·bedrock-agentcore-evaluations
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bedrock-agentcore-evaluations

adaptationio/skrillz

Amazon Bedrock AgentCore Evaluations for testing and monitoring AI agent quality. 13 built-in evaluators plus custom LLM-as-Judge patterns. Use when testing agents, monitoring production quality, setting up alerts, or validating agent behavior.

17Installs·0Trend·@adaptationio

Installation

$npx skills add https://github.com/adaptationio/skrillz --skill bedrock-agentcore-evaluations

SKILL.md

AgentCore Evaluations transforms agent testing from "vibes-based" to metric-based quality assurance. Test agents before production, then continuously monitor live interactions using 13 built-in evaluators and custom scoring systems.

Purpose: Ensure AI agents meet quality, safety, and effectiveness standards

| # | Evaluator | Purpose | Score Range |

Amazon Bedrock AgentCore Evaluations for testing and monitoring AI agent quality. 13 built-in evaluators plus custom LLM-as-Judge patterns. Use when testing agents, monitoring production quality, setting up alerts, or validating agent behavior. Source: adaptationio/skrillz.

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Install command
npx skills add https://github.com/adaptationio/skrillz --skill bedrock-agentcore-evaluations
Category
</>Dev Tools
Verified
First Seen
2026-02-01
Updated
2026-02-18

Quick answers

What is bedrock-agentcore-evaluations?

Amazon Bedrock AgentCore Evaluations for testing and monitoring AI agent quality. 13 built-in evaluators plus custom LLM-as-Judge patterns. Use when testing agents, monitoring production quality, setting up alerts, or validating agent behavior. Source: adaptationio/skrillz.

How do I install bedrock-agentcore-evaluations?

Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/adaptationio/skrillz --skill bedrock-agentcore-evaluations Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor

Where is the source repository?

https://github.com/adaptationio/skrillz