name: prompt-engineer description: Converts user content into a structured prompt using a reusable template.

Prompt Engineer Command

Description

Converts user content into a well-structured prompt using the Universal Prompt Structure Template. Analyzes session context and formats content for optimal AI interaction.

Usage

/prompt-engineer [content]

Arguments

• content (required): The detailed content/topic to convert into a structured prompt

Implementation

When invoked with content, I will:

1. Analyze the provided content - Identify domain (technical, business, creative), complexity level, and core requirements
2. Search current session - Look for relevant context, documents, or previous discussions that add value
3. Apply Universal Prompt Template - Structure using appropriate template sections based on content analysis
4. Output complete structured prompt - Ready-to-use prompt following the template format

Template Sections Applied

• Always Include: Task Context, Tone Context, Detailed Task Description, Immediate Request, Thinking Instructions, Output Formatting
• Include When Relevant: Background Data, Examples, Conversation History, Prefilled Response

Example Usage

/prompt-engineer "Create a customer service chatbot for our e-commerce platform that handles order inquiries"

Output Format

The command outputs a complete structured prompt following this pattern:

# Structured Prompt for: [Topic]

## 1. Task Context
[AI role and purpose based on content analysis]

## 2. Tone Context
[Communication style matching user's approach]

## 3. Background Data (if relevant)
[Session context and relevant documents]

## 4. Detailed Task Description & Rules
[Specific requirements and constraints]

## 5. Examples (if applicable)
[Demonstration of expected interactions]

## 6. Immediate Task Description
<question>{{CONTENT_RESTATED}}</question>

## 7. Thinking Step by Step
[Systematic processing instructions]

## 8. Output Formatting
[Desired response structure]

Benefits

• Context-Aware: Incorporates relevant session history and documentation
• Tone-Matched: Adapts to user's communication style (direct, technical, professional)
• Complete: Includes all necessary prompt engineering elements
• Reusable: Generated prompts work across different AI systems
• Systematic: Follows proven prompt structure template