Prompt Engineering

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