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name: prompt-optimization description: Expert prompt optimization for LLMs and AI systems. Use when building AI features, improving agent performance, crafting system prompts, or optimizing LLM interactions. Masters prompt patterns and techniques. author: Joseph OBrien status: unpublished updated: '2025-12-23' version: 1.0.1 tag: skill type: skill

Prompt Optimization

This skill optimizes prompts for LLMs and AI systems, focusing on effective prompt patterns, few-shot learning, and optimal AI interactions.

When to Use This Skill

• When building AI features or agents
• When improving LLM response quality
• When crafting system prompts
• When optimizing agent performance
• When implementing few-shot learning
• When designing AI workflows

What This Skill Does

1. Prompt Design: Creates effective prompts with clear structure
2. Few-Shot Learning: Implements few-shot examples for better results
3. Chain-of-Thought: Uses reasoning patterns for complex tasks
4. Output Formatting: Specifies clear output formats
5. Constraint Setting: Sets boundaries and constraints
6. Performance Optimization: Improves prompt efficiency and results

How to Use

Optimize Prompt

CopyOptimize this prompt for better results

CopyCreate a system prompt for a code review agent

Specific Patterns

CopyImplement few-shot learning for this task

Prompt Techniques

Structure

Clear Sections:

• Role definition
• Task description
• Constraints and boundaries
• Output format
• Examples

Few-Shot Learning

Pattern:

• Provide 2-3 examples
• Show input-output pairs
• Demonstrate desired style
• Include edge cases

Chain-of-Thought

Approach:

• Break down complex tasks
• Show reasoning steps
• Encourage step-by-step thinking
• Verify intermediate results

Examples

Example 1: Code Review Prompt

Input: Create optimized code review prompt

Output:

Copy## Optimized Prompt: Code Review

### The Prompt

You are an expert code reviewer with 10+ years of experience.

Review the provided code focusing on:

1. Security vulnerabilities
2. Performance optimizations
3. Code maintainability
4. Best practices

For each issue found, provide:

• Severity level (Critical/High/Medium/Low)
• Specific line numbers
• Explanation of the issue
• Suggested fix with code example

Format your response as a structured report with clear sections.

Copy
### Techniques Used
- Role-playing for expertise
- Clear evaluation criteria
- Specific output format
- Actionable feedback requirements

Best Practices

Prompt Design

1. Be Specific: Clear, unambiguous instructions
2. Provide Examples: Show desired output format
3. Set Constraints: Define boundaries clearly
4. Iterate: Test and refine prompts
5. Document: Keep track of effective patterns

Related Use Cases

• AI agent development
• LLM optimization
• System prompt creation
• Few-shot learning implementation
• AI workflow design