ref: prompts-chat/prompt-engineering-expert

title: Prompt Engineering Expert

summary: name: prompt-engineering-expert description: This skill equips Claude with deep expertise in prompt engineering, custom instructions design, and prompt optimization. It provides comprehensive…

credit: "Prompt Engineering Expert" by TomsTools11 (https://incantory.ai/prompts-chat/prompt-engineering-expert), licensed CC0-1.0

title: Prompt Engineering Expert

content:
---
name: prompt-engineering-expert
description: This skill equips Claude with deep expertise in prompt engineering, custom instructions design, and prompt optimization. It provides comprehensive guidance on crafting effective AI prompts, designing agent instructions, and iteratively improving prompt performance.
---

## Core Expertise Areas

### 1. Prompt Writing Best Practices
- **Clarity and Directness**: Writing clear, unambiguous prompts that leave no room for misinterpretation
- **Structure and Formatting**: Organizing prompts with proper hierarchy, sections, and visual clarity
- **Specificity**: Providing precise instructions with concrete examples and expected outputs
- **Context Management**: Balancing necessary context without overwhelming the model
- **Tone and Style**: Matching prompt tone to the task requirements

### 2. Advanced Prompt Engineering Techniques
- **Chain-of-Thought (CoT) Prompting**: Encouraging step-by-step reasoning for complex tasks
- **Few-Shot Prompting**: Using examples to guide model behavior (1-shot, 2-shot, multi-shot)
- **XML Tags**: Leveraging structured XML formatting for clarity and parsing
- **Role-Based Prompting**: Assigning specific personas or expertise to Claude
- **Prefilling**: Starting Claude's response to guide output format
- **Prompt Chaining**: Breaking complex tasks into sequential prompts

### 3. Custom Instructions & System Prompts
- **System Prompt Design**: Creating effective system prompts for specialized domains
- **Custom Instructions**: Designing instructions for AI agents and skills
- **Behavioral Guidelines**: Setting appropriate constraints and guidelines
- **Personality and Voice**: Defining consistent tone and communication style
- **Scope Definition**: Clearly defining what the agent should and shouldn't do

### 4. Prompt Optimization & Refinement
- **Performance Analysis**: Evaluating prompt effectiveness and identifying issues
- **Iterative Improvement**: Systematically refining prompts based on results
- **A/B Testing**: Comparing different prompt variations
- **Consistency Enhancement**: Improving reliability and reducing variability
- **Token Optimization**: Reducing unnecessary tokens while maintaining quality

### 5. Anti-Patterns & Common Mistakes
- **Vagueness**: Identifying and fixing unclear instructions
- **Contradictions**: Detecting conflicting requirements
- **Over-Specification**: Recognizing when prompts are too restrictive
- **Hallucination Risks**: Identifying prompts prone to false information
- **Context Leakage**: Preventing unintended information exposure
- **Jailbreak Vulnerabilities**: Recognizing and mitigating prompt injection risks

### 6. Evaluation & Testing
- **Success Criteria Definition**: Establishing clear metrics for prompt success
- **Test Case Development**: Creating comprehensive test cases
- **Failure Analysis**: Understanding why prompts fail
- **Regression Testing**: Ensuring improvements don't break existing functionality
- **Edge Case Handling**: Testing boundary conditions and unusual inputs

### 7. Multimodal & Advanced Prompting
- **Vision Prompting**: Crafting prompts for image analysis and understanding
- **File-Based Prompting**: Working with documents, PDFs, and structured data
- **Embeddings Integration**: Using embeddings for semantic search and retrieval
- **Tool Use Prompting**: Designing prompts that effectively use tools and APIs
- **Extended Thinking**: Leveraging extended thinking for complex reasoning

## Key Capabilities

- **Prompt Analysis**: Reviewing existing prompts and identifying improvement opportunities
- **Prompt Generation**: Creating new prompts from scratch for specific use cases
- **Prompt Refinement**: Iteratively improving prompts based on performance
- **Custom Instruction Design**: Creating specialized instructions for agents and skills
- **Best Practice Guidance**: Providing expert advice on prompt engineering principles
- **Anti-Pattern Recognition**: Identifying and correcting common mistakes
- **Testing Strategy**: Developing evaluation frameworks for prompt validation
- **Documentation**: Creating clear documentation for prompt usage and maintenance

## Use Cases

- Refining vague or ineffective prompts
- Creating specialized system prompts for specific domains
- Designing custom instructions for AI agents and skills
- Optimizing prompts for consistency and reliability
- Teaching prompt engineering best practices
- Debugging prompt performance issues
- Creating prompt templates for reusable workflows
- Improving prompt efficiency and token usage
- Developing evaluation frameworks for prompt testing

## Skill Limitations

- Does not execute code or run actual prompts (analysis only)
- Cannot access real-time data or external APIs
- Provides guidance based on best practices, not guaranteed results
- Recommendations should be tested with actual use cases
- Does not replace human judgment in critical applications

## Integration Notes

This skill works well with:
- Claude Code for testing and iterating on prompts
- Agent SDK for implementing custom instructions
- Files API for analyzing prompt documentation
- Vision capabilities for multimodal prompt design
- Extended thinking for complex prompt reasoning
FILE:START_HERE.md
# 🎯 Prompt Engineering Expert Skill - Complete Package

## ✅ What Has Been Created

A **comprehensive Claude Skill** for prompt engineering expertise with:

### 📦 Complete Package Contents
- **7 Core Documentation Files**
- **3 Specialized Guides** (Best Practices, Techniques, Troubleshooting)
- **10 Real-World Examples** with before/after comparisons
- **Multiple Navigation Guides** for easy access
- **Checklists and Templates** for practical use

### 📍 Location
```
~/Documents/prompt-engineering-expert/
```

---

## 📋 File Inventory

### Core Skill Files (4 files)
| File | Purpose | Size |
|------|---------|------|
| **SKILL.md** | Skill metadata & overview | ~1 KB |
| **CLAUDE.md** | Main skill instructions | ~3 KB |
| **README.md** | User guide & getting started | ~4 KB |
| **GETTING_STARTED.md** | How to upload & use | ~3 KB |

### Documentation (3 files)
| File | Purpose | Coverage |
|------|---------|----------|
| **docs/BEST_PRACTICES.md** | Comprehensive best practices | Core principles, advanced techniques, evaluation, anti-patterns |
| **docs/TECHNIQUES.md** | Advanced techniques guide | 8 major techniques with examples |
| **docs/TROUBLESHOOTING.md** | Problem solving | 8 common issues + debugging workflow |

### Examples & Navigation (3 files)
| File | Purpose | Content |
|------|---------|---------|
| **examples/EXAMPLES.md** | Real-world examples | 10 practical examples with templates |
| **INDEX.md** | Complete navigation | Quick links, learning paths, integration points |
| **SUMMARY.md** | What was created | Overview of all components |

---

## 🎓 Expertise Covered

### 7 Core Expertise Areas
1. ✅ **Prompt Writing Best Practices** - Clarity, structure, specificity
2. ✅ **Advanced Techniques** - CoT, few-shot, XML, role-based, prefilling, chaining
3. ✅ **Custom Instructions** - System prompts, behavioral guidelines, scope
4. ✅ **Optimization** - Performance analysis, iterative improvement, token efficiency
5. ✅ **Anti-Patterns** - Vagueness, contradictions, hallucinations, jailbreaks
6. ✅ **Evaluation** - Success criteria, test cases, failure analysis
7. ✅ **Multimodal** - Vision, files, embeddings, extended thinking

### 8 Key Capabilities
1. ✅ Prompt Analysis
2. ✅ Prompt Generation
3. ✅ Prompt Refinement
4. ✅ Custom Instruction Design
5. ✅ Best Practice Guidance
6. ✅ Anti-Pattern Recognition
7. ✅ Testing Strategy
8. ✅ Documentation

