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skills/openai-prompt-engineer/SKILL.md
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skills/openai-prompt-engineer/SKILL.md
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---
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name: openai-prompt-engineer
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description: Generate and improve prompts using best practices for OpenAI GPT-5 and other LLMs. Apply advanced techniques like chain-of-thought, few-shot prompting, and progressive disclosure.
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---
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# OpenAI Prompt Engineer
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A comprehensive skill for crafting, analyzing, and improving prompts for OpenAI's GPT-5 and other modern Large Language Models (LLMs), with focus on GPT-5-specific optimizations and universal prompting techniques.
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## What This Skill Does
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Helps you create and optimize prompts using cutting-edge techniques:
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- **Generate new prompts** - Build effective prompts from scratch
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- **Improve existing prompts** - Enhance clarity, structure, and results
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- **Apply best practices** - Use proven techniques for each model
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- **Optimize for specific models** - GPT-5, Claude-specific strategies
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- **Implement advanced patterns** - Chain-of-thought, few-shot, structured prompting
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- **Analyze prompt quality** - Identify issues and suggest improvements
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## Why Prompt Engineering Matters
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**Without good prompts:**
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- Inconsistent or incorrect outputs
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- Poor instruction following
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- Wasted tokens and API costs
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- Multiple attempts needed
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- Unpredictable behavior
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**With optimized prompts:**
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- Accurate, consistent results
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- Better instruction adherence
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- Lower costs and latency
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- First-try success
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- Predictable, reliable outputs
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## Supported Models & Approaches
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### GPT-5 (OpenAI)
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- Structured prompting (role + task + constraints)
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- Reasoning effort calibration
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- Agentic behavior control
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- Verbosity management
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- Prompt optimizer integration
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### Claude (Anthropic)
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- XML tag structuring
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- Step-by-step thinking
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- Clear, specific instructions
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- Example-driven prompting
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- Progressive disclosure
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### Universal Techniques
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- Chain-of-thought prompting
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- Few-shot learning
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- Zero-shot prompting
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- Self-consistency
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- Role-based prompting
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## Core Prompting Principles
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### 1. Be Clear and Specific
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**Bad:** "Write about AI"
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**Good:** "Write a 500-word technical article explaining transformer architecture for software engineers with 2-3 years of experience. Include code examples in Python and focus on practical implementation."
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### 2. Provide Structure
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Use clear formatting to organize instructions:
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```
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Role: You are a senior Python developer
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Task: Review this code for security vulnerabilities
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Constraints:
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- Focus on OWASP Top 10
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- Provide specific line numbers
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- Suggest fixes with code examples
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Output format: Markdown with severity ratings
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```
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### 3. Use Examples (Few-Shot)
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Show the model what you want:
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```
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Input: "User clicked login"
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Output: "USER_LOGIN_CLICKED"
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Input: "Payment processed successfully"
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Output: "PAYMENT_PROCESSED_SUCCESS"
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Input: "Email verification failed"
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Output: [Your turn]
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```
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### 4. Enable Reasoning
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Add phrases like:
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- "Think step-by-step"
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- "Let's break this down"
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- "First, analyze... then..."
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- "Show your reasoning"
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### 5. Define Output Format
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Specify exactly how you want the response:
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```xml
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<output_format>
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<summary>One sentence overview</summary>
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<details>
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<point>Key finding 1</point>
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<point>Key finding 2</point>
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</details>
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<recommendation>Specific action to take</recommendation>
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</output_format>
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```
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## Prompt Engineering Workflow
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### 1. Define Your Goal
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- What task are you solving?
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- What's the ideal output?
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- Who's the audience?
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- What model will you use?
