How does this skill handle prompt regression testing?

It provides configuration patterns and scripts that allow you to test new prompt iterations against established baselines to ensure no loss in quality.

What is the primary purpose of the Promptfoo Config skill?

The skill is designed to automate the setup and execution of promptfoo, a framework used for testing and evaluating the quality of LLM prompts.

What kind of output does the evaluation generate?

The skill supports running evaluations that can produce detailed reports, including HTML summaries for visual comparison of LLM outputs.

Can I use this skill to compare different AI models?

Yes, it includes specific templates for multi-provider comparison, allowing you to run the same prompts across different models to evaluate performance.

Promptfoo Config

Name: Promptfoo Config
Author: vanman2024

byvanman2024

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Security & Testing

Streamlines the configuration and execution of promptfoo for rigorous LLM evaluation and regression testing.

About

The Promptfoo Config skill empowers developers to implement systematic testing for LLM prompts by automating the setup and management of the promptfoo framework. It provides a structured approach to prompt engineering through pre-configured templates for multi-provider comparisons, regression testing, and assertion-based validation, helping teams ensure prompt quality, compare model performance, and generate comprehensive HTML evaluation reports directly within their workflow.

Key Features

Automated initialization of promptfoo projects with standardized templates
Integrated execution scripts for running evaluations and generating reports
Multi-provider comparison configurations for benchmarking different LLMs
Assertion-based validation for ensuring specific output criteria are met
2 GitHub stars
Regression testing patterns to detect performance drops in prompt updates

Use Cases

Creating evaluation pipelines that validate AI outputs against business rules using assertions
Benchmarking different LLM providers like OpenAI, Anthropic, and Google for specific tasks
Setting up automated prompt regression tests to prevent quality degradation

About

Key Features

Automated initialization of promptfoo projects with standardized templates
Integrated execution scripts for running evaluations and generating reports
Multi-provider comparison configurations for benchmarking different LLMs
Assertion-based validation for ensuring specific output criteria are met
2 GitHub stars
Regression testing patterns to detect performance drops in prompt updates

Use Cases

Creating evaluation pipelines that validate AI outputs against business rules using assertions
Benchmarking different LLM providers like OpenAI, Anthropic, and Google for specific tasks
Setting up automated prompt regression tests to prevent quality degradation