---

## 🚀 How to Use

### Step 1: Upload the Skill
```
Go to Claude.com → Click "+" → Upload Skill → Select folder
```

### Step 2: Ask Claude
```
"Review this prompt and suggest improvements:
[YOUR PROMPT]"
```

### Step 3: Get Expert Guidance
Claude will analyze using the skill's expertise and provide recommendations.

---

## 📚 Documentation Breakdown

### BEST_PRACTICES.md (~8 KB)
- Core principles (clarity, conciseness, degrees of freedom)
- Advanced techniques (8 techniques with explanations)
- Custom instructions design
- Skill structure best practices
- Evaluation & testing frameworks
- Anti-patterns to avoid
- Workflows and feedback loops
- Content guidelines
- Multimodal prompting
- Development workflow
- Complete checklist

### TECHNIQUES.md (~10 KB)
- Chain-of-Thought prompting (with examples)
- Few-Shot learning (1-shot, 2-shot, multi-shot)
- Structured output with XML tags
- Role-based prompting
- Prefilling responses
- Prompt chaining
- Context management
- Multimodal prompting
- Combining techniques
- Anti-patterns

### TROUBLESHOOTING.md (~6 KB)
- 8 common issues with solutions
- Debugging workflow
- Quick reference table
- Testing checklist

### EXAMPLES.md (~8 KB)
- 10 real-world examples
- Before/after comparisons
- Templates and frameworks
- Optimization checklists

---

## 💡 Key Features

### ✨ Comprehensive
- Covers all major aspects of prompt engineering
- From basics to advanced techniques
- Real-world examples and templates

### 🎯 Practical
- Actionable guidance
- Step-by-step instructions
- Ready-to-use templates

### 📖 Well-Organized
- Clear structure with progressive disclosure
- Multiple navigation guides
- Quick reference tables

### 🔍 Detailed
- 8 common issues with solutions
- 10 real-world examples
- Multiple checklists

### 🚀 Ready to Use
- Can be uploaded immediately
- No additional setup needed
- Works with Claude.com and API

---

## 📊 Statistics

| Metric | Value |
|--------|-------|
| Total Files | 10 |
| Total Documentation | ~40 KB |
| Core Expertise Areas | 7 |
| Key Capabilities | 8 |
| Use Cases | 9 |
| Common Issues Covered | 8 |
| Real-World Examples | 10 |
| Advanced Techniques | 8 |
| Best Practices | 50+ |
| Anti-Patterns | 10+ |

---

## 🎯 Use Cases

### 1. Refining Vague Prompts
Transform unclear prompts into specific, actionable ones.

### 2. Creating Specialized Prompts
Design prompts for specific domains or tasks.

### 3. Designing Agent Instructions
Create custom instructions for AI agents and skills.

### 4. Optimizing for Consistency
Improve reliability and reduce variability.

### 5. Teaching Best Practices
Learn prompt engineering principles and techniques.

### 6. Debugging Prompt Issues
Identify and fix problems with existing prompts.

### 7. Building Evaluation Frameworks
Develop test cases and success criteria.

### 8. Multimodal Prompting
Design prompts for vision, embeddings, and files.

### 9. Creating Prompt Templates
Build reusable prompt templates for workflows.

---

## ✅ Quality Checklist

- ✅ Based on official Anthropic documentation
- ✅ Comprehensive coverage of prompt engineering
- ✅ Real-world examples and templates
- ✅ Clear, well-organized structure
- ✅ Progressive disclosure for learning
- ✅ Multiple navigation guides
- ✅ Practical, actionable guidance
- ✅ Troubleshooting and debugging help
- ✅ Best practices and anti-patterns
- ✅ Ready to upload and use

---

## 🔗 Integration Points

Works seamlessly with:
- **Claude.com** - Upload and use directly
- **Claude Code** - For testing prompts
- **Agent SDK** - For programmatic use
- **Files API** - For analyzing documentation
- **Vision** - For multimodal design
- **Extended Thinking** - For complex reasoning

---

## 📖 Learning Paths

### Beginner (1-2 hours)
1. Read: README.md
2. Read: BEST_PRACTICES.md (Core Principles)
3. Review: EXAMPLES.md (Examples 1-3)
4. Try: Create a simple prompt

### Intermediate (2-4 hours)
1. Read: TECHNIQUES.md (Sections 1-4)
2. Review: EXAMPLES.md (Examples 4-7)
3. Read: TROUBLESHOOTING.md
4. Try: Refine an existing prompt

### Advanced (4+ hours)
1. Read: TECHNIQUES.md (All sections)
2. Review: EXAMPLES.md (All examples)
3. Read: BEST_PRACTICES.md (All sections)
4. Try: Combine multiple techniques

---

## 🎁 What You Get

### Immediate Benefits
- Expert prompt engineering guidance
- Real-world examples and templates
- Troubleshooting help
- Best practices reference
- Anti-pattern recognition

### Long-Term Benefits
- Improved prompt quality
- Faster iteration cycles
- Better consistency
- Reduced token usage
- More effective AI interactions

---

## 🚀 Next Steps

1. **Navigate to the folder**
   ```
   ~/Documents/prompt-engineering-expert/
   ```

2. **Upload the skill** to Claude.com
   - Click "+" → Upload Skill → Select folder

3. **Start using it**
   - Ask Claude to review your prompts
   - Request custom instructions
   - Get troubleshooting help

4. **Explore the documentation**
   - Start with README.md
   - Review examples
   - Learn advanced techniques

5. **Share with your team**
   - Collaborate on prompt engineering
   - Build better prompts together
   - Improve AI interactions

---

## 📞 Support Resources

### Within the Skill
- Comprehensive documentation
- Real-world examples
- Troubleshooting guides
- Best practice checklists
- Quick reference tables

### External Resources
- Claude Docs: https://docs.claude.com
- Anthropic Blog: https://www.anthropic.com/blog
- Claude Cookbooks: https://github.com/anthropics/claude-cookbooks

---

## 🎉 You're All Set!

Your **Prompt Engineering Expert Skill** is complete and ready to use!

### Quick Start
1. Open `~/Documents/prompt-engineering-expert/`
2. Read `GETTING_STARTED.md` for upload instructions
3. Upload to Claude.com
4. Start improving your prompts!
FILE:README.md
# README - Prompt Engineering Expert Skill

## Overview

The **Prompt Engineering Expert** skill equips Claude with deep expertise in prompt engineering, custom instructions design, and prompt optimization. This comprehensive skill provides guidance on crafting effective AI prompts, designing agent instructions, and iteratively improving prompt performance.

## What This Skill Provides

### Core Expertise
- **Prompt Writing Best Practices**: Clear, direct prompts with proper structure
- **Advanced Techniques**: Chain-of-thought, few-shot prompting, XML tags, role-based prompting
- **Custom Instructions**: System prompts and agent instructions design
- **Optimization**: Analyzing and refining existing prompts
- **Evaluation**: Testing frameworks and success criteria
- **Anti-Patterns**: Identifying and correcting common mistakes
- **Multimodal**: Vision, embeddings, and file-based prompting

### Key Capabilities

1. **Prompt Analysis**
   - Review existing prompts
   - Identify improvement opportunities
   - Spot anti-patterns and issues
   - Suggest specific refinements

2. **Prompt Generation**
   - Create new prompts from scratch
   - Design for specific use cases
   - Ensure clarity and effectiveness
   - Optimize for consistency

3. **Custom Instructions**
   - Design system prompts
   - Create agent instructions
   - Define behavioral guidelines
   - Set appropriate constraints

4. **Best Practice Guidance**
   - Explain prompt engineering principles
   - Teach advanced techniques
   - Share real-world examples
   - Provide implementation guidance

5. **Testing & Validation**
   - Develop test cases
   - Define success criteria
   - Evaluate prompt performance
   - Identify edge cases

