agent-evaluation

Agent benchmarking evaluates framework performance by running standardized tasks through agents/benchmark.py. This process invokes ComparativeEvaluator to parse results and present standardized metrics in a table, solving the problem of manually comparing agent performance across different frameworks.

Automating agent evaluation pipelines involves executing agents/benchmark.py to run end-to-end tests across agents like AutoGen and CrewAI. The workflow aggregates scores, parses results, and presents standardized metrics in a table, streamlining the evaluation process for VibeTeam workflows.

Yes, you can generate tabular reports comparing AutoGen, CrewAI, and OpenHands performance. The agent-evaluation workflow parses benchmark results from agents/benchmark.py and presents standardized metrics, feedback, and recommendations in a structured table format.

Yes, the VibeTeam benchmarking workflow supports performance scoring and feedback generation. It executes benchmarks using agents/benchmark.py and compiles results to include scores, feedback, and recommendations for evaluated agents like AutoGen, CrewAI, and OpenHands.

ComparativeEvaluator in agents/benchmark.py works by executing standardized benchmark tasks across specified agents. It parses the results from these end-to-end evaluations and presents standardized metrics in a table for direct comparison of frameworks like AutoGen, CrewAI, and OpenHands.