mutual-dissent 0.1.1

Cross-vendor multi-model debate and consensus engine for AI response distillation

Mutual Dissent

Cross-vendor multi-model debate and consensus engine for AI response distillation.

NiceGUI web interface with live debate view, research dashboard, and full CLI research tool. Direct vendor APIs, replay, ground-truth scoring, cost tracking, and markdown export. 400+ tests across Windows and Linux CI.

Sends a user query to multiple AI models simultaneously, shares competing responses back to each model for reflection and critique, then synthesizes a final answer through a user-selected model.

How It Works

1. Fan out — Query goes to Claude, GPT, Gemini, and Grok (direct APIs or via OpenRouter)
2. Reflect — Each model sees the others' responses and argues back
3. Synthesize — A user-selected model distills the debate into a final answer
4. Log — Full debate transcript saved as structured JSON with cost and token data

Why Cross-Vendor?

Single-vendor multi-agent systems (Grok's 4-agent debate, Anthropic's agent teams) share the same training data and blind spots. Cross-vendor debate surfaces disagreements that correlated architectures can't — different training data, different safety postures, different failure modes.

Installation

git clone https://github.com/q-uestionable-AI/mutual-dissent.git
cd mutual-dissent
uv sync

Usage

# Run a debate
dissent ask "Your query here"

# With explicit panel and options
dissent ask "Your query here" --synthesizer claude --rounds 2 --panel claude,gpt,gemini
dissent ask "Summarize this" --file report.pdf
dissent replay <transcript-id> --synthesizer grok
dissent serve
dissent config test

mutual-dissent also works as the full command name.

Status

Capability	Status
Core debate loop	✅ Complete — fan-out, reflection, synthesis via OpenRouter
Provider abstraction	✅ Complete — direct Anthropic API, mixed-panel routing
CLI research tools	✅ Complete — replay, scoring, cost tracking, markdown export
Web GUI	✅ Complete — NiceGUI debate view, research dashboard, live streaming
Documentation	✅ Complete — Mintlify docs site with AI assistant and MCP server
Desktop app & batch mode	Planned — Tauri wrapper, alternative topologies, public release

Research Platform

Full debate transcripts are logged as structured JSON for research — disagreement patterns, convergence dynamics, consensus poisoning, and hallucination detection. See Research Methodology for details.

Documentation

• docs.mutual-dissent.dev — Full documentation
• Roadmap — Vision and development history
• Contributing — Development setup and workflow

License

MIT — see LICENSE for details.

Author

Richard Spicer — Security research at mlsecopslab.io