Demerzels-lab 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:
- Calls Kimi K2.5 and GPT 5.3 Codex in parallel
- Injects their perspectives into your system context
- You synthesize all viewpoints into your response
- 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