llm-council

LLM Council Skill

A Claude skill that enables collaborative brainstorming with multiple AI models (ChatGPT and Gemini) before presenting implementation plans.

What It Does

When you ask Claude to consult with other AI models, Claude will:

1. Query both ChatGPT and Gemini for their perspectives
2. Analyze their responses and identify valuable insights
3. Synthesize a comprehensive implementation plan incorporating ideas from all three models
4. Present the final plan with attribution to each model's contributions

How to Use

Simply ask Claude to consult with other AI models using phrases like:

• "Consult the council: How should I architect a microservices system?"
• "Ask ChatGPT and Gemini what they think about my database design"
• "Get perspectives from other AI models on this technical decision"
• "Consult with other LLMs: What's the best approach for..."

Example:

User: Consult the council: How should I structure my React app for scalability?

Claude will then:
- Query ChatGPT and Gemini about React architecture
- Analyze their suggestions on components, state management, and organization
- Present a synthesized plan incorporating insights from all three models

Installation

1. Install the skill in Claude by uploading the llm-council.skill file
2. Set up API keys and model preferences:
   • Copy .env.template to create a .env file in your working directory
   • Add your OpenAI API key (get it at https://platform.openai.com/api-keys)
   • Add your Gemini API key (get it at https://aistudio.google.com/app/apikey)
   • Optionally customize which models to use (see Model Options below)

Model Options

Default Models (Fast & Cost-Effective):

• ChatGPT: gpt-5-nano-2025-08-07 (highly cost-effective)
• Gemini: gemini-3-flash-preview (balanced speed and intelligence)

Upgrade Options for Better Collaboration:

OpenAI models (ordered by capability):

• gpt-5-nano - Fastest, cheapest version of GPT-5. It's great for summarization and classification tasks. (Default)
• gpt-5-mini - Balanced cost and quality
• gpt-5.2 - Smart model, capable of most tasks
• gpt-5.2-pro - State-of-the-art for professional knowledge work

Gemini models (ordered by capability):

• gemini-2.5-flash-lite - Ultra-fast, optimized for throughput
• gemini-2.5-flash - Best price-performance
• gemini-3-flash-preview - Balanced (default)
• gemini-3-pro-preview - Most intelligent, best reasoning

How to Configure: Add these lines to your .env file:

OPENAI_MODEL=gpt-5-nano
GEMINI_MODEL=gemini-3-flash-preview

Recommended Configurations:

• Balanced: Defaults (gpt-5-nano + gemini-3-flash-preview)
• Budget: gpt-5-nano + gemini-2.5-flash
• High Quality: gpt-5 + gemini-3-flash-preview
• Premium Reasoning: gpt-5.2 + gemini-3-pro-preview
• Professional Work: gpt-5.2-pro + gemini-3-pro-preview

Benefits

• Diverse perspectives: Get insights from three different AI models with different training and capabilities
• Better decisions: Identify potential issues or alternatives you might have missed with a single model
• Comprehensive planning: Combine strengths of multiple models for more robust implementation plans

API Costs

Both OpenAI and Gemini APIs have usage costs that vary significantly by model:

OpenAI Cost Tiers (approximate, check current pricing):

Budget Tier:

• gpt-5-nano: Very low cost per token

Standard Tier:

• gpt-5-mini: Moderate cost

Premium Tier:

• gpt-5.2: Higher cost per token
• gpt-5.2-pro: Highest cost for professional work

Gemini Cost Tiers (approximate, check current pricing):

Budget Tier:

• gemini-2.5-flash-lite: Very low cost, optimized for throughput
• gemini-2.5-flash: Low cost, best price-performance

Standard Tier:

• gemini-3-flash-preview: Moderate cost (default)

Premium Tier:

• gemini-3-pro-preview: Higher cost for advanced reasoning

Cost Management Tips:

• Start with default models for routine brainstorming (very cost-effective)
• Use mid-tier models (gpt-5-mini + gemini-3-flash-preview) for balanced quality/cost
• Upgrade to premium models only for critical architectural decisions or complex reasoning tasks
• Set usage limits in your API dashboards (OpenAI Platform and Google AI Studio)
• Consider setting monthly budgets to avoid surprises
• Monitor your usage patterns and adjust model choices accordingly

Note: Each /council command makes 2 API calls (one to ChatGPT, one to Gemini), so total cost is the sum of both models' pricing.

Skill Structure

llm-council/
├── SKILL.md                    # Main skill instructions
├── scripts/
│   └── query_llms.py          # Python script that queries both APIs
└── references/
    └── setup.md               # Detailed setup instructions

Troubleshooting

"API key not found" error: Make sure your .env file is in the current working directory with the correct keys.

API timeout: The script has a 30-second timeout per API. If an API is slow or down, it will show an error but continue with the other model's response.

One API fails: Claude will note which model's perspective is unavailable and proceed with the available responses.