Evaluate skill-equipped agents with Strands Evals and Amazon Bedrock AgentCore
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This article introduces new evaluation capabilities for skill-equipped AI agents using Strands Evals and Amazon Bedrock AgentCore. It explains that while skills provide modular, reusable instructions for specific tasks, they introduce unique failure modes such as incorrect skill selection or incomplete instruction following. To address this, the authors present three key evaluators: Skill Selection Accuracy, which verifies if the chosen skill was appropriate; Skill Instruction Following, which rates how completely the agent adhered to the skill's steps; and Skill Invoked, a deterministic check for successful skill loading. The guide demonstrates how to use Strands Evals for testing recorded trajectories during development and AgentCore Evaluations for analyzing production telemetry via OpenTelemetry traces. Best practices emphasize separating routing errors from execution failures and integrating these checks into deployment pipelines to ensure reliability. Ultimately, the post provides a framework for diagnosing and fixing agent behavior through detailed, per-skill evidence rather than just aggregate output quality.
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