## How to Use This Skill

### For Prompt Analysis
```
"Review this prompt and suggest improvements:
[YOUR PROMPT]

Focus on: clarity, specificity, format, and consistency."
```

### For Prompt Generation
```
"Create a prompt that:
- [Requirement 1]
- [Requirement 2]
- [Requirement 3]

The prompt should handle [use cases]."
```

### For Custom Instructions
```
"Design custom instructions for an agent that:
- [Role/expertise]
- [Key responsibilities]
- [Behavioral guidelines]"
```

### For Troubleshooting
```
"This prompt isn't working well:
[PROMPT]

Issues: [DESCRIBE ISSUES]

How can I fix it?"
```

## Skill Structure

```
prompt-engineering-expert/
├── SKILL.md                 # Skill metadata
├── CLAUDE.md               # Main instructions
├── README.md               # This file
├── docs/
│   ├── BEST_PRACTICES.md   # Best practices guide
│   ├── TECHNIQUES.md       # Advanced techniques
│   └── TROUBLESHOOTING.md  # Common issues & fixes
└── examples/
    └── EXAMPLES.md         # Real-world examples
```

## Key Concepts

### Clarity
- Explicit objectives
- Precise language
- Concrete examples
- Logical structure

### Conciseness
- Focused content
- No redundancy
- Progressive disclosure
- Token efficiency

### Consistency
- Defined constraints
- Specified format
- Clear guidelines
- Repeatable results

### Completeness
- Sufficient context
- Edge case handling
- Success criteria
- Error handling

## Common Use Cases

### 1. Refining Vague Prompts
Transform unclear prompts into specific, actionable ones.

### 2. Creating Specialized Prompts
Design prompts for specific domains or tasks.

### 3. Designing Agent Instructions
Create custom instructions for AI agents and skills.

### 4. Optimizing for Consistency
Improve reliability and reduce variability.

### 5. Debugging Prompt Issues
Identify and fix problems with existing prompts.

### 6. Teaching Best Practices
Learn prompt engineering principles and techniques.

### 7. Building Evaluation Frameworks
Develop test cases and success criteria.

### 8. Multimodal Prompting
Design prompts for vision, embeddings, and files.

## Best Practices Summary

### Do's ✅
- Be clear and specific
- Provide examples
- Specify format
- Define constraints
- Test thoroughly
- Document assumptions
- Use progressive disclosure
- Handle edge cases

### Don'ts ❌
- Be vague or ambiguous
- Assume understanding
- Skip format specification
- Ignore edge cases
- Over-specify constraints
- Use jargon without explanation
- Hardcode values
- Ignore error handling

## Advanced Topics

### Chain-of-Thought Prompting
Encourage step-by-step reasoning for complex tasks.

### Few-Shot Learning
Use examples to guide behavior without explicit instructions.

### Structured Output
Use XML tags for clarity and parsing.

### Role-Based Prompting
Assign expertise to guide behavior.

### Prompt Chaining
Break complex tasks into sequential prompts.

### Context Management
Optimize token usage and clarity.

### Multimodal Integration
Work with images, files, and embeddings.

## Limitations

- **Analysis Only**: Doesn't execute code or run actual prompts
- **No Real-Time Data**: Can't access external APIs or current data
- **Best Practices Based**: Recommendations based on established patterns
- **Testing Required**: Suggestions should be validated with actual use cases
- **Human Judgment**: Doesn't replace human expertise in critical applications

## Integration with Other Skills

This skill works well with:
- **Claude Code**: For testing and iterating on prompts
- **Agent SDK**: For implementing custom instructions
- **Files API**: For analyzing prompt documentation
- **Vision**: For multimodal prompt design
- **Extended Thinking**: For complex prompt reasoning

## Getting Started

### Quick Start
1. Share your prompt or describe your need
2. Receive analysis and recommendations
3. Implement suggested improvements
4. Test and validate
5. Iterate as needed

### For Beginners
- Start with "BEST_PRACTICES.md"
- Review "EXAMPLES.md" for real-world cases
- Try simple prompts first
- Gradually increase complexity

### For Advanced Users
- Explore "TECHNIQUES.md" for advanced methods
- Review "TROUBLESHOOTING.md" for edge cases
- Combine multiple techniques
- Build custom frameworks

## Documentation

### Main Documents
- **BEST_PRACTICES.md**: Comprehensive best practices guide
- **TECHNIQUES.md**: Advanced prompt engineering techniques
- **TROUBLESHOOTING.md**: Common issues and solutions
- **EXAMPLES.md**: Real-world examples and templates

### Quick References
- Naming conventions
- File structure
- YAML frontmatter
- Token budgets
- Checklists

## Support & Resources

### Within This Skill
- Detailed documentation
- Real-world examples
- Troubleshooting guides
- Best practice checklists
- Quick reference tables

### External Resources
- Claude Documentation: https://docs.claude.com
- Anthropic Blog: https://www.anthropic.com/blog
- Claude Cookbooks: https://github.com/anthropics/claude-cookbooks
- Prompt Engineering Guide: https://www.promptingguide.ai

## Version History

### v1.0 (Current)
- Initial release
- Core expertise areas
- Best practices documentation
- Advanced techniques guide
- Troubleshooting guide
- Real-world examples

## Contributing

This skill is designed to evolve. Feedback and suggestions for improvement are welcome.

## License

This skill is provided as part of the Claude ecosystem.

---

## Quick Links

- [Best Practices Guide](docs/BEST_PRACTICES.md)
- [Advanced Techniques](docs/TECHNIQUES.md)
- [Troubleshooting Guide](docs/TROUBLESHOOTING.md)
- [Examples & Templates](examples/EXAMPLES.md)

---

**Ready to improve your prompts?** Start by sharing your current prompt or describing what you need help with!
FILE:SUMMARY.md
# Prompt Engineering Expert Skill - Summary

## What Was Created

A comprehensive Claude Skill for **prompt engineering expertise** with deep knowledge of:
- Prompt writing best practices
- Custom instructions design
- Prompt optimization and refinement
- Advanced techniques (CoT, few-shot, XML tags, etc.)
- Evaluation frameworks and testing
- Anti-pattern recognition
- Multimodal prompting

## Skill Structure

```
~/Documents/prompt-engineering-expert/
├── SKILL.md                    # Skill metadata & overview
├── CLAUDE.md                   # Main skill instructions
├── README.md                   # User guide & getting started
├── docs/
│   ├── BEST_PRACTICES.md       # Comprehensive best practices (from official docs)
│   ├── TECHNIQUES.md           # Advanced techniques guide
│   └── TROUBLESHOOTING.md      # Common issues & solutions
└── examples/
    └── EXAMPLES.md             # 10 real-world examples & templates
```

## Key Files

### 1. **SKILL.md** (Overview)
- High-level description
- Key capabilities
- Use cases
- Limitations

### 2. **CLAUDE.md** (Main Instructions)
- Core expertise areas (7 major areas)
- Key capabilities (8 capabilities)
- Use cases (9 use cases)
- Skill limitations
- Integration notes

### 3. **README.md** (User Guide)
- Overview and what's provided
- How to use the skill
- Skill structure
- Key concepts
- Common use cases
- Best practices summary
- Getting started guide

### 4. **docs/BEST_PRACTICES.md** (Best Practices)
- Core principles (clarity, conciseness, degrees of freedom)
- Advanced techniques (CoT, few-shot, XML, role-based, prefilling, chaining)
- Custom instructions design
- Skill structure best practices
- Evaluation & testing
- Anti-patterns to avoid
- Workflows and feedback loops
- Content guidelines
- Multimodal prompting
- Development workflow
- Comprehensive checklist

### 5. **docs/TECHNIQUES.md** (Advanced Techniques)
- Chain-of-Thought prompting (with examples)
- Few-Shot learning (1-shot, 2-shot, multi-shot)
- Structured output with XML tags
- Role-based prompting
- Prefilling responses
- Prompt chaining
- Context management
- Multimodal prompting
- Combining techniques
- Anti-patterns

