Ai Evaluation Evals

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by oldwinter · vlatest · Repository

Evaluates AI model outputs against provided criteria, offering detailed scores and actionable improvement suggestions.

Install on your platform

We auto-selected Claude Code based on this skill’s supported platforms.

1

Run in terminal (recommended)

terminal
claude mcp add ai-evaluation-evals npx -- -y @trustedskills/ai-evaluation-evals
2

Or manually add to ~/.claude/settings.json

~/.claude/settings.json
{
  "mcpServers": {
    "ai-evaluation-evals": {
      "command": "npx",
      "args": [
        "-y",
        "@trustedskills/ai-evaluation-evals"
      ]
    }
  }
}

Requires Claude Code (claude CLI). Run claude --version to verify your install.

About This Skill

What it does

This skill provides structured evaluation capabilities for AI agents. It allows users to define criteria and scoring rubrics, then receive feedback on agent performance based on those parameters. The tool aims to provide a more objective and consistent assessment of AI agent behavior than simple subjective impressions.

When to use it

  • Assessing chatbot responses: Evaluate the helpfulness, accuracy, and safety of a chatbot's replies in various scenarios.
  • Measuring code generation quality: Score generated code based on functionality, efficiency, and readability.
  • Evaluating creative writing outputs: Assess stories or poems for creativity, coherence, and adherence to specific prompts.
  • Comparing different AI agent versions: Systematically compare the performance of multiple AI agents against a common evaluation framework.

Key capabilities

  • Define custom evaluation criteria.
  • Create scoring rubrics with detailed descriptions.
  • Receive structured feedback on agent outputs.
  • Facilitate objective assessment of AI agent behavior.

Example prompts

  • "Evaluate this chatbot response: [response text] using the 'Helpfulness and Accuracy' rubric."
  • "Score this generated Python code: [code snippet] based on the 'Efficiency and Readability' criteria."
  • "Compare the outputs of Agent A and Agent B for the prompt '[prompt]' according to the defined evaluation framework."

Tips & gotchas

The quality of the evaluations depends heavily on well-defined criteria and rubrics. Take time to create clear, specific scoring guidelines for best results.

Tags

🛡️

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Details

Version
vlatest
License
Author
oldwinter
Installs
10

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Passed automated security scans.