OmniCouncil – Zero-API-cost local MoA desktop app for Mac

A local-first Mixture-of-Agents desktop app for macOS. Ask Claude, Gemini and Codex at once. They answer independently or debate, and a Judge model returns one verdict with a measured consensus score.

Important

OmniCouncil drives the vendors' official CLIs (claude, codex, agy) non-interactively, signed in with your own accounts. Requests count against your plan's usage limits, and each provider's terms for this kind of use differ and can change. Check the terms of every provider you connect before using OmniCouncil.

Different models get different things wrong. Asking several models and having a strong model judge the results can catch mistakes that one model alone would miss — and makes disagreement visible instead of hiding it behind one confident answer.

• 🔌 No separate API keys or per-token billing. Every model call goes through an official CLI using the subscription sign-in you already have. API keys are removed from each CLI's environment (env_unset ), so a call is never silently billed to an API account instead.
• ⚖️ Two modes: Judge and Co-work - Judge Mode: workers answer in parallel without seeing each other. The Judge receives the answersanonymized and shuffled , and returns a structured verdict with aconsensus score (1.0 🟢 / 0.5 🟡 / 0 🔴 ) and a confidence level. Low confidenceor zero consensus triggers asecond review by a model from a different vendor .
  • Co-work Mode: a multi-round discussion. Each round, every worker sees the other (anonymous) participants' answers and revises, adds to or keeps its own. If the Leader still finds a dispute, it issues guidance and the discussion gets extra rounds.
• 🖥️ Native macOS GUI. A dark, minimal PySide6 app: the final answer is the main body of each reply, with every agent's raw answer, timing and the Judge's analysis folded away until you open them. Saved history, follow-up questions with context, attachments and voice notes, an English/Chinese interface and a global hotkey (⌘⇧J ).

| Warm process pool | Persistent CLI processes skip cold starts (31–36% faster end to end in our tests). Sessions are reset between runs, so questions never share context. | | Honest consensus | With only one usable answer, the UI says "Insufficient quorum · not cross-validated" instead of showing a perfect score. | | Prompt-injection hygiene | Worker answers and attachment text are passed to the Judge as length-capped, clearly delimited untrusted data . | | Multimodal input | Images, PDFs, text and voice notes. The Leader turns them into text first; workers only see plain text. | | Per-worker models | Switch any worker between fast and heavy models (e.g. Haiku ↔ Opus) from a dropdown. | | Account & usage dashboard | Sign-in status, 5-hour / 7-day usage, rate-limit alerts, and a log-in / switch-account button per provider. | | Terminal CLI | Everything also runs from the terminal ( omnicouncil ask … ). |

llm-council popularized this idea: models answer, review each other's answers anonymously, and a Chairman model writes the final answer. OmniCouncil takes a different route on a few points:

flowchart LR
    U([User]) -->|question · files · voice| GUI["Desktop GUI<br/>omnicouncil.gui<br/>PySide6 + qasync"]
    T([Terminal]) --> TCLI["Terminal CLI<br/>omnicouncil.cli<br/>Typer + Rich"]

    GUI --> E
    TCLI --> E

    subgraph E["Engine (output-free, event-driven)"]
        direction TB
        PRE["multimodal<br/>Leader reads attachments"]
        CTX["orchestrate<br/>context injection"]
        ORC{"Mode"}
        PRE --> CTX --> ORC
    end

    ORC -->|Judge: parallel| W
    ORC -->|Co-work: N rounds,<br/>anonymous peers| W

    subgraph W["CLI Workers · subscription logins"]
        direction TB
        W1["claude"]
        W2["agy · Gemini"]
        W3["codex"]
    end

    POOL[("pool<br/>persistent processes")] -.-> W1
    W -->|answers| BL["blind + bounded<br/>untrusted data"]
    BL --> J["Judge / Leader<br/>JSON verdict + consensus"]
    J -->|low confidence<br/>or no consensus| R["Second review (other vendor)<br/>or extra Co-work round"]
    R --> V
    J --> V["Final verdict"]
    V --> GUI
    V --> DB[("SQLite<br/>data/history.sqlite")]

Every model call is a local subprocess, argv only (never through a shell), with its own timeout. Workers that fail (for example at a usage limit) are dropped from later rounds without blocking the others. Closing the app terminates every child process.