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### 2. Choose Your Technique
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- **Simple task?** → Direct instruction
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- **Complex reasoning?** → Chain-of-thought
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- **Pattern matching?** → Few-shot examples
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- **Need consistency?** → Structured format + examples
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### 3. Build Your Prompt
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Use this template:
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```
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[ROLE/CONTEXT]
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You are [specific role with relevant expertise]
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[TASK]
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[Clear, specific task description]
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[CONSTRAINTS]
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- [Limitation 1]
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- [Limitation 2]
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[FORMAT]
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Output should be [exact format specification]
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[EXAMPLES - if using few-shot]
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[Example 1]
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[Example 2]
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[THINK STEP-BY-STEP - if complex reasoning]
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Before answering, [thinking instruction]
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```
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### 4. Test and Iterate
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- Run the prompt
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- Analyze output quality
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- Identify issues
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- Refine and retry
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- Document what works
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## Advanced Techniques
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### Chain-of-Thought (CoT) Prompting
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**When to use:** Complex reasoning, math, multi-step problems
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**How it works:** Ask the model to show intermediate steps
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**Example:**
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```
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Problem: A store has 15 apples. They sell 60% in the morning and
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half of what's left in the afternoon. How many remain?
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Please solve this step-by-step:
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1. Calculate morning sales
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2. Calculate remaining after morning
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3. Calculate afternoon sales
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4. Calculate final remaining
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```
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**Result:** More accurate answers through explicit reasoning
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### Few-Shot Prompting
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**When to use:** Pattern matching, classification, style transfer
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**How it works:** Provide 2-5 examples, then the actual task
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**Example:**
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```
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Convert casual text to professional business tone:
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Input: "Hey! Thanks for reaching out. Let's chat soon!"
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Output: "Thank you for your message. I look forward to our conversation."
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Input: "That's a great idea! I'm totally on board with this."
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Output: "I appreciate your suggestion and fully support this initiative."
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Input: "Sounds good, catch you later!"
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Output: [Model completes]
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```
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### Zero-Shot Chain-of-Thought
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**When to use:** Complex problems without examples
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**How it works:** Simply add "Let's think step by step"
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**Example:**
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```
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Question: What are the security implications of storing JWTs
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in localStorage?
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Let's think step by step:
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```
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**Magic phrase:** "Let's think step by step" → dramatically improves reasoning
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### Structured Output with XML
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**When to use:** Working with Claude or need parsed output
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**Example:**
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```
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Analyze this code for issues. Structure your response as:
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<analysis>
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<security_issues>
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<issue severity="high|medium|low">
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<description>What's wrong</description>
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<location>File and line number</location>
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<fix>How to fix it</fix>
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</issue>
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</security_issues>
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<performance_issues>
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<!-- Same structure -->
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</performance_issues>
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<best_practices>
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<suggestion>Improvement suggestion</suggestion>
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</best_practices>
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</analysis>
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```
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### Progressive Disclosure
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**When to use:** Large context, multi-step workflows
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**How it works:** Break tasks into stages, only request what's needed now
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**Example:**
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```
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Stage 1: "Analyze this codebase structure and list the main components"
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[Get response]
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Stage 2: "Now, for the authentication component you identified,
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show me the security review"
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[Get response]
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Stage 3: "Based on that review, generate fixes for the high-severity issues"
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```
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## Model-Specific Best Practices
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### GPT-5 Optimization
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**Structured Prompting:**
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```
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ROLE: Senior TypeScript Developer
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TASK: Implement user authentication service
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CONSTRAINTS:
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- Use JWT with refresh tokens
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- TypeScript with strict mode
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- Include comprehensive error handling
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- Follow SOLID principles
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OUTPUT: Complete TypeScript class with JSDoc comments
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REASONING_EFFORT: high (for complex business logic)
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```
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**Control Agentic Behavior:**
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```
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"Implement this feature step-by-step, asking for confirmation
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before each major decision"
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OR
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"Complete this task end-to-end without asking for guidance.
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Persist until fully handled."
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```
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**Manage Verbosity:**
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```
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"Provide a concise implementation (under 100 lines) focusing
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only on core functionality"
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```
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### Claude Optimization
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**Use XML Tags:**
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```
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<instruction>
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Review this pull request for security issues
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</instruction>
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<code>
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[Code to review]
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</code>
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<focus_areas>
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- SQL injection vulnerabilities
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- XSS attack vectors
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- Authentication bypasses
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- Data exposure risks
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</focus_areas>
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<output_format>
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For each issue found, provide:
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1. Severity (Critical/High/Medium/Low)
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2. Location
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3. Explanation
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4. Fix recommendation
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</output_format>
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```
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**Step-by-Step Thinking:**
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```
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Think through this architecture decision step by step:
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1. First, identify the requirements
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2. Then, list possible approaches
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3. Evaluate trade-offs for each
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4. Make a recommendation with reasoning
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```
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**Clear Specificity:**
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```
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BAD: "Make the response professional"
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GOOD: "Use formal business language, avoid contractions,
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address the user as 'you', keep sentences under 20 words"
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```
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## Prompt Improvement Checklist
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Use this checklist to improve any prompt:
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- [ ] **Clear role defined** - Is the AI's expertise specified?
