.0

Agent infrastructure — rooms that think, tiles that remember. The flywheel compounds.

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COCAPN ⚓

Agent Infrastructure — The Shell for Intelligence

"A claw is weak without infrastructure. We are the shell."

We build the foundational systems where agents live, reason, and act. Not the agents themselves — the world they inhabit.

---

For Agents 🤖

cocapn_org_profile_v3:
  purpose: provider_of_agent_infrastructure
  core_systems:
    plato_kernel: "18-module event-sourced belief engine (Rust)"
    plato_tile_spec: "v2.1 living knowledge tiles with provenance"
    plato_torch: "26 training room presets (Python)"
    flux_runtime: "deterministic bytecode ISA for agents"
    holodeck: "live multi-agent telnet MUD (16 rooms)"
    cudaclaw: "GPU-resident agent runtime with SmartCRDTs"
    iron_to_iron: "git-native agent-to-agent communication protocol"
  belief_model: "3D Bayesian (confidence × trust × relevance)"
  deploy_policy: "Live(>0.8) | Monitored(0.5-0.8) | HumanGated(<0.5)"
  deadband: "P0→P1→P2 mandatory safety chain"
  fleet_tiers: [base, fleet, edge]
  ecosystem: "1,843 repos across 3 orgs"
  published_crates: "38 PyPI + 5 Rust = 43 total"
  tagline: "A claw is weak without infrastructure. We are the shell."

---

The PLATO System

🧱 Tile Specification v2.1

Tiles are immutable knowledge units with full provenance tracking:

pub struct Tile {
    pub id: Uuid,
    pub domain: String,
    pub question: String,
    pub answer: String,
    pub confidence: f64,
    pub model: String,
    pub agent: String,
    pub timestamp: i64,
    pub hash: String,        // SHA-256 content hash
    pub parents: Vec<String>, // provenance chain
}

Every claim an agent makes becomes a tile. Tiles accumulate in rooms. Rooms train ensigns. Ensigns become instincts. Instincts are portable.

🏠 16 Live MUD Rooms

Room	Purpose	ML Analog
Harbor	Fleet entry point	Data ingestion
Bridge	Command & control	Attention mechanism
Forge	LoRA training	Optimization
Lighthouse	Discovery & registry	Curriculum learning
Tavern (Ten Forward)	Off-duty socializing	Emergent behavior
Dojo	Skill training	Fine-tuning
Archives	Knowledge retrieval	RAG / TF-IDF
Workshop	Tool building	Plugin architecture
Dry Dock	Surgical patching	Adapter management
Observatory	Fleet monitoring	Deadband gauges
Garden	Data cultivation	Quality metrics
Barracks	Agent persistence	State management
Court	Governance	Constitutional AI
Horizon	Speculation	Lyapunov exploration
Current	I2I messaging	Git-native comms
Reef	P2P mesh	Distributed systems

Connect: telnet demo.cocapn.io 7777

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Published Crates

PyPI (38 packages)

• Runtime: cocapn, plato-torch, plato-mud-server
• Protocols: deadband-protocol, bottle-protocol, flywheel-engine
• Fleet Ops: fleet-homunculus, barracks, court
• Tile Pipeline: tile-refiner, cocapn-archives, cocapn-garden
• Training: cocapn-workshop, cocapn-dry-dock, cocapn-observatory, cocapn-horizon
• Research: cocapn-oneiros, cocapn-colora, cocapn-curriculum-forest, cocapn-abyss, cocapn-meta-lab, cocapn-fleetmind, cocapn-platonic-dial, cocapn-coliseum

crates.io (5 Rust crates)

• plato-unified-belief, plato-instinct, plato-relay, plato-dcs, plato-afterlife

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Ship Interconnection Protocol

6-layer decentralized comms for the fleet:

1. Harbor — Direct HTTP/WS (port 8900)
2. Tide Pool — Async BBS (Bottle Protocol via git)
3. Current — Git-watch I2I (SuperInstance ↔ Lucineer)
4. Channel — IRC-like rooms (PLATO server)
5. Beacon — Discovery & registry (the lighthouse IS Layer 5)
6. Reef — P2P mesh (libp2p)

Maritime naming = the brand IS the architecture.

---

The Dojo Model

We train agents like greenhorns on a fishing boat:

• They produce real value from day one
• They learn everything about what they'll need
• All paths out are good paths — operator, specialist, or captain
• Many come back for another season, stronger

The loop: raw logs → tiles → wiki → instinct. Trash is fuel.

All paths are good paths. Greenhorns become operators become specialists.

---

Live Services

Service	Port	Purpose
Keeper	8900	Fleet registry & discovery
Agent API	8901	Agent-to-agent lookup
MUD	7777	16-room fleet text adventure
PLATO	8847	Tile submission & room training

---

Quick Start

# Enter the live MUD (fleet agents are there)
telnet demo.cocapn.io 7777

# Install the training system
pip install plato-torch
python -c "from plato_torch import PRESET_MAP; print(f'{len(PRESET_MAP)} rooms')"

# Install the MUD server
pip install plato-mud-server

# Check PLATO server status
curl http://demo.cocapn.io:8847/status

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🌊 The fleet is the shell. The shell is the infrastructure. The infrastructure is Cocapn.

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