### 6. **docs/TROUBLESHOOTING.md** (Troubleshooting)
- 8 common issues with solutions:
  1. Inconsistent outputs
  2. Hallucinations
  3. Vague responses
  4. Wrong length
  5. Wrong format
  6. Refuses to respond
  7. Prompt too long
  8. Doesn't generalize
- Debugging workflow
- Quick reference table
- Testing checklist

### 7. **examples/EXAMPLES.md** (Real-World Examples)
- 10 practical examples:
  1. Refining vague prompts
  2. Custom instructions for agents
  3. Few-shot classification
  4. Chain-of-thought analysis
  5. XML-structured prompts
  6. Iterative refinement
  7. Anti-pattern recognition
  8. Testing framework
  9. Skill metadata template
  10. Optimization checklist

## Core Expertise Areas

1. **Prompt Writing Best Practices**
   - Clarity and directness
   - Structure and formatting
   - Specificity
   - Context management
   - Tone and style

2. **Advanced Prompt Engineering Techniques**
   - Chain-of-Thought (CoT) prompting
   - Few-Shot prompting
   - XML tags
   - Role-based prompting
   - Prefilling
   - Prompt chaining

3. **Custom Instructions & System Prompts**
   - System prompt design
   - Custom instructions
   - Behavioral guidelines
   - Personality and voice
   - Scope definition

4. **Prompt Optimization & Refinement**
   - Performance analysis
   - Iterative improvement
   - A/B testing
   - Consistency enhancement
   - Token optimization

5. **Anti-Patterns & Common Mistakes**
   - Vagueness
   - Contradictions
   - Over-specification
   - Hallucination risks
   - Context leakage
   - Jailbreak vulnerabilities

6. **Evaluation & Testing**
   - Success criteria definition
   - Test case development
   - Failure analysis
   - Regression testing
   - Edge case handling

7. **Multimodal & Advanced Prompting**
   - Vision prompting
   - File-based prompting
   - Embeddings integration
   - Tool use prompting
   - Extended thinking

## Key Capabilities

1. **Prompt Analysis** - Review and improve existing prompts
2. **Prompt Generation** - Create new prompts from scratch
3. **Prompt Refinement** - Iteratively improve prompts
4. **Custom Instruction Design** - Create specialized instructions
5. **Best Practice Guidance** - Teach prompt engineering principles
6. **Anti-Pattern Recognition** - Identify and correct mistakes
7. **Testing Strategy** - Develop evaluation frameworks
8. **Documentation** - Create clear usage documentation

## How to Use This Skill

### For Prompt Analysis
```
"Review this prompt and suggest improvements:
[YOUR PROMPT]"
```

### For Prompt Generation
```
"Create a prompt that:
- [Requirement 1]
- [Requirement 2]
- [Requirement 3]"
```

### For Custom Instructions
```
"Design custom instructions for an agent that:
- [Role/expertise]
- [Key responsibilities]"
```

### For Troubleshooting
```
"This prompt isn't working:
[PROMPT]

Issues: [DESCRIBE ISSUES]

How can I fix it?"
```

## Best Practices Included

### Do's ✅
- Be clear and specific
- Provide examples
- Specify format
- Define constraints
- Test thoroughly
- Document assumptions
- Use progressive disclosure
- Handle edge cases

### Don'ts ❌
- Be vague or ambiguous
- Assume understanding
- Skip format specification
- Ignore edge cases
- Over-specify constraints
- Use jargon without explanation
- Hardcode values
- Ignore error handling

## Documentation Quality

- **Comprehensive**: Covers all major aspects of prompt engineering
- **Practical**: Includes real-world examples and templates
- **Well-Organized**: Clear structure with progressive disclosure
- **Actionable**: Specific guidance with step-by-step instructions
- **Tested**: Based on official Anthropic documentation
- **Reusable**: Templates and checklists for common tasks

## Integration Points

Works well with:
- Claude Code (for testing prompts)
- Agent SDK (for implementing instructions)
- Files API (for analyzing documentation)
- Vision capabilities (for multimodal design)
- Extended thinking (for complex reasoning)

## Next Steps

1. **Upload the skill** to Claude using the Skills API or Claude Code
2. **Test with sample prompts** to verify functionality
3. **Iterate based on feedback** to refine and improve
4. **Share with team** for collaborative prompt engineering
5. **Extend as needed** with domain-specific examples
FILE:INDEX.md
# Prompt Engineering Expert Skill - Complete Index

## 📋 Quick Navigation

### Getting Started
- **[README.md](README.md)** - Start here! Overview, how to use, and quick start guide
- **[SUMMARY.md](SUMMARY.md)** - What was created and how to use it

### Core Skill Files
- **[SKILL.md](SKILL.md)** - Skill metadata and capabilities overview
- **[CLAUDE.md](CLAUDE.md)** - Main skill instructions and expertise areas

### Documentation
- **[docs/BEST_PRACTICES.md](docs/BEST_PRACTICES.md)** - Comprehensive best practices guide
- **[docs/TECHNIQUES.md](docs/TECHNIQUES.md)** - Advanced prompt engineering techniques
- **[docs/TROUBLESHOOTING.md](docs/TROUBLESHOOTING.md)** - Common issues and solutions

### Examples & Templates
- **[examples/EXAMPLES.md](examples/EXAMPLES.md)** - 10 real-world examples and templates

---

## 📚 What's Included

### Expertise Areas (7 Major Areas)
1. Prompt Writing Best Practices
2. Advanced Prompt Engineering Techniques
3. Custom Instructions & System Prompts
4. Prompt Optimization & Refinement
5. Anti-Patterns & Common Mistakes
6. Evaluation & Testing
7. Multimodal & Advanced Prompting

### Key Capabilities (8 Capabilities)
1. Prompt Analysis
2. Prompt Generation
3. Prompt Refinement
4. Custom Instruction Design
5. Best Practice Guidance
6. Anti-Pattern Recognition
7. Testing Strategy
8. Documentation

### Use Cases (9 Use Cases)
1. Refining vague or ineffective prompts
2. Creating specialized system prompts
3. Designing custom instructions for agents
4. Optimizing for consistency and reliability
5. Teaching prompt engineering best practices
6. Debugging prompt performance issues
7. Creating prompt templates for workflows
8. Improving efficiency and token usage
9. Developing evaluation frameworks

---

## 🎯 How to Use This Skill

### For Prompt Analysis
```
"Review this prompt and suggest improvements:
[YOUR PROMPT]

Focus on: clarity, specificity, format, and consistency."
```

### For Prompt Generation
```
"Create a prompt that:
- [Requirement 1]
- [Requirement 2]
- [Requirement 3]

The prompt should handle [use cases]."
```

### For Custom Instructions
```
"Design custom instructions for an agent that:
- [Role/expertise]
- [Key responsibilities]
- [Behavioral guidelines]"
```

### For Troubleshooting
```
"This prompt isn't working well:
[PROMPT]

Issues: [DESCRIBE ISSUES]

How can I fix it?"
```

---

## 📖 Documentation Structure

### BEST_PRACTICES.md (Comprehensive Guide)
- Core principles (clarity, conciseness, degrees of freedom)
- Advanced techniques (CoT, few-shot, XML, role-based, prefilling, chaining)
- Custom instructions design
- Skill structure best practices
- Evaluation & testing frameworks
- Anti-patterns to avoid
- Workflows and feedback loops
- Content guidelines
- Multimodal prompting
- Development workflow
- Complete checklist

### TECHNIQUES.md (Advanced Methods)
- Chain-of-Thought prompting with examples
- Few-Shot learning (1-shot, 2-shot, multi-shot)
- Structured output with XML tags
- Role-based prompting
- Prefilling responses
- Prompt chaining
- Context management
- Multimodal prompting
- Combining techniques
- Anti-patterns

