Council
Council is a macOS multi-LLM deliberation app: pose one question, get blind peer-reviewed answers and a 0–100 divergence score.
Council solves a real problem most people work around by hand: juggling five chatbot tabs to compare reasoning. Blind peer review plus a divergence score is a genuinely useful lens — the dissent spotlight is the feature we'd keep coming back for. The catch is the audience: you need keys for multiple providers and a Mac, and the project is early with a small star count. If that describes you, install it; if you want one assistant, this isn't it.
Verified 15d ago · liveness 70/100 · cite: rightaichoice.com/tools/council
- Researchers and analysts cross-checking AI reasoning across multiple models before trusting a claim
- Developers weighing architecture decisions or gating CI on multi-model divergence via the council CLI
- Writers and strategists who want genuinely diverse perspectives instead of three paraphrases of one answer
- Privacy-conscious professionals using local Ollama or self-hosted endpoints with no account or telemetry
- Casual users who want a single AI assistant for everyday questions — the three-seat setup is overhead
- Anyone without API keys for at least a couple of LLM providers (Ollama or Apple Intelligence can fill seats, but you'll want real breadth)
- Windows, Linux, or mobile users — Council is a native macOS app with no web version
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Skip Council if you're not willing to build from source on macOS, don't have API keys for multiple LLM providers, or need a web/mobile/Windows solution or team collaboration features.
You'll pay each provider directly for API usage — costs vary per model and can add up fast if you run frequent councils with multiple seats.
Council is $0 — entirely free and open-source (MIT). You pay only for the AI API usage of your chosen providers. There are no tiers or upsells. Compared to subscription AI tools like ChatGPT Plus ($20/mo) or Claude Pro, Council's cost is your API usage, which can be cheaper or more expensive depending on volume. It's ideal for power users who already have API keys and want to maximize value from existing subscriptions.
In short
Council — Council is a macOS multi-LLM deliberation app: pose one question, get blind peer-reviewed answers and a 0–100 divergence score. Best for Researchers and analysts cross-checking AI reasoning across multiple models before trusting a claim, Developers weighing architecture decisions or gating CI on multi-model divergence via the council CLI, Writers and strategists who want genuinely diverse perspectives instead of three paraphrases of one answer. Free to use.
What people actually say about Council — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
104 mentions across 8 sources (Hacker News, YouTube, Product Hunt, App Store, Bluesky, Stack Overflow, GitHub, Lemmy) · researched Jun 18, 2026.
Average across the 8 sources that answered — each source counts once, not each post.
- +Solves parallel monologue by letting models critique each other blind.
- +Privacy-focused: all keys and data stay on your device.
- +Open source under MIT license for full transparency.
- +Native macOS app runs locally without server dependency.
- +Supports multiple major LLMs (Claude, GPT, Gemini, Grok).
- −App crashes frequently according to multiple App Store reviews.
- −Extremely slow and unresponsive, per user complaints.
- −Log in issues and no notification for lesson/calls.
- −Almost never works properly, many 1-star reviews.
- −Limited to macOS only, no cross-platform support.
- • No hidden costs, but API usage fees from each LLM provider apply separately.
