Prompt Engineering Patterns

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

Overview

Effective prompt engineering combines structured patterns, iterative optimization, and psychological principles to achieve consistent, high-quality LLM outputs. This skill covers core capabilities, key patterns, best practices, and production-ready templates.

Core Capabilities

1. Few-Shot Learning: Teach by showing examples (2-5 input-output pairs)
2. Chain-of-Thought Prompting: Request step-by-step reasoning
3. Prompt Optimization: Systematically improve through testing
4. Template Systems: Build reusable prompt structures
5. System Prompt Design: Set global behavior and constraints

When to Use

Use prompt engineering when:

• Writing commands, hooks, or skills for agents
• Designing prompts for sub-agents
• Optimizing LLM interactions
• Building production prompt templates
• Improving output consistency and reliability

Progressive Loading

L2 Content (loaded when patterns and practices needed):

• See: references/patterns.md
  • Core Capabilities (detailed)
  • Key Patterns
  • Best Practices
  • Common Pitfalls
  • Integration Patterns
  • Performance Optimization

L3 Content (loaded when advanced techniques and examples needed):

• See: references/advanced.md
  • The Seven Principles
  • Principle Combinations by Prompt Type
  • Psychology Behind Effective Prompts
  • Ethical Use Guidelines
  • Production Examples
  • Quick Reference