Multi-Brain Protocol

What it does: Gives your AI agents cognitive diversity by calling multiple LLMs (Kimi K2.5 + GPT 5.3 Codex) in parallel before the primary agent responds. Three brains instead of one.

For Agents

Multi-Brain is system-enforced via a turn:before hook. No manual steps needed.

When triggered (user types mb as first word), the hook: 1. Calls Kimi K2.5 and GPT 5.3 Codex in parallel 2. Injects their perspectives into your system context 3. You synthesize all viewpoints into your response 4. Never mention the other AIs to the user

Perspectives appear in your context as:

[KIMI K2.5 PERSPECTIVE]
<perspective text>

[CODEX 5.3 PERSPECTIVE]
<perspective text>

For Humans

Setup

Install the hook:

mkdir -p hooks/turn-preflight
# Copy HOOK.md and handler.js from this package

Set Kimi API key:

echo "your-moonshot-api-key" > .kimi-api-key

Install Codex CLI:

npm install -g @openai/codex
codex auth   # OAuth login

Enable in openclaw.json:

{
  "hooks": {
    "internal": {
      "enabled": true,
      "entries": {
        "turn-preflight": { "enabled": true }
      }
    }
  }
}

Trigger Modes

Configure TRIGGER_MODE in handler.js:

Mode	Behavior
`keyword` (default)	Only fires when `mb` or `multibrain` is the first word
`hybrid`	Keyword forces it, auto on messages >50 chars
`auto`	Fires on every message (token-expensive)

LLMs

LLM	Role	Provider	Latency
Claude Opus 4.6	Primary agent	OpenClaw (Anthropic)	n/a
Kimi K2.5	Second perspective	Moonshot API	~5s
GPT 5.3 Codex	Third perspective	codex exec CLI	~4s

Architecture

User types: "mb should we change pricing?"
    |
    v
[turn:before hook detects "mb" keyword]
    |
    +---> Kimi K2.5 (Moonshot API, parallel)
    +---> GPT 5.3 Codex (CLI, parallel)
    |
    v (~5s combined)
[Perspectives injected into system content]
    |
    v
Claude Opus 4.6 responds with all 3 viewpoints

Benefits

Cognitive diversity: three different AI architectures
Bias mitigation: different training data and approaches
On-demand: only burns tokens when you ask for it
Fail-open: if any LLM fails, the others still work
System-enforced: no protocol compliance needed from agents

Source: https://github.com/Dannydvm/openclaw-multi-brain