Viability Score
How well maintained and how widely used is Council? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- Twelve LLM backends: Claude, GPT, Gemini, DeepSeek, Grok, Mistral, Perplexity, OpenRouter, Ollama, Apple Intelligence,
- Blind peer review — each advisor critiques the others' answers without knowing who wrote them
- Divergence score (0–100) showing how far apart the council landed, how many camps formed, and the outlier
- Optional bounded debate round — one rebuttal per advisor, with original answers kept underneath
- Dissent spotlight — surfaces the outlier's full answer on its own for you to judge
- Neutral chair role — a model that moderates and writes the synthesis instead of answering
- Selective deliberation — choose which answers enter peer review after reading them
- Guest seat — paste an outside answer from any AI for blind review, counted in divergence and synthesis
- Devil's Advocate role to pressure-test the consensus
- Decision journal — log decisions, set a reminder, then record how it turned out (local only)
- Vision — attach an image for models that support it
- Document attachment (.md/.txt) — the whole council reads it before weighing in, file stays out of saved history
- Calm cost estimate — running token and dollar tally with optional spend alert
- Export to Markdown, PDF, image, or a paste-ready decision memo; share councils as importable presets
- council CLI — pipe documents in, get JSON out, gate CI on divergence
About Council
Council puts one question to a panel of LLMs at once and then makes them argue. Each advisor answers independently, then critiques the others blind — no brand bias, no knowing which model wrote what. A divergence score from 0 to 100 shows how far apart the council landed, how many camps formed, and who the outlier is. The score measures agreement, not correctness, which is the honest framing most multi-model tools skip. It's built for people who already juggle API keys for several providers. Twelve backends are supported: Claude, GPT, Gemini, DeepSeek, Grok, Mistral, Perplexity, OpenRouter, Ollama for local models, Apple Intelligence on-device, plus two custom OpenAI-compatible endpoints for llama.cpp, LM Studio, or vLLM. Each of the three seats carries a persona — Analyst, Practitioner, Skeptic — so the council doesn't just produce three versions of the same answer. The workflow goes further than a side-by-side comparison. An optional debate round gives every advisor one rebuttal, with original answers tucked underneath so you can see who moved and who held. A neutral chair model can moderate and write the synthesis instead of answering. Dissent surfaces the outlier's full answer on its own. Selective deliberation lets you pick which responses even enter peer review, and you can paste an outside answer from ChatGPT or Gemini as a guest seat to be critiqued anonymously alongside the rest. Privacy is the whole architecture, not a feature: no account, no server, no telemetry, and API keys live only in the macOS Keychain. You bring your own keys and pay providers directly. A CLI brings the same engine to the terminal with JSON output and divergence gating for CI. Compared with single-chatbot workflows or manual copy-paste between tabs, Council is the structured version — but it is macOS-only and open-source (MIT), so Windows and Linux users are out of scope today.
Behind the Verdict
Most multi-model tools are just split-screen chat. Council goes a step past that by having the models read each other without knowing the author — which is the only way peer review means anything. The divergence score is the part we didn't expect to care about. Watching three models agree at 8/100 on a question you assumed was settled is worth the setup time on its own. Pick this when the question actually matters. Architecture decisions, factual claims you're about to repeat, research directions where a single model's blind spots could cost you a week. The guest seat is quietly the best feature for those moments — paste in the answer you already got from ChatGPT, and the council tells you what it thinks without knowing where it came from. Pass when the question is simple. Council has real setup cost: three seats, three keys, personas to pick. That friction pays off on hard questions and wastes your time on easy ones. A single chat window is faster for 80% of daily use. The closest alternative isn't a competitor app so much as the manual workflow — copying answers between tabs by hand. Council replaces that with a repeatable process and a number attached to it. The community forks and personae suggestions are active enough to suggest the project is being used, not just starred. What bites in practice: it's an unsigned build, so macOS won't hand the new version the old one's Keychain items. You re-enter your API keys once after each update, inline. Annoying but honest, and better than a signed build that phones home. Another caveat: divergence is a measure of disagreement, not of who's right. A high score doesn't mean the outlier is correct and the majority is wrong — it means the council split. Read the dissent before you take the number as a verdict. If you run
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Real-world workflow fit
Concrete scenarios for the personas Council actually fits — and what changes day-one when you adopt it.
Researcher loads Council, selects three backends (e.g., GPT, Claude, Gemini), pastes a draft sentence listing a factual claim, and hits Ask. Sees parallel answers, blind critiques, divergence score of 45 with two camps. Drills into dissent, reviews the outlier's answer, and logs the decision in the journal.
Outcome: Cross-checks the claim with evidence from multiple models, spots a consensus error, and avoids publishing a mistake.
Developer poses a trade-off question to the council with personas Analyst, Practitioner, Skeptic. Uses selective deliberation to only send the two contender answers into peer review. Runs a debate round and sees which advisor changes position.
Outcome: Gets a structured comparison with explicit trade-offs and a recommendation backed by multi-model reasoning.
