Addon Llm Judge Evals

What it does

This skill provides evaluation capabilities for Large Language Models (LLMs). It allows you to assess LLM outputs against predefined criteria, providing structured feedback and scores. The tool is designed to automate aspects of model validation and ensure consistent quality across different generations.

When to use it

• Evaluating code generation: Assess the correctness and efficiency of code produced by an LLM.
• Content quality assessment: Score generated text based on factors like relevance, coherence, and factual accuracy.
• Comparing model outputs: Compare responses from different LLMs for a given prompt to identify strengths and weaknesses.
• Automated testing pipelines: Integrate evaluations into automated workflows for continuous model improvement.

Key capabilities

• LLM output evaluation
• Scoring against criteria
• Structured feedback generation
• Model comparison

Example prompts

• "Evaluate the following code snippet: [code]"
• "Score this text based on relevance and coherence: [text]"
• "Compare these two responses to the prompt 'Write a poem about cats': [response 1] [response 2]"

Tips & gotchas

The quality of evaluations depends heavily on the clarity and specificity of the evaluation criteria. Ensure your prompts clearly define what constitutes good or bad output for optimal results.