Strands Evaluation is a powerful framework for evaluating AI agents and LLM applications. From simple output validation to complex multi-agent interaction analysis, trajectory evaluation, and automated experiment generation, Strands Evaluation provides comprehensive tools to measure and improve your AI systems.
Feature Overview
- Multiple Evaluation Types: Output evaluation, trajectory analysis, tool usage assessment, and interaction evaluation
- LLM-as-a-Judge: Built-in evaluators using language models for sophisticated assessment with structured scoring
- Trace-based Evaluation: Analyze agent behavior through OpenTelemetry execution traces
- Automated Experiment Generation: Generate comprehensive test suites from context descriptions
- Custom Evaluators: Extensible framework for domain-specific evaluation logic
- Experiment Management: Save, load, and version your evaluation experiments with JSON serialization
- Built-in Scoring Tools: Helper functions for exact, in-order, and any-order trajectory matching
- Simulators: Enable multi-turn evaluation of conversational agents by generating realistic interaction patterns that adapt based on agent responses to create authentic evaluation scenarios