Prompt Engineering Patterns

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability.

When to Use This Skill

Designing complex prompts for production LLM applications
Optimizing prompt performance and consistency
Implementing structured reasoning patterns (chain-of-thought, tree-of-thought)
Building few-shot learning systems with dynamic example selection
Creating reusable prompt templates with variable interpolation
Debugging and refining prompts that produce inconsistent outputs
Implementing system prompts for specialized AI assistants
Using structured outputs (JSON mode) for reliable parsing
Context Engineering: Optimizing the structure, density, and ordering of context
Reasoning Architecture: Implementing multi-stage reasoning (CoT, ToT, GoT)