Prompt Engineer

What it does

This skill, akiselev-prompt-engineer, provides tools to refine and optimize prompts for large language models (LLMs). It allows users to iteratively improve LLM outputs by suggesting modifications and evaluating different prompt variations. The core functionality focuses on enhancing the quality and relevance of responses generated by LLMs.

When to use it

• Improving Response Quality: When initial LLM responses are unsatisfactory, vague, or inaccurate.
• Experimenting with Prompt Strategies: To test different phrasing and approaches for eliciting desired behaviors from an LLM.
• Refining Complex Tasks: When breaking down a complex task into smaller steps and crafting prompts for each step requires precision.
• Debugging Unexpected Behavior: When an LLM exhibits undesirable or inconsistent behavior, prompt engineering can help identify and correct the underlying issues.

Key capabilities

• Prompt suggestion & modification
• Evaluation of different prompt variations
• Iterative refinement process

Example prompts

• "Can you suggest a better way to phrase this prompt: 'Write a short story about a cat'?"
• "Evaluate these two prompts for generating marketing copy: [prompt 1], [prompt 2]"
• "I want the LLM to summarize this article. Suggest some improvements to my current prompt."

Tips & gotchas

This skill is most effective when you have a clear understanding of the desired outcome from the LLM and can provide specific examples of what works or doesn't work with initial prompts. The quality of suggestions depends on the clarity of your feedback during the iterative refinement process.