Is this skill suitable for production validation?

Absolutely. It is designed to help developers validate a model's performance metrics against real-world data representativeness before deployment.

How do I trigger the model evaluation skill?

You can trigger it by asking Claude to 'evaluate model performance', 'test metrics', or 'compare results', which prompts Claude to use the /eval-model command.

Which machine learning metrics does this skill support?

The suite provides a comprehensive set of metrics including accuracy, precision, recall, F1-score, and other relevant performance indicators.

Can I compare two different models at once?

Yes, you can ask Claude to compare Model A and Model B, and the skill will extract and present a side-by-side comparison of their scores.

Machine Learning Model Evaluation Suite

Name: Machine Learning Model Evaluation Suite
Author: jeremylongshore

byjeremylongshore

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884

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Data Science & ML

Assesses machine learning model performance through comprehensive metric analysis, including accuracy, precision, and F1-scores.

The Machine Learning Model Evaluation Suite empowers Claude to conduct deep performance audits on AI models directly within your development environment. By leveraging the /eval-model command, this skill automates the calculation of essential validation metrics like precision, recall, and F1-score, allowing developers to compare multiple models, identify optimization opportunities, and validate performance benchmarks before production deployment.

Key Features

01884 GitHub stars

02Context-aware interpretation of model performance results

03Integration with the /eval-model command for streamlined workflows

04Comparative analysis tools for benchmarking multiple models

05Automated calculation of accuracy, precision, recall, and F1-score

06Validation of models against representative held-out datasets

Use Cases

01Comparing performance metrics between different model architectures

02Validating a model's performance on a test dataset before deployment

03Identifying specific areas for model optimization and refinement

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills model-evaluation-suite

For use in Claude.ai and ChatGPT

Download Skill

Key Features

01884 GitHub stars

02Context-aware interpretation of model performance results

03Integration with the /eval-model command for streamlined workflows

04Comparative analysis tools for benchmarking multiple models

05Automated calculation of accuracy, precision, recall, and F1-score

06Validation of models against representative held-out datasets

Use Cases

01Comparing performance metrics between different model architectures

02Validating a model's performance on a test dataset before deployment

03Identifying specific areas for model optimization and refinement

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills model-evaluation-suite

For use in Claude.ai and ChatGPT

Download Skill