domains / families / agent-tooling / senior-prompt-engineer
This skill should be used when the user asks to "optimize prompts", "design prompt templates", "evaluate LLM outputs", "build agentic systems", "implement RAG", "create few-shot examples", "analyze token usage", or "design AI workflows". Use for prompt engineering patterns, LLM evaluation frameworks, agent architectures, and structured output design. World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implementing advanced prompting techniques.
The two copies share the same three tool names (prompt_optimizer, rag_evaluator, agent_orchestrator) but disagree on their purpose and usage. The first copy frames the skill as a broad 'Senior AI/ML Engineer' with generic MLOps patterns, Kubernetes deployment, and high-level performance targets, while the second copy provides specific, actionable workflows for prompt optimization, RAG evaluation metrics, and agent flow visualization. Because the first copy lacks the specific evaluation metrics and the second lacks the broader MLOps/deployment context, crowning one would hide the specific tooling details or the broader architectural guidance respectively.