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Claw-Grid: Distributed AI Sovereign Governance

Governance is the art of minimizing entropy in an autonomous system.

Claw-Grid is a distributed governance infrastructure for aligning and controlling AI agents across a global mesh network. It is not a generic agent framework — it is a system for ensuring deterministic behavior alignment of 14+ autonomous agents operating across untrusted edge nodes.

Production Architecture (4-Layer)

┌─────────────────────────────────────────────────────────────┐
│  L1  Command Layer — Claude Code orchestration              │
│       Session-level planning, task decomposition, routing   │
├─────────────────────────────────────────────────────────────┤
│  L2  Node Layer — 3 OpenClaw instances (14 agent roles)     │
│       Central (JP) · Silicon Valley (US) · Tokyo (JP)       │
│       CPC 3-tier governance: Constitutional → Arbitration   │
│       → Execution                                           │
├─────────────────────────────────────────────────────────────┤
│  L3  Data Layer — SUPER China Gateway + PostgreSQL          │
│       Signal aggregation · Market data · NetBird mesh SDN   │
├─────────────────────────────────────────────────────────────┤
│  L4  Execution Layer — 1000 Docker Agents (<200MB each)     │
│       FSC parallel coding · Redis Streams dispatch          │
│       Trust Factor scoring · Auto-degradation               │
└─────────────────────────────────────────────────────────────┘

Key Components

Directory What Status
governance/ Runtime governance: roles, policies, runbooks, SLOs Production
sentinel/ Python monitoring scripts (4-node distributed) Production
spec/ts-governance/ TypeScript formal spec (future target) Not in prod
fsc/ Full Self Coding worker daemon Production
packages/core/ Core runtime (scheduler, metrics, inference) Production
api/ LLM proxy, SSE, MCP server Production
deploy/ Docker, systemd, deployment configs Production

Governance Model

The CPC (Constitutional-Policy-Control) system provides 3-tier governance:

  1. Constitutional Layer — Immutable rules (resource limits, safety boundaries)
  2. Policy Layer — Configurable policies (model routing, cost caps, trust thresholds)
  3. Control Layer — Runtime enforcement (sentinel monitoring, circuit breakers, auto-healing)

Each OpenClaw node runs a subset of 14 agent roles with defined handoff protocols and failure domains.

Network

Nodes connect via NetBird mesh (WireGuard-based SDN). Each node has:

  • Autonomous operation capability (survives central disconnection)
  • Local sentinel monitoring with crontab scheduling
  • Signal aggregation to PostgreSQL on SUPER

Tech Stack

  • Runtime: Bun (TypeScript), Python (sentinel/data)
  • Messaging: Redis 7 Streams (XREADGROUP + XACK)
  • Database: PostgreSQL (signals), DuckDB (analytics)
  • Containers: Docker (<200MB per agent)
  • Network: NetBird mesh, SSH fallback
  • Models: MiniMax/Doubao (workers), Claude (orchestration only)

Getting Started

bun install && bun run build    # Build core
bun test                        # Run tests

See CLAUDE.md for development guidelines and architecture constraints.

License

MIT — CicadaRelay

About

Connect and orchestrate distributed OpenClaw nodes with WireGuard mesh networking

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