prompt-engineering-patterns

Structured prompt engineering patterns like Chain-of-Thought, few-shot learning, and role-based system prompts enforce controllable, consistent LLM generation. This Skill provides ready-to-use templates to maximize output reliability for production systems.

The best way to design system prompts is by applying pattern-driven templates that enforce structured outputs, evaluation, and safety. This Skill supplies production-ready system prompts and best practices for scalable, controllable LLM workflows.

Integrate the provided few-shot and Chain-of-Thought templates directly into your agent workflows. These patterns guide the LLM through structured reasoning and examples to maximize task performance and output accuracy.

This Skill requires numpy as its only dependency. It provides scripts, references, and assets to support prompt evaluation and iteration without mandating specific external LLM frameworks.

Evaluate and iterate on prompt templates by applying the Skill's built-in best practices for structured outputs and safety. It provides references and scripts to systematically test, refine, and optimize prompts across diverse domains.