Agentic Eval Multi-Participant Coordination
What it is
An evaluation framework for assessing AI agents in multi-participant coordination tasks. It utilizes LangGraph for orchestration, custom MCP tools for interaction, and LLM-as-a-Judge for automated scoring.
The problem it solves
Lack of standardized, automated evaluation methods for complex multi-agent coordination tasks.
What you could use it for
- Evaluating the performance of LLM agents in collaborative scenarios
- Benchmarking multi-agent systems on coordination challenges
- Researching the effectiveness of LLM-based judging in agent evaluation
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