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Streamlines the process of building robust testing frameworks for AI agents by automating the creation of AgentV evaluation files. It enables developers to define complex test cases with multi-role conversation threads, integrate file-based inputs, and configure sophisticated validation logic using either programmatic code scripts or LLM-based judges. This skill ensures consistency across agent benchmarks and helps optimize performance through systematic, schema-validated evaluation workflows that support sequential evaluator chaining.