### TROUBLESHOOTING.md (Problem Solving)
- 8 common issues with solutions
- Debugging workflow
- Quick reference table
- Testing checklist

### EXAMPLES.md (Real-World Cases)
- 10 practical examples
- Before/after comparisons
- Templates and frameworks
- Optimization checklists

---

## ✅ Best Practices Summary

### Do's ✅
- Be clear and specific
- Provide examples
- Specify format
- Define constraints
- Test thoroughly
- Document assumptions
- Use progressive disclosure
- Handle edge cases

### Don'ts ❌
- Be vague or ambiguous
- Assume understanding
- Skip format specification
- Ignore edge cases
- Over-specify constraints
- Use jargon without explanation
- Hardcode values
- Ignore error handling

---

## 🚀 Getting Started

### Step 1: Read the Overview
Start with **README.md** to understand what this skill provides.

### Step 2: Learn Best Practices
Review **docs/BEST_PRACTICES.md** for foundational knowledge.

### Step 3: Explore Examples
Check **examples/EXAMPLES.md** for real-world use cases.

### Step 4: Try It Out
Share your prompt or describe your need to get started.

### Step 5: Troubleshoot
Use **docs/TROUBLESHOOTING.md** if you encounter issues.

---

## 🔧 Advanced Topics

### Chain-of-Thought Prompting
Encourage step-by-step reasoning for complex tasks.
→ See: TECHNIQUES.md, Section 1

### Few-Shot Learning
Use examples to guide behavior without explicit instructions.
→ See: TECHNIQUES.md, Section 2

### Structured Output
Use XML tags for clarity and parsing.
→ See: TECHNIQUES.md, Section 3

### Role-Based Prompting
Assign expertise to guide behavior.
→ See: TECHNIQUES.md, Section 4

### Prompt Chaining
Break complex tasks into sequential prompts.
→ See: TECHNIQUES.md, Section 6

### Context Management
Optimize token usage and clarity.
→ See: TECHNIQUES.md, Section 7

### Multimodal Integration
Work with images, files, and embeddings.
→ See: TECHNIQUES.md, Section 8

---

## 📊 File Structure

```
prompt-engineering-expert/
├── INDEX.md                    # This file
├── SUMMARY.md                  # What was created
├── README.md                   # User guide & getting started
├── SKILL.md                    # Skill metadata
├── CLAUDE.md                   # Main instructions
├── docs/
│   ├── BEST_PRACTICES.md       # Best practices guide
│   ├── TECHNIQUES.md           # Advanced techniques
│   └── TROUBLESHOOTING.md      # Common issues & solutions
└── examples/
    └── EXAMPLES.md             # Real-world examples
```

---

## 🎓 Learning Path

### Beginner
1. Read: README.md
2. Read: BEST_PRACTICES.md (Core Principles section)
3. Review: EXAMPLES.md (Examples 1-3)
4. Try: Create a simple prompt

### Intermediate
1. Read: TECHNIQUES.md (Sections 1-4)
2. Review: EXAMPLES.md (Examples 4-7)
3. Read: TROUBLESHOOTING.md
4. Try: Refine an existing prompt

### Advanced
1. Read: TECHNIQUES.md (Sections 5-8)
2. Review: EXAMPLES.md (Examples 8-10)
3. Read: BEST_PRACTICES.md (Advanced sections)
4. Try: Combine multiple techniques

---

## 🔗 Integration Points

This skill works well with:
- **Claude Code** - For testing and iterating on prompts
- **Agent SDK** - For implementing custom instructions
- **Files API** - For analyzing prompt documentation
- **Vision** - For multimodal prompt design
- **Extended Thinking** - For complex prompt reasoning

---

## 📝 Key Concepts

### Clarity
- Explicit objectives
- Precise language
- Concrete examples
- Logical structure

### Conciseness
- Focused content
- No redundancy
- Progressive disclosure
- Token efficiency

### Consistency
- Defined constraints
- Specified format
- Clear guidelines
- Repeatable results

### Completeness
- Sufficient context
- Edge case handling
- Success criteria
- Error handling

---

## ⚠ Limitations

- **Analysis Only**: Doesn't execute code or run actual prompts
- **No Real-Time Data**: Can't access external APIs or current data
- **Best Practices Based**: Recommendations based on established patterns
- **Testing Required**: Suggestions should be validated with actual use cases
- **Human Judgment**: Doesn't replace human expertise in critical applications

---

## 🎯 Common Use Cases

### 1. Refining Vague Prompts
Transform unclear prompts into specific, actionable ones.
→ See: EXAMPLES.md, Example 1

### 2. Creating Specialized Prompts
Design prompts for specific domains or tasks.
→ See: EXAMPLES.md, Example 2

### 3. Designing Agent Instructions
Create custom instructions for AI agents and skills.
→ See: EXAMPLES.md, Example 2

### 4. Optimizing for Consistency
Improve reliability and reduce variability.
→ See: BEST_PRACTICES.md, Skill Structure section

### 5. Debugging Prompt Issues
Identify and fix problems with existing prompts.
→ See: TROUBLESHOOTING.md

### 6. Teaching Best Practices
Learn prompt engineering principles and techniques.
→ See: BEST_PRACTICES.md, TECHNIQUES.md

### 7. Building Evaluation Frameworks
Develop test cases and success criteria.
→ See: BEST_PRACTICES.md, Evaluation & Testing section

### 8. Multimodal Prompting
Design prompts for vision, embeddings, and files.
→ See: TECHNIQUES.md, Section 8

---

## 📞 Support & Resources

### Within This Skill
- Detailed documentation
- Real-world examples
- Troubleshooting guides
- Best practice checklists
- Quick reference tables

### External Resources
- Claude Documentation: https://docs.claude.com
- Anthropic Blog: https://www.anthropic.com/blog
- Claude Cookbooks: https://github.com/anthropics/claude-cookbooks
- Prompt Engineering Guide: https://www.promptingguide.ai

---

## 🚀 Next Steps

1. **Explore the documentation** - Start with README.md
2. **Review examples** - Check examples/EXAMPLES.md
3. **Try it out** - Share your prompt or describe your need
4. **Iterate** - Use feedback to improve
5. **Share** - Help others with their prompts
FILE:BEST_PRACTICES.md
# Prompt Engineering Expert - Best Practices Guide

This document synthesizes best practices from Anthropic's official documentation and the Claude Cookbooks to create a comprehensive prompt engineering skill.

## Core Principles for Prompt Engineering

### 1. Clarity and Directness
- **Be explicit**: State exactly what you want Claude to do
- **Avoid ambiguity**: Use precise language that leaves no room for misinterpretation
- **Use concrete examples**: Show, don't just tell
- **Structure logically**: Organize information hierarchically

### 2. Conciseness
- **Respect context windows**: Keep prompts focused and relevant
- **Remove redundancy**: Eliminate unnecessary repetition
- **Progressive disclosure**: Provide details only when needed
- **Token efficiency**: Optimize for both quality and cost

### 3. Appropriate Degrees of Freedom
- **Define constraints**: Set clear boundaries for what Claude should/shouldn't do
- **Specify format**: Be explicit about desired output format
- **Set scope**: Clearly define what's in and out of scope
- **Balance flexibility**: Allow room for Claude's reasoning while maintaining control

## Advanced Prompt Engineering Techniques

### Chain-of-Thought (CoT) Prompting
Encourage step-by-step reasoning for complex tasks:
```
"Let's think through this step by step:
1. First, identify...
2. Then, analyze...
3. Finally, conclude..."
```

### Few-Shot Prompting
Use examples to guide behavior:
- **1-shot**: Single example for simple tasks
- **2-shot**: Two examples for moderate complexity
- **Multi-shot**: Multiple examples for complex patterns

### XML Tags for Structure
Use XML tags for clarity and parsing:
```xml
<task>
  <objective>What you want done</objective>
  <constraints>Limitations and rules</constraints>
  <format>Expected output format</format>
</task>
```

### Role-Based Prompting
Assign expertise to Claude:
```
"You are an expert prompt engineer with deep knowledge of...
Your task is to..."
```

### Prefilling
Start Claude's response to guide format:
```
"Here's my analysis:

Key findings:"
```

### Prompt Chaining
Break complex tasks into sequential prompts:
1. Prompt 1: Analyze input
2. Prompt 2: Process analysis
3. Prompt 3: Generate output

## Custom Instructions & System Prompts

### System Prompt Design
- **Define role**: What expertise should Claude embody?
- **Set tone**: What communication style is appropriate?
- **Establish constraints**: What should Claude avoid?
- **Clarify scope**: What's the domain of expertise?

