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