ftm-council-chat

Multi-model AI debate works by coordinating Claude, Codex, and Gemini agents in a browser chatroom with parallel-turn execution and a local SQLite-backed history, enabling persistent context carryover so all three peers remember previous discussion rounds before surfacing a final verdict.

Capturing a consensus verdict from multiple AI agents is handled by a structured wrap-up flow that performs auto-consensus checks and generates a formal verdict export, preserving the final decision result suitable for archiving after the live debate concludes.

Multi-model orchestration stores conversation memory using a local SQLite-backed database, enabling context carryover and summarization across rounds so AI peers maintain persistent history and coherent topic exploration throughout the live debate session.

Yes, you can use Claude, Codex, and Gemini together for live topic exploration; this Skill orchestrates all three as distinct personas in a single chatroom to discuss topics, check consensus, and preserve results in a shareable summary.

You need a local SQLite-backed history for AI chat orchestration when your use case requires persistent conversation memory across rounds, context carryover for summarization, and a formal verdict export for archiving live debates and decision capture sessions.