Does asking several models and judging the results actually help? A first pilot on 20 randomly sampled MMLU-Pro questions (10-option multiple choice, graded by exact match; workers: Claude Code default model, Gemini 3.8 Flash, Codex gpt-5.6-sol; Judge: Claude Opus):

What it suggests:

• The council fixed both questions the Judge model got wrong on its own. On one, all three workers agreed on the right answer and the Judge followed them. On the other, no worker was right and they disagreed completely (consensus 0); that triggered the different-vendor second review, which reached the correct answer on its own.
• The Judge beat a plain majority vote 3 times and never overturned a correct majority. Once it sided with a correct minority answer against two agreeing workers.
• It costs time and calls: ~4 model calls and ~26 s per question versus one call and a few seconds. Co-work was slower still and no more accurate here.

This is a pilot, not proof: with 20 questions every confidence interval overlaps, and one sample is no substitute for hundreds of questions across domains. Full results: evals/pilot-2026-10/. Reproduce or extend it (uses your subscription quota):

python evals/run_eval.py --n 200 --cowork 50
python evals/run_eval.py --augment evals/results/<run>/results.jsonl   # add a "Judge model alone" baseline

macOS (the GUI, global hotkey and voice recording use macOS APIs; tested on macOS 15). #

Python 3.9+ (3.11+ recommended — 3.9 is past end-of-life). #

At least one of these CLIs , installed and signed in with your subscription:Provider CLI Sign in Anthropic Claude Code ·claude`` claude auth loginOpenAI Codex CLI · codex``codex login Google Antigravity CLI ·agy run agy once and follow the promptsAgents whose CLI is missing are skipped automatically. Two signed-in CLIs are enough to compare answers.

With pipx (recommended — isolated, adds the omnicouncil and omnicouncil-gui commands):

pipx install git+https://github.com/OmniCouncil/OmniCouncil.git
omnicouncil-gui

From a clone (for development):

git clone https://github.com/OmniCouncil/OmniCouncil.git
cd OmniCouncil
python3 -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
python gui.py            # or: omnicouncil-gui

As a macOS app (built locally with Briefcase):

pip install briefcase
briefcase build macOS                    # → build/omnicouncil/macos/app/OmniCouncil.app (~465 MB)
briefcase package macOS --adhoc-sign     # → a .dmg in dist/

The app is ad-hoc signed, not notarized: the first time, right-click it and choose Open. Launched from Finder, it picks up your login shell's PATH, so it finds the CLIs just like a terminal would.

On first launch, config.json is created from the bundled template. Installed via pipx, OmniCouncil keeps its files in ~/Library/Application Support/OmniCouncil; run from a clone, it uses ./config.json and ./data. OMNICOUNCIL_HOME overrides both.

• Type a question and press Enter (Shift+Enter for a new line).
• The settings panel chooses the mode, the workers, each worker's model, the Leader, and the second-review / extend-discussion option.
• 📎 attaches files and 🎤 records a voice note; the Leader reads them before the workers start.
• Click Process on any reply to see each agent's raw answer, timing, the Judge's analysis and which anonymous label was which model.
• ⌘⇧J brings the window to the front from anywhere.

omnicouncil ask "Which is larger, 9.11 or 9.9?"               # Judge Mode
omnicouncil ask -m cowork -r 3 "Is a tomato a fruit?"          # Co-work Mode, 3 rounds
omnicouncil ask -l "Gemini 3.1 Pro" "..."                      # pick the Leader
omnicouncil ask --model Claude=haiku -v "..."                  # override a model, print commands
omnicouncil ask -f invoice.png "What is the total due?"        # attachments
omnicouncil config --show                                      # agents, models, install status

(From a clone without installing, use python main.py instead of omnicouncil.)

