prompt-engineering-patterns

Design prompt templates for LLM production by validating YAML frontmatter, enforcing functional requirements, and defining scope for design, evaluation, and versioning to ensure robust performance.

The best way to use chain-of-thought and few-shot patterns is by creating reusable system prompts and templates that enforce structured outputs, maximizing LLM reliability and controllability.

Evaluate and version prompt templates by applying structured evaluation metrics and best practices, centralizing prompt design and testing to maintain LLM performance at scale.

Common pitfalls when productionizing LLM prompts include neglecting structured evaluation metrics, ignoring YAML frontmatter validation, and failing to version prompt templates properly.

Yes, numpy is a required dependency for this Skill, utilized within scripts and assets to support the structured evaluation and optimization of prompt templates.