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- [ ] **Specific task** - Is it unambiguous what to do?
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- [ ] **Constraints listed** - Are limitations clear?
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- [ ] **Format specified** - Is output structure defined?
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- [ ] **Examples provided** - Do you show what you want (if needed)?
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- [ ] **Reasoning enabled** - Do you ask for step-by-step thinking (if complex)?
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- [ ] **Context included** - Does the AI have necessary background?
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- [ ] **Edge cases covered** - Are exceptions handled?
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- [ ] **Length specified** - Is output length clear?
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- [ ] **Tone/style defined** - Is the desired voice specified?
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## Common Prompt Problems & Fixes
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### Problem: Vague Instructions
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**Before:**
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```
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"Write some code for user authentication"
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```
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**After:**
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```
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"Write a TypeScript class called AuthService that:
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- Accepts email/password credentials
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- Validates against a User repository
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- Returns a JWT token on success
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- Throws AuthenticationError on failure
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- Includes comprehensive JSDoc comments
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- Follows dependency injection pattern"
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```
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### Problem: No Examples (When Needed)
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**Before:**
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```
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"Convert these variable names to camelCase"
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```
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**After:**
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```
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"Convert these variable names to camelCase:
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user_name → userName
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total_count → totalCount
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is_active → isActive
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Now convert:
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order_status →
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created_at →
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max_retry_count →"
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```
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### Problem: Missing Output Format
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**Before:**
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```
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"Analyze this code for problems"
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```
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**After:**
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```
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"Analyze this code and output in this format:
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## Security Issues
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- [Issue]: [Description] (Line X)
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## Performance Issues
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- [Issue]: [Description] (Line X)
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## Code Quality
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- [Issue]: [Description] (Line X)
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## Recommendations
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1. [Priority 1 fix]
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2. [Priority 2 fix]"
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```
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### Problem: Too Complex (Single Shot)
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**Before:**
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```
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"Build a complete e-commerce backend with authentication,
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payments, inventory, and shipping"
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```
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**After (Progressive):**
