evaluation

Automate benchmarking evaluations for intelligent agents with standardized test cases and scoring reports.

3|Updated Jul 9, 2026

Search Tags:#testing #benchmarking #reporting #data analytics #agent evaluation

Ready to run

npx skills add https://github.com/jixu-ai/metisai --skill evaluation-jixu-ai

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: evaluation
Source: https://github.com/jixu-ai/metisai/tree/main/skills/evaluation
Command: npx skills add https://github.com/jixu-ai/metisai --skill evaluation-jixu-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires read, write, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

The evaluation Skill addresses the need for a streamlined, standardized process for assessing the performance of intelligent agents.

Core Features & Use Cases

Standardized Test Suite Creation: Generate test cases and scoring criteria to evaluate agent performance.
Evaluation Execution: Execute the tests, grade responses, and generate a comprehensive scoring report.
Use Case: Utilize this Skill to create a benchmarking tool for assessing the capabilities of a custom-built intelligent agent across a defined set of tasks.

Quick Start

Create a new evaluation by running 'evaluation create' to define the test set and scoring criteria, followed by 'evaluation run' to execute the test suite on a specified agent.

Frequently Asked Questions about evaluation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate agent evaluation and benchmarking?▼

Automating agent evaluation involves generating standardized test cases, executing them against your agent, and grading responses to compile a comprehensive scoring report. This streamlines benchmarking intelligent agents across defined tasks.

What is a standardized test suite for intelligent agents?▼

A standardized test suite for intelligent agents is a collection of generated test cases and scoring criteria used to assess performance. It provides a consistent benchmarking environment to grade agent responses across defined tasks.

Do I need a specific environment to run agent benchmarking tests?▼

Yes, you need a structured test environment to execute agent benchmarking tests. The evaluation Skill requires this setup to properly generate test cases, run evaluations, and compile scoring reports.

Can I generate custom scoring criteria for data analytics agent testing?▼

Yes, you can generate custom scoring criteria for data analytics agent testing. The evaluation Skill enables defining specific test cases and grading rules to assess agent performance in data analytics tasks.

What's the best way to create a benchmarking report for a custom intelligent agent?▼

The best way to create a benchmarking report is to use a standardized evaluation process. Generate test cases, execute them on your custom intelligent agent, grade responses, and compile a comprehensive scoring report.

How do I start evaluating agent performance end to end?▼

To start evaluating agent performance, define your test set and scoring criteria using 'evaluation create', then execute 'evaluation run' to test the agent and generate a comprehensive scoring report.