name: prompt-engineering
description: |-
This skill transforms raw prompts into clear, effective prompts using proven frameworks and best practices. It applies the six-part prompting framework and other advanced techniques to enhance prompt quality, specificity, and effectiveness. This skill should be used when users need to convert vague or basic prompts into professional-grade prompts that yield better results from AI models.

Prompt Engineering Skill

This skill enhances raw prompts by transforming them into clear, structured prompts using industry-standard frameworks and best practices. It leverages the six-part prompting framework and other advanced techniques to improve prompt effectiveness and output quality.

Core Capabilities

1. Framework Application: Applies the six-part prompting framework to structure prompts effectively
2. Best Practice Integration: Incorporates proven prompt engineering techniques
3. Quality Enhancement: Improves clarity, specificity, and effectiveness of prompts
4. Template Generation: Creates professional-grade prompts with optimal structure

The Six-Part Prompting Framework

The skill implements the comprehensive six-part framework for optimal prompt engineering:

1. Command: Start Strong, Not Soft

• Begins with clear, direct commands using strong action verbs
• Uses specific action verbs: analyze, create, design, recommend, generate, evaluate
• Avoids weak words like "give" or "help"
• Sets a professional, focused tone

2. Context: More is Always Better

• Provides comprehensive background information to narrow AI's interpretation range
• Implements the Rule of Three Framework:
• Who: Age, profession, experience level, situation
• What: Specific goal, constraints, requirements
• When: Timeline, deadlines, urgency
• Scales context appropriately based on complexity and importance

3. Logic: Define the Output Structure

• Specifies exactly how the AI should think and respond
• Defines clear output requirements and structure
• May include tables, checklists, or specific formatting

4. Roleplay: Transform Generic into Expert-Level

• Has the AI adopt a specific professional identity to improve response quality
• Assigns field-specific roles based on the prompt's domain
• Examples: "You are a certified financial advisor with 15 years of experience..."

5. Formatting: Structure for Success

• Organizes information in immediately useful and actionable ways
• Offers popular formatting options:
• Numbered lists for sequential steps
• Bullet points for equal-weight items
• Tables for comparing options
• Sections with headers for complex topics
• Summary boxes for key takeaways

6. Questions: The Secret Sauce

• Ends prompts with question requests to identify gaps and refine results
• Implements iterative questioning for deeper refinement
• Uses follow-up questions to enhance precision

Additional Prompt Engineering Techniques

• Zero-Shot: Direct requests without examples
• Few-Shot: Multiple examples to establish pattern (typically 3-5 optimal)
• Chain of Thought (CoT): Encourages step-by-step reasoning
• System Prompting: Sets overall context and behavior guidelines
• Role Prompting: Assigns specific expertise to the AI

Configuration Settings Guidance

• Temperature (0-1): Low (0-0.3) for focused responses, high (0.8-1.0) for creative outputs
• Output Length/Token Limits: Controls maximum response length
• Top-K and Top-P: Limit choices to top most likely tokens based on probability

Input Parameters

• Raw Prompt: The initial, potentially vague or basic prompt to be enhanced
• Target Domain: The specific field or application area for the prompt (optional)
• Output Requirements: Specific format or structure requirements (optional)

Output

An enhanced, professionally-structured prompt in JSON format that incorporates the six-part framework and other best practices, designed to produce superior results from AI models. The JSON output includes:

• originalPrompt: The input prompt provided by the user
• enhancedPrompt: The improved prompt following the six-part framework
• frameworkApplied: Details of which framework elements were applied
• improvementNotes: Explanation of the enhancements made
• expectedBenefits: Expected improvements from the enhanced prompt

Before Implementation

Gather context to ensure successful implementation:

Ensure all required context is gathered before implementing.
Only ask user for THEIR specific requirements (domain expertise is in this skill).