Elrond
Orchestrates a multi-agent system to provide hierarchical LLM critique and synthesis for enhanced decision-making and idea evaluation.
Acerca de
Elrond implements a multi-agent thinking augmentation system that analyzes proposals through three specialized critique perspectives: positive, neutral, and negative. By leveraging multiple LLM agents (Gemini 2.5 Flash for critiques and Gemini 2.5 Pro for synthesis), it overcomes single-model biases and synthesizes comprehensive, actionable insights. This approach ensures more thorough analysis of complex ideas, offering a robust framework for evaluating proposals, identifying consensus, and guiding next steps.
Características Principales
- MCP Compliance for seamless integration with AI assistants
- Structured Responses using Pydantic models for reliable outputs
- Google AI Integration with Gemini 2.5 Flash and Pro models
- Parallel Critique Analysis from multiple specialized agents
- Comprehensive Analysis covering feasibility, risks, benefits, and stakeholder impact
- 0 GitHub stars
Casos de Uso
- Analyze project proposals, strategies, or ideas through multi-perspective critique
- Enhance decision-making by synthesizing diverse LLM perspectives on complex topics
- Integrate advanced thinking augmentation capabilities with AI assistants like Claude Desktop
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