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Bedrock Agentcore Evaluations

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adaptationio·vlatest·ai-ml

This skill assesses LLM outputs using AgentCore's framework, providing structured evaluations for improved reasoning and alignment.

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This skill no longer installs under the name bedrock-agentcore-evaluations. adaptationio/skrillz is deleted or private, so it cannot be installed from.

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adaptationio

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About this skill

What it does

This skill provides evaluation capabilities for Bedrock agents. It allows you to assess agent performance based on predefined metrics and criteria, providing feedback loops for improvement. The evaluations can be used to track progress, identify areas of weakness, and optimize agent behavior over time.

When to use it

  • Debugging Agent Behavior: Use this skill when an agent is not performing as expected to pinpoint the root cause through structured evaluation.
  • Measuring Improvement: Track changes made to an agent's configuration or tools by evaluating its performance before and after modifications.
  • Benchmarking Different Agents: Compare the effectiveness of multiple agents on a standardized set of tasks using consistent evaluation criteria.
  • Training Data Generation: Use evaluations to identify scenarios where the agent struggles, creating targeted training data for refinement.

Key capabilities

  • Evaluation metric definition
  • Performance tracking
  • Agent feedback loops
  • Standardized task assessment

Example prompts

  • "Evaluate the agent's response to this user query: 'Summarize the key findings of this research paper.'"
  • "Run a performance evaluation on the agent using the 'customer service resolution rate' metric."
  • "Compare the agent’s performance on Task A versus Task B, and provide a detailed report."

Tips & gotchas

This skill requires careful definition of evaluation metrics to ensure accurate and meaningful results. Ensure that your evaluation criteria are aligned with the desired agent behavior and objectives.