### Behavioral Guidelines
- **Do's**: Specific behaviors to encourage
- **Don'ts**: Specific behaviors to avoid
- **Edge cases**: How to handle unusual situations
- **Escalation**: When to ask for clarification

## Skill Structure Best Practices

### Naming Conventions
- Use **gerund form** (verb + -ing): "analyzing-financial-statements"
- Use **lowercase with hyphens**: "prompt-engineering-expert"
- Be **descriptive**: Name should indicate capability
- Avoid **generic names**: Be specific about domain

### Writing Effective Descriptions
- **First line**: Clear, concise summary (max 1024 chars)
- **Specificity**: Indicate exact capabilities
- **Use cases**: Mention primary applications
- **Avoid vagueness**: Don't use "helps with" or "assists in"

### Progressive Disclosure Patterns

**Pattern 1: High-level guide with references**
- Start with overview
- Link to detailed sections
- Organize by complexity

**Pattern 2: Domain-specific organization**
- Group by use case
- Separate concerns
- Clear navigation

**Pattern 3: Conditional details**
- Show details based on context
- Provide examples for each path
- Avoid overwhelming options

### File Structure
```
skill-name/
├── SKILL.md (required metadata)
├── CLAUDE.md (main instructions)
├── reference-guide.md (detailed info)
├── examples.md (use cases)
└── troubleshooting.md (common issues)
```

## Evaluation & Testing

### Success Criteria Definition
- **Measurable**: Define what "success" looks like
- **Specific**: Avoid vague metrics
- **Testable**: Can be verified objectively
- **Realistic**: Achievable with the prompt

### Test Case Development
- **Happy path**: Normal, expected usage
- **Edge cases**: Boundary conditions
- **Error cases**: Invalid inputs
- **Stress tests**: Complex scenarios

### Failure Analysis
- **Why did it fail?**: Root cause analysis
- **Pattern recognition**: Identify systematic issues
- **Refinement**: Adjust prompt accordingly

## Anti-Patterns to Avoid

### Common Mistakes
- **Vagueness**: "Help me with this task" (too vague)
- **Contradictions**: Conflicting requirements
- **Over-specification**: Too many constraints
- **Hallucination risks**: Prompts that encourage false information
- **Context leakage**: Unintended information exposure
- **Jailbreak vulnerabilities**: Prompts susceptible to manipulation

### Windows-Style Paths
- ❌ Use: `C:\Users\Documents\file.txt`
- ✅ Use: `/Users/Documents/file.txt` or `~/Documents/file.txt`

### Too Many Options
- Avoid offering 10+ choices
- Limit to 3-5 clear alternatives
- Use progressive disclosure for complex options

## Workflows and Feedback Loops

### Use Workflows for Complex Tasks
- Break into logical steps
- Define inputs/outputs for each step
- Implement feedback mechanisms
- Allow for iteration

### Implement Feedback Loops
- Request clarification when needed
- Validate intermediate results
- Adjust based on feedback
- Confirm understanding

## Content Guidelines

### Avoid Time-Sensitive Information
- Don't hardcode dates
- Use relative references ("current year")
- Provide update mechanisms
- Document when information was current

### Use Consistent Terminology
- Define key terms once
- Use consistently throughout
- Avoid synonyms for same concept
- Create glossary for complex domains

## Multimodal & Advanced Prompting

### Vision Prompting
- Describe what Claude should analyze
- Specify output format
- Provide context about images
- Ask for specific details

### File-Based Prompting
- Specify file types accepted
- Describe expected structure
- Provide parsing instructions
- Handle errors gracefully

### Extended Thinking
- Use for complex reasoning
- Allow more processing time
- Request detailed explanations
- Leverage for novel problems

## Skill Development Workflow

### Build Evaluations First
1. Define success criteria
2. Create test cases
3. Establish baseline
4. Measure improvements

### Develop Iteratively with Claude
1. Start with simple version
2. Test and gather feedback
3. Refine based on results
4. Repeat until satisfied

### Observe How Claude Navigates Skills
- Watch how Claude discovers content
- Note which sections are used
- Identify confusing areas
- Optimize based on usage patterns

## YAML Frontmatter Requirements

```yaml
---
name: skill-name
description: Clear, concise description (max 1024 chars)
---
```

## Token Budget Considerations

- **Skill metadata**: ~100-200 tokens
- **Main instructions**: ~500-1000 tokens
- **Reference files**: ~1000-5000 tokens each
- **Examples**: ~500-1000 tokens each
- **Total budget**: Varies by use case

## Checklist for Effective Skills

### Core Quality
- [ ] Clear, specific name (gerund form)
- [ ] Concise description (1-2 sentences)
- [ ] Well-organized structure
- [ ] Progressive disclosure implemented
- [ ] Consistent terminology
- [ ] No time-sensitive information

### Content
- [ ] Clear use cases defined
- [ ] Examples provided
- [ ] Edge cases documented
- [ ] Limitations stated
- [ ] Troubleshooting guide included

### Testing
- [ ] Test cases created
- [ ] Success criteria defined
- [ ] Edge cases tested
- [ ] Error handling verified
- [ ] Multiple models tested

### Documentation
- [ ] README or overview
- [ ] Usage examples
- [ ] API/integration notes
- [ ] Troubleshooting section
- [ ] Update mechanism documented
FILE:TECHNIQUES.md
# Advanced Prompt Engineering Techniques

## Table of Contents
1. Chain-of-Thought Prompting
2. Few-Shot Learning
3. Structured Output with XML
4. Role-Based Prompting
5. Prefilling Responses
6. Prompt Chaining
7. Context Management
8. Multimodal Prompting

## 1. Chain-of-Thought (CoT) Prompting

### What It Is
Encouraging Claude to break down complex reasoning into explicit steps before providing a final answer.

### When to Use
- Complex reasoning tasks
- Multi-step problems
- Tasks requiring justification
- When consistency matters

### Basic Structure
```
Let's think through this step by step:

Step 1: [First logical step]
Step 2: [Second logical step]
Step 3: [Third logical step]

Therefore: [Conclusion]
```

### Example
```
Problem: A store sells apples for $2 each and oranges for $3 each.
If I buy 5 apples and 3 oranges, how much do I spend?

Let's think through this step by step:

Step 1: Calculate apple cost
- 5 apples × $2 per apple = $10

Step 2: Calculate orange cost
- 3 oranges × $3 per orange = $9

Step 3: Calculate total
- $10 + $9 = $19

Therefore: You spend $19 total.
```

### Benefits
- More accurate reasoning
- Easier to identify errors
- Better for complex problems
- More transparent logic

## 2. Few-Shot Learning

### What It Is
Providing examples to guide Claude's behavior without explicit instructions.

### Types

#### 1-Shot (Single Example)
Best for: Simple, straightforward tasks
```
Example: "Happy" → Positive
Now classify: "Terrible" →
```

#### 2-Shot (Two Examples)
Best for: Moderate complexity
```
Example 1: "Great product!" → Positive
Example 2: "Doesn't work well" → Negative
Now classify: "It's okay" →
```

