Agent Evaluation
Evaluates agent performance based on provided metrics, offering actionable insights for improvement and optimization.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add dokhacgiakhoa-agent-evaluation npx -- -y @trustedskills/dokhacgiakhoa-agent-evaluation
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"dokhacgiakhoa-agent-evaluation": {
"command": "npx",
"args": [
"-y",
"@trustedskills/dokhacgiakhoa-agent-evaluation"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The agent-evaluation skill allows you to assess and provide feedback on the performance of AI agents. It can analyze agent responses, identify areas for improvement, and generate reports summarizing its findings. This helps refine agent behavior and ensure they meet desired objectives.
When to use it
- Evaluating a newly trained agent before deployment to production.
- Identifying weaknesses in an existing agent's performance on specific tasks.
- Comparing the effectiveness of different agent configurations or training datasets.
- Generating reports for stakeholders demonstrating agent progress and areas needing attention.
Key capabilities
- Response analysis
- Performance reporting
- Identification of improvement areas
- Agent feedback generation
Example prompts
- "Evaluate this agent's response to the prompt: 'Write a short story about a cat.'"
- "Generate a report on the agent’s performance in summarizing news articles."
- "Identify any biases present in the agent's responses regarding [topic]."
Tips & gotchas
The quality of the evaluation depends heavily on the clarity and specificity of your prompts. Providing detailed instructions or example outputs can significantly improve the accuracy and usefulness of the feedback generated by this skill.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
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Passed automated security scans.