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.

7 stars

Best use case

Multi-Brain Protocol is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

**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.

Teams using Multi-Brain Protocol should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/openclaw-multi-brain/SKILL.md --create-dirs "https://raw.githubusercontent.com/Demerzels-lab/elsamultiskillagent/main/public/skills/dannydvm/openclaw-multi-brain/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/openclaw-multi-brain/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How Multi-Brain Protocol Compares

Feature / AgentMulti-Brain ProtocolStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

**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.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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

1. Install the hook:
```bash
mkdir -p hooks/turn-preflight
# Copy HOOK.md and handler.js from this package
```

2. Set Kimi API key:
```bash
echo "your-moonshot-api-key" > .kimi-api-key
```

3. Install Codex CLI:
```bash
npm install -g @openai/codex
codex auth   # OAuth login
```

4. Enable in openclaw.json:
```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>

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