council
Consult a multi LLM council for deliberation, debate, voting, critique, or verification. Uses GPT 5.4, Gemini 2.5, and Claude as peers.
16 stars
Best use case
council is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Consult a multi LLM council for deliberation, debate, voting, critique, or verification. Uses GPT 5.4, Gemini 2.5, and Claude as peers.
Teams using council should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
How council Compares
| Feature / Agent | council | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Consult a multi LLM council for deliberation, debate, voting, critique, or verification. Uses GPT 5.4, Gemini 2.5, and Claude as peers.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# LLM Council Skill You have access to the LLM Council MCP tools. Use them to orchestrate multimodel deliberation. ## Available Tools 1. **council_deliberate**. Full council deliberation with configurable protocol 2. **council_vote**. Quick voting: all models answer, then anonymously rank each other 3. **council_debate**. Structured debate with adaptive stopping 4. **council_critique**. Peer critique or adversarial redteaming 5. **council_verify**. Multi agent verification of an answer 6. **council_estimate_cost**. Estimate cost before running 7. **council_status**. Check which providers are available 8. **council_configure**. Update default council composition ## Usage Patterns ### Quick consensus Use `council_vote` for straightforward questions where you want the best answer selected by peer review. ### Deep analysis Use `council_debate` with `adaptiveStop: true` for complex questions that benefit from iterative refinement. Set `maxRounds: 3` for thorough analysis. ### Verification Use `council_verify` to check if an answer is correct by having multiple models independently verify it. ### Stress testing Use `council_critique` with `redTeam: true` to find flaws, edge cases, and failure modes in responses. ### Full deliberation Use `council_deliberate` with `protocol: "synthesize"` for the chairman synthesis pattern. All models answer, then a chairman produces an authoritative synthesis. ## Best Practices (from research) * Scale agents (more models), not rounds (more debate turns) * Heterogeneous models (mix providers) outperform homogeneous ones * Anonymous peer review prevents model favoritism bias * Always check cost estimate before large council runs * Default council (GPT 5.4 + Gemini 2.5 Pro + Claude Sonnet 4.6) provides optimal diversity ## Example Invocations User: "What are the tradeoffs of microservices vs monolith?" → Use council_vote for quick consensus User: "Is this algorithm correct? [code]" → Use council_verify User: "Debate whether Rust or Go is better for this use case" → Use council_debate with maxRounds: 2 User: "Red team this API design" → Use council_critique with redTeam: true
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