OpenClaw Integration

How b1e55ed connects to the operator layer.

Two-Layer Architecture

b1e55ed is an engine, not an interface. It processes signals, runs brain cycles, and generates trade intents. But it doesn’t handle conversation, curation, or operator interaction directly. That’s the operator layer’s job.

┌─────────────────────────────────────────────┐
│            OPERATOR LAYER                    │
│                                             │
│   Chat ─── Curation ─── Control ─── Alerts  │
│                                             │
│   OpenClaw / Custom Agent / Direct API      │
└──────────────────┬──────────────────────────┘
                   │  Events + API
                   ▼
┌─────────────────────────────────────────────┐
│            b1e55ed ENGINE                    │
│                                             │
│   Producers → Brain → Conviction → Execution│
│                                             │
│   Event Store ─── Learning Loop ─── Audit   │
└─────────────────────────────────────────────┘

b1e55ed is designed to run under OpenClaw as a sovereign trading agent — but any system that speaks HTTP and emits events can serve as the operator layer.

Integration Points

1. Curator Pipeline (Operator → Engine)

The curator producer accepts structured signals from the operator layer. This is how human intelligence enters the system. Via CLI:

b1e55ed signal "Whale cluster accumulating SOL — 3 wallets, $2M+ in 48h" \
  --symbols SOL --direction bullish --conviction 7

Via API:

POST /api/v1/signals/submit
{
  "event_type": "signal.curator.v1",
  "node_id": "your-node-id",
  "source": "operator:telegram",
  "payload": {
    "symbol": "SOL",
    "direction": "bullish",
    "conviction": 7.0,
    "rationale": "Whale cluster accumulating"
  }
}

See: curator.md.

2. Brain Control (Operator → Engine)

# Trigger brain cycle
POST /api/v1/brain/run

# Check status
GET /api/v1/brain/status

3. Alerts (Engine → Operator)

The engine emits alert events. The operator layer decides how to deliver them.

Alert	Event Type	Urgency
Stop hit	`alert.stop_triggered`	Immediate
Target reached	`alert.target_hit`	Immediate
Kill switch escalation	`alert.kill_switch`	Immediate
Regime change	`alert.regime_shift`	Standard
Learning loop update	`alert.weights_adjusted`	Low

Subscribe via SSE stream: GET /api/v1/events/stream?domain=alert

4. Agent Interfaces

Agents connect via SSE stream or MCP server.

# Real-time event feed
GET /api/v1/events/stream

# MCP tool calls
POST /api/v1/mcp

# Producer provenance (no auth)
GET /api/v1/oracle/producers/{id}/provenance

See: agent-interfaces.md.

5. Dashboard (Passive Monitoring)

The web dashboard at localhost:5051 provides real-time visualization. It reads the same event store — no special integration needed.

Component Status

Component	Status
REST API	✅ Live
Dashboard	✅ Live
Event store	✅ Live
Curator endpoint	✅ Live
SSE event stream	✅ Live (`GET /api/v1/events/stream`)
MCP server	✅ Live (`POST /api/v1/mcp`)
Signal attribution	✅ Live
Oracle endpoint	✅ Live (public, no auth)
Provenance check MCP tool	✅ Live
OpenClaw skill package	⬜ Planned
Alert → chat routing	⬜ Planned

Integration Patterns

Pattern 1: Headless (API Only)

Your Code → HTTP → b1e55ed API → Brain → Events

No operator layer. Direct API calls. Good for backtesting, CI pipelines, or embedding b1e55ed in a larger system.

Pattern 2: Agent-Operated (OpenClaw)

Chat → OpenClaw → b1e55ed API → Brain → Events → OpenClaw → Chat

Full conversational loop. Drop alpha, get alerts, control the system through natural language.

Pattern 3: Multi-Agent

Agent A (Research) → Curator API ──┐
Agent B (On-chain) → Curator API ──┤→ Brain → Conviction → Execution
Agent C (Social)   → Curator API ──┘
         Operator  → Control API ──→ Override / Kill Switch

Multiple agents feeding signals. One operator with kill switch authority. The compound learning loop benefits from every participant.

Operator Workspace

If you’re running a b1e55ed instance with OpenClaw, use the operator template:

GitHub template: P-U-C/b1e55ed-operator-template — fork and fill in 3 files
ClawHub skill: clawhub install b1e55ed-operator — auto-installs to your workspace
Skills repo: P-U-C/openclaw-skills

Getting Started

Setup

Producers

Operations

Features

Integrations

API Reference

Contributing

Reference

OpenClaw Integration

OpenClaw Integration

Two-Layer Architecture

Integration Points

1. Curator Pipeline (Operator → Engine)

2. Brain Control (Operator → Engine)

3. Alerts (Engine → Operator)

4. Agent Interfaces

5. Dashboard (Passive Monitoring)

Component Status

Integration Patterns

Pattern 1: Headless (API Only)

Pattern 2: Agent-Operated (OpenClaw)

Pattern 3: Multi-Agent

Operator Workspace

​OpenClaw Integration

​Two-Layer Architecture

​Integration Points

​1. Curator Pipeline (Operator → Engine)

​2. Brain Control (Operator → Engine)

​3. Alerts (Engine → Operator)

​4. Agent Interfaces

​5. Dashboard (Passive Monitoring)

​Component Status

​Integration Patterns

​Pattern 1: Headless (API Only)

​Pattern 2: Agent-Operated (OpenClaw)

​Pattern 3: Multi-Agent

​Operator Workspace

OpenClaw Integration

Two-Layer Architecture

Integration Points

1. Curator Pipeline (Operator → Engine)

2. Brain Control (Operator → Engine)

3. Alerts (Engine → Operator)

4. Agent Interfaces

5. Dashboard (Passive Monitoring)

Component Status

Integration Patterns

Pattern 1: Headless (API Only)

Pattern 2: Agent-Operated (OpenClaw)

Pattern 3: Multi-Agent

Operator Workspace