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```
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"Let's build this in stages:
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Stage 1: Design the authentication system architecture
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[Get response, review]
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Stage 2: Implement the auth service
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[Get response, review]
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Stage 3: Add payment processing
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[Continue...]"
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```
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## Using This Skill
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### Generate a New Prompt
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**Ask:**
|
||||
```
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"Using the prompt-engineer skill, create a prompt for:
|
||||
[Describe your task and requirements]"
|
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```
|
||||
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**You'll get:**
|
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- Structured prompt template
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- Recommended techniques
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- Example few-shots if applicable
|
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- Model-specific optimizations
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### Improve an Existing Prompt
|
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**Ask:**
|
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```
|
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"Using the prompt-engineer skill, improve this prompt:
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|
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[Your current prompt]
|
||||
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||||
Goal: [What you want to achieve]
|
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Model: [GPT-5 / Claude / Other]"
|
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```
|
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**You'll get:**
|
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- Analysis of current issues
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||||
- Improved version
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||||
- Explanation of changes
|
||||
- Expected improvement in results
|
||||
|
||||
### Analyze Prompt Quality
|
||||
|
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**Ask:**
|
||||
```
|
||||
"Using the prompt-engineer skill, analyze this prompt:
|
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[Your prompt]"
|
||||
```
|
||||
|
||||
**You'll get:**
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- Quality score
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||||
- Identified weaknesses
|
||||
- Specific improvement suggestions
|
||||
- Best practices violations
|
||||
|
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## Real-World Examples
|
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|
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### Example 1: Code Review Prompt
|
||||
|
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**Task:** Get thorough, consistent code reviews
|
||||
|
||||
**Optimized Prompt:**
|
||||
```
|
||||
ROLE: Senior Software Engineer conducting PR review
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||||
|
||||
REVIEW THIS CODE:
|
||||
[code block]
|
||||
|
||||
REVIEW CRITERIA:
|
||||
1. Security vulnerabilities (OWASP Top 10)
|
||||
2. Performance issues
|
||||
3. Code quality and readability
|
||||
4. Best practices compliance
|
||||
5. Test coverage gaps
|
||||
|
||||
OUTPUT FORMAT:
|
||||
For each issue found:
|
||||
- Severity: [Critical/High/Medium/Low]
|
||||
- Category: [Security/Performance/Quality/Testing]
|
||||
- Location: [File:Line]
|
||||
- Issue: [Clear description]
|
||||
- Impact: [Why this matters]
|
||||
- Fix: [Specific code recommendation]
|
||||
|
||||
At the end, provide:
|
||||
- Overall assessment (Approve/Request Changes/Comment)
|
||||
- Summary of critical items that must be fixed
|
||||
```
|
||||
|
||||
### Example 2: Technical Documentation
|
||||
|
||||
**Task:** Generate clear API documentation
|
||||
|
||||
**Optimized Prompt:**
|
||||
```
|
||||
ROLE: Technical writer with API documentation expertise
|
||||
|
||||
TASK: Generate API documentation for this endpoint
|
||||
|
||||
ENDPOINT DETAILS:
|
||||
[code/specs]
|
||||
|
||||
DOCUMENTATION REQUIREMENTS:
|
||||
- Target audience: Junior to mid-level developers
|
||||
- Include curl and JavaScript examples
|
||||
- Explain all parameters clearly
|
||||
- Show example responses with descriptions
|
||||
- Include common error cases
|
||||
- Add troubleshooting section
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||||
|
||||
FORMAT:
|
||||
# [Endpoint Name]
|
||||
|
||||
## Overview
|
||||
[One paragraph description]
|
||||
|
||||
## Endpoint
|
||||
`[HTTP METHOD] /path`
|
||||
|
||||
## Parameters
|
||||
| Name | Type | Required | Description |
|
||||
|------|------|----------|-------------|
