senior-prompt-engineer

You can optimize LLM prompts by analyzing and refining them for better token efficiency, clarity, and structure. This Skill evaluates prompt components to ensure your AI interactions yield accurate and helpful responses.

RAG evaluation assesses the quality of retrieval-augmented generation systems by measuring context relevance and answer faithfulness. This ensures your AI applications retrieve accurate context and generate faithful responses.

You validate agent workflows by using orchestration tools to visualize configurations and tool usage. This verifies that your agentic workflows operate correctly and integrate tools effectively for sophisticated AI applications.

Yes, you can analyze a customer support chatbot prompt from a text file. The Skill processes text files like 'customer_service_prompt.txt' to evaluate and refine prompts for accurate chatbot interactions.

Prompt engineering optimizes text inputs, RAG evaluation metrics, and agent configuration validation, but does not handle underlying model training or infrastructure scaling. It refines interactions within existing LLM capabilities.