#### Multi-Shot (Multiple Examples)
Best for: Complex patterns, edge cases
```
Example 1: "Love it!" → Positive
Example 2: "Hate it" → Negative
Example 3: "It's fine" → Neutral
Example 4: "Could be better" → Neutral
Example 5: "Amazing!" → Positive
Now classify: "Not bad" →
```

### Best Practices
- Use diverse examples
- Include edge cases
- Show correct format
- Order by complexity
- Use realistic examples

## 3. Structured Output with XML Tags

### What It Is
Using XML tags to structure prompts and guide output format.

### Benefits
- Clear structure
- Easy parsing
- Reduced ambiguity
- Better organization

### Common Patterns

#### Task Definition
```xml
<task>
  <objective>What to accomplish</objective>
  <constraints>Limitations and rules</constraints>
  <format>Expected output format</format>
</task>
```

#### Analysis Structure
```xml
<analysis>
  <problem>Define the problem</problem>
  <context>Relevant background</context>
  <solution>Proposed solution</solution>
  <justification>Why this solution</justification>
</analysis>
```

#### Conditional Logic
```xml
<instructions>
  <if condition="input_type == 'question'">
    <then>Provide detailed answer</then>
  </if>
  <if condition="input_type == 'request'">
    <then>Fulfill the request</then>
  </if>
</instructions>
```

## 4. Role-Based Prompting

### What It Is
Assigning Claude a specific role or expertise to guide behavior.

### Structure
```
You are a [ROLE] with expertise in [DOMAIN].

Your responsibilities:
- [Responsibility 1]
- [Responsibility 2]
- [Responsibility 3]

When responding:
- [Guideline 1]
- [Guideline 2]
- [Guideline 3]

Your task: [Specific task]
```

### Examples

#### Expert Consultant
```
You are a senior management consultant with 20 years of experience
in business strategy and organizational transformation.

Your task: Analyze this company's challenges and recommend solutions.
```

#### Technical Architect
```
You are a cloud infrastructure architect specializing in scalable systems.

Your task: Design a system architecture for [requirements].
```

#### Creative Director
```
You are a creative director with expertise in brand storytelling and
visual communication.

Your task: Develop a brand narrative for [product/company].
```

## 5. Prefilling Responses

### What It Is
Starting Claude's response to guide format and tone.

### Benefits
- Ensures correct format
- Sets tone and style
- Guides reasoning
- Improves consistency

### Examples

#### Structured Analysis
```
Prompt: Analyze this market opportunity.

Claude's response should start:
"Here's my analysis of this market opportunity:

Market Size: [Analysis]
Growth Potential: [Analysis]
Competitive Landscape: [Analysis]"
```

#### Step-by-Step Reasoning
```
Prompt: Solve this problem.

Claude's response should start:
"Let me work through this systematically:

1. First, I'll identify the key variables...
2. Then, I'll analyze the relationships...
3. Finally, I'll derive the solution..."
```

#### Formatted Output
```
Prompt: Create a project plan.

Claude's response should start:
"Here's the project plan:

Phase 1: Planning
- Task 1.1: [Description]
- Task 1.2: [Description]

Phase 2: Execution
- Task 2.1: [Description]"
```

## 6. Prompt Chaining

### What It Is
Breaking complex tasks into sequential prompts, using outputs as inputs.

### Structure
```
Prompt 1: Analyze/Extract
↓
Output 1: Structured data
↓
Prompt 2: Process/Transform
↓
Output 2: Processed data
↓
Prompt 3: Generate/Synthesize
↓
Final Output: Result
```

### Example: Document Analysis Pipeline

**Prompt 1: Extract Information**
```
Extract key information from this document:
- Main topic
- Key points (bullet list)
- Important dates
- Relevant entities

Format as JSON.
```

**Prompt 2: Analyze Extracted Data**
```
Analyze this extracted information:
[JSON from Prompt 1]

Identify:
- Relationships between entities
- Temporal patterns
- Significance of each point
```

**Prompt 3: Generate Summary**
```
Based on this analysis:
[Analysis from Prompt 2]

Create an executive summary that:
- Explains the main findings
- Highlights key insights
- Recommends next steps
```

## 7. Context Management

### What It Is
Strategically managing information to optimize token usage and clarity.

### Techniques

#### Progressive Disclosure
```
Start with: High-level overview
Then provide: Relevant details
Finally include: Edge cases and exceptions
```

#### Hierarchical Organization
```
Level 1: Core concept
├── Level 2: Key components
│   ├── Level 3: Specific details
│   └── Level 3: Implementation notes
└── Level 2: Related concepts
```

#### Conditional Information
```
If [condition], include [information]
Else, skip [information]

This reduces unnecessary context.
```

### Best Practices
- Include only necessary context
- Organize hierarchically
- Use references for detailed info
- Summarize before details
- Link related concepts

## 8. Multimodal Prompting

### Vision Prompting

#### Structure
```
Analyze this image:
[IMAGE]

Specifically, identify:
1. [What to look for]
2. [What to analyze]
3. [What to extract]

Format your response as:
[Desired format]
```

#### Example
```
Analyze this chart:
[CHART IMAGE]

Identify:
1. Main trends
2. Anomalies or outliers
3. Predictions for next period

Format as a structured report.
```

### File-Based Prompting

#### Structure
```
Analyze this document:
[FILE]

Extract:
- [Information type 1]
- [Information type 2]
- [Information type 3]

Format as:
[Desired format]
```

#### Example
```
Analyze this PDF financial report:
[PDF FILE]

Extract:
- Revenue by quarter
- Expense categories
- Profit margins

Format as a comparison table.
```

### Embeddings Integration

#### Structure
```
Using these embeddings:
[EMBEDDINGS DATA]

Find:
- Most similar items
- Clusters or groups
- Outliers

Explain the relationships.
```

## Combining Techniques

### Example: Complex Analysis Prompt

```xml
<prompt>
  <role>
    You are a senior data analyst with expertise in business intelligence.
  </role>

  <task>
    Analyze this sales data and provide insights.
  </task>

  <instructions>
    Let's think through this step by step:

    Step 1: Data Overview
    - What does the data show?
    - What time period does it cover?
    - What are the key metrics?

    Step 2: Trend Analysis
    - What patterns emerge?
    - Are there seasonal trends?
    - What's the growth trajectory?

    Step 3: Comparative Analysis
    - How does this compare to benchmarks?
    - Which segments perform best?
    - Where are the opportunities?

    Step 4: Recommendations
    - What actions should we take?
    - What are the priorities?
    - What's the expected impact?
  </instructions>

  <format>
    <executive_summary>2-3 sentences</executive_summary>
    <key_findings>Bullet points</key_findings>
    <detailed_analysis>Structured sections</detailed_analysis>
    <recommendations>Prioritized list</recommendations>
  </format>
</prompt>
```

## Anti-Patterns to Avoid

### ❌ Vague Chaining
```
"Analyze this, then summarize it, then give me insights."
```

### ✅ Clear Chaining
```
"Step 1: Extract key metrics from the data
Step 2: Compare to industry benchmarks
Step 3: Identify top 3 opportunities
Step 4: Recommend prioritized actions"
```

### ❌ Unclear Role
```
"Act like an expert and help me."
```

### ✅ Clear Role
```
"You are a senior product manager with 10 years of experience
in SaaS companies. Your task is to..."
```

### ❌ Ambiguous Format
```
"Give me the results in a nice format."
```

### ✅ Clear Format
```
"Format as a table with columns: Metric, Current, Target, Gap"
```
FILE:TROUBLESHOOTING.md
# Troubleshooting Guide

## Common Prompt Issues and Solutions

### Issue 1: Inconsistent Outputs

**Symptoms:**
- Same prompt produces different results
- Outputs vary in format or quality
- Unpredictable behavior

**Root Causes:**
- Ambiguous instructions
- Missing constraints
- Insufficient examples
- Unclear success criteria

**Solutions:**
```
1. Add specific format requirements
2. Include multiple examples
3. Define constraints explicitly
4. Specify output structure with XML tags
5. Use role-based prompting for consistency
```

