prompt-engineering

name	prompt-engineering
description	Comprehensive prompt engineering framework for designing, optimizing, and iterating LLM prompts. Use when creating prompts, optimizing existing prompts, or improving AI instructions.

Prompt Engineering

Workflow

User Request
|
+-- "Create a prompt" --> EXPLORATION PHASE
+-- "Optimize this prompt" --> OPTIMIZATION PHASE
+-- "Fix this issue" --> ANALYSIS PHASE

Phase 1: Exploration

Before creating any prompt, understand:

• What task will this prompt accomplish?
• Who will use it?
• What does success look like?
• What are the constraints?

Phase 2: Analysis

Task Classification

Dimension	Options
Complexity	Simple vs multi-step
Output	Creative vs analytical vs structured
Stakes	High vs experimental

Strategy Selection

Task Type	Approach
Simple	Direct instructions
Complex	Chain-of-thought
Creative	Role setting
Structured	Format specs + examples

Phase 3: Implementation

Version 1 - Minimal

• Core instructions only
• Test basic functionality

Version 2 - Enhanced

• Add examples
• Clarify ambiguities
• Add constraints

Version 3+ - Optimized

• Refine wording
• Remove redundancy

Key Techniques

Role Setting

As an experienced code reviewer, analyze...

Chain-of-Thought

Think step-by-step:
1. First, identify...
2. Then, analyze...
3. Finally, conclude...

Few-Shot Learning

Example 1:
Input: "Great product"
Output: { "sentiment": "positive" }

Now analyze: "It was okay"

Explicit Constraints

- Limit to 3 paragraphs
- Focus on technical aspects only
- Do not include pricing

Prompt Template

## Context
[Background information]

## Role (Optional)
You are a [ROLE] with expertise in [DOMAIN].

## Task
[Clear instruction]

## Constraints
- Constraint 1
- Constraint 2

## Output Format
[Format specification]

## Examples (Optional)
[Input/Output examples]

Common Mistakes

Mistake	Fix
Vague instructions	Be specific
No examples	Add 1-2 examples
Too many rules	Simplify
No format spec	Define output structure