Writer asks the council 'What are the strongest arguments for and against remote work?' and includes a guest seat with an answer from a previous AI chat. The council critiques the guest answer blindly and includes it in the divergence score.
Outcome: Produces a synthesis with distinct perspectives, identifying a minority view that becomes an article angle.
Use Cases
- Ask the same complex question to GPT-4o and Claude Sonnet, then compare blind critiques and the divergence score
- Verify factual claims by checking agreement across multiple LLMs before publishing or acting
- Identify model-specific biases in generated text by catching outliers and dissent
- Generate diverse solution approaches for coding problems, then let the council critique each approach
- Log high-stakes decisions in the journal and track whether the consensus was right
- Paste an existing answer from any AI into the guest seat to have it blind-reviewed
Models Under the Hood
as of 2026-09-22
Limitations
- Council is a native macOS app that requires you to bring your own API keys for at least two providers to get meaningful divergence.
- It's macOS-only and requires building from source — there's no ready-to-install binary.
- No multi-user collaboration; the journal is single-user local.
- No web or mobile version.
- Some features like Apple Intelligence need macOS 26 and Apple Silicon.
as of 2026-08-29
Verification history
We have re-verified Council 11 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 11 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Council tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free (MIT open source)
$0
Where the pricing makes sense
The company stage and team size where Council's pricing actually pencils out — and where peers do it cheaper.
Council is $0 — entirely free and open-source (MIT). You pay only for the AI API usage of your chosen providers. There are no tiers or upsells. Compared to subscription AI tools like ChatGPT Plus ($20/mo) or Claude Pro, Council's cost is your API usage, which can be cheaper or more expensive depending on volume. It's ideal for power users who already have API keys and want to maximize value from existing subscriptions.
Setup time & first value
How long it actually takes to get something useful out of Council — broken out by persona, not the marketing-page minute.
For a developer familiar with Xcode: build from source in ~10-20 minutes, then configure API keys in the app (5-10 minutes). First council can run within the hour. For a non-developer: expect longer, possibly an hour or more if you need to set up Xcode and manage API keys. Overall, plan for 30-60 minutes to get a working council with three backends.
Switching to or from Council
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From NotebookLM: Paste existing generated answers into guest seats for blind peer review.
- →From ChatGPT Plus: Use your OpenAI API key and paste ChatGPT outputs as guest seats.
- ↗To a custom script: Export council results to JSON via CLI and feed into your own pipeline.
- ↗To another multi-model tool like ChatLLM: Export Markdown/PDF from Council and import manually.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Council”, and we withheld 6: 6 could not be judged, because “Council” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Council.
Official links
Tools that pair well with Council
Common stack mates teams adopt alongside Council, with the specific reason each pairing earns its keep.
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Typli.ai
Typli.ai packs 187 AI writing tools, AI image generation, and multi-model AI chat into one credit-based subscription.
xeditai
Multi-model AI workspace merging ChatGPT, Notion, and Gamma into one editable canvas.
Featured Head-to-Head Comparisons
Council vs Praktika
Praktika and Council serve completely different needs. If you want to improve your spoken language skills through AI conversation partners, Praktika is the clear choice. If you need to cross-check outputs from multiple large language models to reduce bias and make better decisions, Council’s free, open-source macOS app is unmatched. Choose based on your primary goal: language learning vs. multi-model validation.
Council vs Spider Cloud
Spider Cloud and Council serve entirely different needs. Spider Cloud is for developers and AI agents that need fast, low-cost web data extraction; its new Browser AI commands and scraper catalog are recent game-changers. Council is for macOS users who want to reduce AI bias by comparing multiple LLMs side-by-side with blind reviews. Buy Spider Cloud if you need structured web data at scale; choose Council if you want to verify LLM outputs.
Council vs Push Security
These tools address completely different problems. Choose Push Security if you're a security or identity team fighting AI-powered phishing, session hijacking, and data leaks from employee AI use. Choose Council if you're a researcher or developer who wants to reduce single-LLM bias by comparing and reviewing answers from multiple models on macOS. There's no overlap — your use case determines the pick.
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Frequently Asked Questions
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