|
||||
|
||||
## Request Example
|
||||
```bash
|
||||
[curl example]
|
||||
```
|
||||
|
||||
## Response
|
||||
### Success (200)
|
||||
```json
|
||||
[example with inline comments]
|
||||
```
|
||||
|
||||
### Errors
|
||||
- 400: [Description and fix]
|
||||
- 401: [Description and fix]
|
||||
|
||||
## Common Issues
|
||||
[Troubleshooting guide]
|
||||
```
|
||||
|
||||
### Example 3: Data Analysis
|
||||
|
||||
**Task:** Analyze data and provide insights
|
||||
|
||||
**Optimized Prompt:**
|
||||
```
|
||||
ROLE: Data analyst with expertise in business metrics
|
||||
|
||||
DATA:
|
||||
[dataset]
|
||||
|
||||
ANALYSIS REQUEST:
|
||||
Analyze this data step-by-step:
|
||||
|
||||
1. FIRST: Identify key metrics and trends
|
||||
2. THEN: Calculate:
|
||||
- Growth rate (month-over-month)
|
||||
- Average values
|
||||
- Anomalies or outliers
|
||||
3. NEXT: Draw business insights
|
||||
4. FINALLY: Provide actionable recommendations
|
||||
|
||||
OUTPUT FORMAT:
|
||||
## Executive Summary
|
||||
[2-3 sentences]
|
||||
|
||||
## Key Metrics
|
||||
| Metric | Value | Change | Trend |
|
||||
|
||||
## Insights
|
||||
1. [Insight with supporting data]
|
||||
2. [Insight with supporting data]
|
||||
|
||||
## Recommendations
|
||||
1. [Action]: [Expected impact]
|
||||
2. [Action]: [Expected impact]
|
||||
|
||||
## Methodology
|
||||
[Brief explanation of analysis approach]
|
||||
```
|
||||
|
||||
## Best Practices Summary
|
||||
|
||||
### DO ✅
|
||||
|
||||
- **Be specific** - Exact requirements, not vague requests
|
||||
- **Use structure** - Organize with clear sections
|
||||
- **Provide examples** - Show what you want (few-shot)
|
||||
- **Request reasoning** - "Think step-by-step" for complex tasks
|
||||
- **Define format** - Specify exact output structure
|
||||
- **Test iteratively** - Refine based on results
|
||||
- **Match to model** - Use model-specific techniques
|
||||
- **Include context** - Give necessary background
|
||||
- **Handle edge cases** - Specify exception handling
|
||||
- **Set constraints** - Define limitations clearly
|
||||
|
||||
### DON'T ❌
|
||||
|
||||
- **Be vague** - "Write something about X"
|
||||
- **Skip examples** - When patterns need to be matched
|
||||
- **Assume format** - Model will choose unpredictably
|
||||
- **Overload single prompt** - Break complex tasks into stages
|
||||
- **Ignore model differences** - GPT-5 and Claude need different approaches
|
||||
- **Give up too soon** - Iterate on prompts
|
||||
- **Mix instructions** - Keep separate concerns separate
|
||||
- **Forget constraints** - Specify ALL requirements
|
||||
- **Use ambiguous terms** - "Good", "professional", "better" without definition
|
||||
- **Skip testing** - Always validate outputs
|
||||
|
||||
## Quick Reference
|
||||
|
||||
### Prompt Template (Universal)
|
||||
```
|
||||
[ROLE]
|
||||
You are [specific expertise]
|
||||
|
||||
[CONTEXT]
|
||||
[Background information]
|
||||
|
||||
[TASK]
|
||||
[Clear, specific task]
|
||||
|
||||
[CONSTRAINTS]
|
||||
- [Limit 1]
|
||||
- [Limit 2]
|
||||
|
||||
[FORMAT]
|
||||
[Exact output structure]
|
||||
|
||||
[EXAMPLES - Optional]
|
||||
[2-3 examples]
|
||||
|
||||
[REASONING - Optional]
|
||||
Think through this step-by-step:
|
||||
[Thinking guidance]
|
||||
```
|
||||
|
||||
### When to Use Each Technique
|
||||
|
||||
| Technique | Best For | Example Use Case |
|
||||
|-----------|----------|------------------|
|
||||
| Chain-of-Thought | Complex reasoning | Math, logic puzzles, multi-step analysis |
|
||||
| Few-Shot | Pattern matching | Classification, style transfer, formatting |
|
||||
| Zero-Shot | Simple, clear tasks | Direct questions, basic transformations |
|
||||
| Structured (XML) | Parsed output | Data extraction, API responses |
|
||||
| Progressive Disclosure | Large tasks | Full implementations, research |
|
||||
| Role-Based | Expert knowledge | Code review, architecture decisions |
|
||||
|
||||
### Model Selection Guide
|
||||
|
||||
**Use GPT-5 when:**
|
||||
- Need strong reasoning
|
||||
- Agentic behavior helpful
|
||||
- Code generation focus
|
||||
- Latest knowledge needed
|
||||
|
||||
**Use Claude when:**
|
||||
- Very long context (100K+ tokens)
|
||||
- Detailed instruction following
|
||||
- Safety-critical applications
|
||||
- Prefer XML structuring
|
||||
|
||||
## Resources
|
||||
|
||||
All reference materials included:
|
||||
- GPT-5 specific techniques and patterns
|
||||
- Claude optimization strategies
|
||||
- Advanced prompting patterns
|
||||
- Optimization and improvement frameworks
|
||||
|
||||
## Summary
|
||||
|
||||
Effective prompt engineering:
|
||||
- **Saves time** - Get right results faster
|
||||
- **Reduces costs** - Fewer API calls needed
|
||||
- **Improves quality** - More accurate, consistent outputs
|
||||
- **Enables complexity** - Tackle harder problems
|
||||
- **Scales knowledge** - Capture best practices
|
||||
|
||||
Use this skill to create prompts that:
|
||||
- Are clear and specific
|
||||
- Use proven techniques
|
||||
- Match your model
|
||||
- Get consistent results
|
||||
- Achieve your goals
|
||||
|
||||
---
|
||||
|
||||
**Remember:** A well-crafted prompt is worth 10 poorly-attempted ones. Invest time upfront for better results.
|
||||
Reference in New Issue
Block a user