Ensemble — AI skill for Claude Code

🗳️ Ensemble

*Multi-model consensus debate via the filesystem — LLMs propose, peer-review, rebut, vote, and synthesize a group-confirmed answer. CLI + MCP.*

    

**Multi-round: propose → peer-review → rebut → vote → synthesize → converge.** Not a one-shot poll — an auditable debate that runs until the models agree on a *specific answer* (or provably can't), with every step left on disk.

Multi-model consensus debate via the filesystem. Several top LLMs (OpenAI, Anthropic, DeepSeek) independently **propose**, **review** each other, **rebut** the critiques of their own proposal, and **vote** — and, once a majority agrees, **synthesize** a single merged answer that the group **confirms**. They never talk to each other directly: every contribution is a file in a shared folder, and a coordinator advances the debate phase by phase. Participants are **anonymized** to each other (shown only as "Participant A/B/C"), so they judge arguments on merit, not on brand.

%%{init: {'theme':'neutral', 'themeVariables': {'fontSize':'22px'}, 'flowchart': {'nodeSpacing': 55, 'rankSpacing': 70, 'padding': 16}}}%%
flowchart LR
    P[PROPOSING] --> R[REVIEWING] --> B[REBUTTAL] --> V{VOTING}
    V -- "revise / split
(positions still moving)" --> P
    V -- "stable disagreement
or safety fuse" --> D["Best-effort answer
(plurality, Borda-broken tie)"]
    V -- "majority finalize" --> S["SYNTHESIS
endorsed author merges
(minority views kept)"]
    S --> C{"CONFIRM
APPROVE majority?"}
    C -- yes --> A1["Synthesis = consensus answer"]
    C -- "no / stall / error" --> A2["Verbatim winning proposal
(today's