Every enabled worker answers on its own, in parallel. 2. The Judge receives the answers anonymized ("Assistant A/B/…") and in random order , each inside<answer> tags that the prompt declares untrusted. It returns JSON:{"consensus_score": 1.0 | 0.5 | 0 | null, "confidence": "...", "analysis": "...", "final_answer": "..."}Score Meaning 1.0 🟢Every agent's core answer is the same 0.5 🟡A majority agrees, but at least one answer is clearly different 0 🔴No majority; the answers all differ — Only one answer: insufficient quorum, not cross-validatedMalformed output is still parsed: from code fences, by matching braces, or with regex fallbacks. 3. If confidence is Low , or the answers showno consensus (score 0), a reviewer from adifferent vendor is picked automatically, and its verdict replaces the first.

1. Round 1: independent answers.
2. Rounds 2–N: each worker gets the question, its own previous answer and the other participants' answers under anonymous, per-run-stable labels, and revises, adds to or keeps its answer.
3. Leader summary (blind, like the Judge). If confidence is still Low or there is no consensus, the Leader's dispute guidance becomes the focus of another round, up tocowork_max_rounds .

config.json controls everything. Main fields:

Custom prompts: every prompt is an editable file in omnicouncil/prompts/ (<name>.<lang>.md). To change one, copy it to <OMNICOUNCIL_HOME>/prompts/ with the same name and edit the copy; it overrides the built-in version.

• OmniCouncil has no backend and stores its own data locally — history, attachments, recordings and the usage cache live indata/ (or~/Library/Application Support/OmniCouncil/data ).
• Your prompts, conversation context and attachment contents are still sent to the model providers you select , through their CLIs, under those providers' privacy terms. Local storage does not mean the data never leaves your machine.
• No credential files are read: account status comes from each CLI's own status command.
• Claude-based workers and Leaders get no file or memory tools — only the read-only web tools when web search is on. Only attachment pre-processing enables the Read tool, limited to the attachment folder.
• With web search on, search queries are sent to the provider's search service as well.

See SECURITY.md for the threat model and how to report a vulnerability.

• Microphone (voice notes): the first recording asks for permission for the app you launch OmniCouncil from (Terminal, iTerm, VS Code…). If it doesn't ask, or recordings are silent:System Settings → Privacy & Security → Microphone , enable that app, and restart it.
• Global hotkey: uses CarbonRegisterEventHotKey , which needs no Accessibility permission. If the combination is taken, choose another inconfig.json .

pip install -e ".[dev]"
pytest                    # ~100 tests, all with fake CLIs — no model calls, no quota
python -m pyflakes omnicouncil tests
omnicouncil/
  orchestrate.py   Judge mode, blind answer formatting, context injection, reviewer choice
  cowork.py        Co-work mode
  multimodal.py    attachment pre-processing
  pool.py          warm pool (stream-json persistent processes)
  runner.py        one model call: pool or one-shot subprocess, structured-output adapters
  parsing.py       verdict parsing with fallbacks
  prompts.py       prompt  (prompts/*.md, user overrides)
  config.py        config , validation, migration
  storage.py       SQLite history (schema v2)
  accounts.py      account status, usage limits, login helpers
  cli.py           terminal CLI · cli_render.py  rich rendering
  gui.py           desktop app · hotkey.py  global hotkey · i18n.py  UI strings
evals/run_eval.py  accuracy / latency / cost evaluation
tests/             pytest suite

See CONTRIBUTING.md before opening a pull request.

• Depends on the CLIs: their flags and output formats can change between versions; usage counts against your plan's limits. Respect each provider's terms of service.
• Uneven pool support:codex has no stable persistent mode, so it always runs one-shot.
• macOS only for now.

MIT © 2026 OmniCouncil