What is the LLM Council skill?

It is an extension for Claude Code that runs a 'council' of multiple models (such as GPT-4, Gemini, and Claude) to draft, critique, and validate code and architectural decisions.

Do I need multiple API keys to use Council?

While you can use individual keys for OpenAI and Google, the recommended setup is a single OpenRouter API key, which provides access to all models through one interface.

How does the adversarial critique work?

The skill runs specialized 'critic' agents that analyze drafts from other models to find bugs, security flaws, or architectural weaknesses before a final 'synthesizer' merges the best elements into a final result.

Is this skill suitable for small bug fixes?

Council is best suited for high-stakes or complex tasks. For single-line fixes or simple questions, using Claude's native capabilities is faster and more cost-effective.

Does Council support security standards?

Yes, its critic agent in security mode is specifically designed to identify vulnerabilities and map them to CWE (Common Weakness Enumeration) IDs.

LLM Council

Name: LLM Council
Author: sherifkozman

bysherifkozman

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Security & Testing

Orchestrates a multi-LLM consensus system for high-stakes code implementation, security auditing, and architectural design.

About

The Council skill enables Claude to act as an orchestrator for a multi-model development pipeline, utilizing parallel drafting, adversarial critique, and validated synthesis. By leveraging diverse models like GPT-4, Gemini, and Claude in tandem via the the-llm-council framework, it ensures production-grade results through rigorous cross-validation. This skill is indispensable for complex architectural decisions, security-sensitive code reviews with CWE identification, and robust feature implementations where accuracy, safety, and multiple perspectives are paramount.

Key Features

Multi-LLM adversarial debate and cross-validation for high-accuracy outputs
Unified orchestration via OpenRouter or direct provider SDKs (OpenAI, Google, Anthropic)
Structured JSON output support for seamless integration into CI/CD and dev workflows
13 GitHub stars
Automated code reviews with CWE security vulnerability identification
Specialized subagents for implementation, architecture, testing, and research

Use Cases

Synthesizing complex architectural decisions across multiple reasoning models
Performing deep security audits on authentication and authorization logic
Generating high-coverage test suites through multi-model validation and drafting

About

Key Features

Multi-LLM adversarial debate and cross-validation for high-accuracy outputs
Unified orchestration via OpenRouter or direct provider SDKs (OpenAI, Google, Anthropic)
Structured JSON output support for seamless integration into CI/CD and dev workflows
13 GitHub stars
Automated code reviews with CWE security vulnerability identification
Specialized subagents for implementation, architecture, testing, and research

Use Cases

Synthesizing complex architectural decisions across multiple reasoning models
Performing deep security audits on authentication and authorization logic
Generating high-coverage test suites through multi-model validation and drafting