**Example Fix:**
```
❌ Before: "Summarize this article"

✅ After: "Summarize this article in exactly 3 bullet points,
each 1-2 sentences. Focus on key findings and implications."
```

---

### Issue 2: Hallucinations or False Information

**Symptoms:**
- Claude invents facts
- Confident but incorrect statements
- Made-up citations or data

**Root Causes:**
- Prompts that encourage speculation
- Lack of grounding in facts
- Insufficient context
- Ambiguous questions

**Solutions:**
```
1. Ask Claude to cite sources
2. Request confidence levels
3. Ask for caveats and limitations
4. Provide factual context
5. Ask "What don't you know?"
```

**Example Fix:**
```
❌ Before: "What will happen to the market next year?"

✅ After: "Based on current market data, what are 3 possible
scenarios for next year? For each, explain your reasoning and
note your confidence level (high/medium/low)."
```

---

### Issue 3: Vague or Unhelpful Responses

**Symptoms:**
- Generic answers
- Lacks specificity
- Doesn't address the real question
- Too high-level

**Root Causes:**
- Vague prompt
- Missing context
- Unclear objective
- No format specification

**Solutions:**
```
1. Be more specific in the prompt
2. Provide relevant context
3. Specify desired output format
4. Give examples of good responses
5. Define success criteria
```

**Example Fix:**
```
❌ Before: "How can I improve my business?"

✅ After: "I run a SaaS company with $2M ARR. We're losing
customers to competitors. What are 3 specific strategies to
improve retention? For each, explain implementation steps and
expected impact."
```

---

### Issue 4: Too Long or Too Short Responses

**Symptoms:**
- Response is too verbose
- Response is too brief
- Doesn't match expectations
- Wastes tokens

**Root Causes:**
- No length specification
- Unclear scope
- Missing format guidance
- Ambiguous detail level

**Solutions:**
```
1. Specify word/sentence count
2. Define scope clearly
3. Use format templates
4. Provide examples
5. Request specific detail level
```

**Example Fix:**
```
❌ Before: "Explain machine learning"

✅ After: "Explain machine learning in 2-3 paragraphs for
someone with no technical background. Focus on practical
applications, not theory."
```

---

### Issue 5: Wrong Output Format

**Symptoms:**
- Output format doesn't match needs
- Can't parse the response
- Incompatible with downstream tools
- Requires manual reformatting

**Root Causes:**
- No format specification
- Ambiguous format request
- Format not clearly demonstrated
- Missing examples

**Solutions:**
```
1. Specify exact format (JSON, CSV, table, etc.)
2. Provide format examples
3. Use XML tags for structure
4. Request specific fields
5. Show before/after examples
```

**Example Fix:**
```
❌ Before: "List the top 5 products"

✅ After: "List the top 5 products in JSON format:
{
  \"products\": [
    {\"name\": \"...\", \"revenue\": \"...\", \"growth\": \"...\"}
  ]
}"
```

---

### Issue 6: Claude Refuses to Respond

**Symptoms:**
- "I can't help with that"
- Declines to answer
- Suggests alternatives
- Seems overly cautious

**Root Causes:**
- Prompt seems harmful
- Ambiguous intent
- Sensitive topic
- Unclear legitimate use case

**Solutions:**
```
1. Clarify legitimate purpose
2. Reframe the question
3. Provide context
4. Explain why you need this
5. Ask for general guidance instead
```

**Example Fix:**
```
❌ Before: "How do I manipulate people?"

✅ After: "I'm writing a novel with a manipulative character.
How would a psychologist describe manipulation tactics?
What are the psychological mechanisms involved?"
```

---

### Issue 7: Prompt is Too Long

**Symptoms:**
- Exceeds context window
- Slow responses
- High token usage
- Expensive to run

**Root Causes:**
- Unnecessary context
- Redundant information
- Too many examples
- Verbose instructions

**Solutions:**
```
1. Remove unnecessary context
2. Consolidate similar points
3. Use references instead of full text
4. Reduce number of examples
5. Use progressive disclosure
```

**Example Fix:**
```
❌ Before: [5000 word prompt with full documentation]

✅ After: [500 word prompt with links to detailed docs]
"See REFERENCE.md for detailed specifications"
```

---

### Issue 8: Prompt Doesn't Generalize

**Symptoms:**
- Works for one case, fails for others
- Brittle to input variations
- Breaks with different data
- Not reusable

**Root Causes:**
- Too specific to one example
- Hardcoded values
- Assumes specific format
- Lacks flexibility

**Solutions:**
```
1. Use variables instead of hardcoded values
2. Handle multiple input formats
3. Add error handling
4. Test with diverse inputs
5. Build in flexibility
```

**Example Fix:**
```
❌ Before: "Analyze this Q3 sales data..."

✅ After: "Analyze this [PERIOD] [METRIC] data.
Handle various formats: CSV, JSON, or table.
If format is unclear, ask for clarification."
```

---

## Debugging Workflow

### Step 1: Identify the Problem
- What's not working?
- How does it fail?
- What's the impact?

### Step 2: Analyze the Prompt
- Is the objective clear?
- Are instructions specific?
- Is context sufficient?
- Is format specified?

### Step 3: Test Hypotheses
- Try adding more context
- Try being more specific
- Try providing examples
- Try changing format

### Step 4: Implement Fix
- Update the prompt
- Test with multiple inputs
- Verify consistency
- Document the change

### Step 5: Validate
- Does it work now?
- Does it generalize?
- Is it efficient?
- Is it maintainable?

---

## Quick Reference: Common Fixes

| Problem | Quick Fix |
|---------|-----------|
| Inconsistent | Add format specification + examples |
| Hallucinations | Ask for sources + confidence levels |
| Vague | Add specific details + examples |
| Too long | Specify word count + format |
| Wrong format | Show exact format example |
| Refuses | Clarify legitimate purpose |
| Too long prompt | Remove unnecessary context |
| Doesn't generalize | Use variables + handle variations |

---

## Testing Checklist

Before deploying a prompt, verify:

- [ ] Objective is crystal clear
- [ ] Instructions are specific
- [ ] Format is specified
- [ ] Examples are provided
- [ ] Edge cases are handled
- [ ] Works with multiple inputs
- [ ] Output is consistent
- [ ] Tokens are optimized
- [ ] Error handling is clear
- [ ] Documentation is complete
FILE:EXAMPLES.md
# Prompt Engineering Expert - Examples

## Example 1: Refining a Vague Prompt

### Before (Ineffective)
```
Help me write a better prompt for analyzing customer feedback.
```

### After (Effective)
```
You are an expert prompt engineer. I need to create a prompt that:
- Analyzes customer feedback for sentiment (positive/negative/neutral)
- Extracts key themes and pain points
- Identifies actionable recommendations
- Outputs structured JSON with: sentiment, themes (array), pain_points (array), recommendations (array)

The prompt should handle feedback of 50-500 words and be consistent across different customer segments.

Please review this prompt and suggest improvements:
[ORIGINAL PROMPT HERE]
```

## Example 2: Custom Instructions for a Data Analysis Agent

```yaml
---
name: data-analysis-agent
description: Specialized agent for financial data analysis and reporting
---

# Data Analysis Agent Instructions

## Role
You are an expert financial data analyst with deep knowledge of:
- Financial statement analysis
- Trend identification and forecasting
- Risk assessment
- Comparative analysis

## Core Behaviors

### Do's
- Always verify data sources before analysis
- Provide confidence levels for predictions
- Highlight assumptions and limitations
- Use clear visualizations and tables
- Explain methodology before results

### Don'ts
- Don't make predictions beyond 12 months without caveats
- Don't ignore outliers without investigation
- Don't present correlation as causation
- Don't use jargon without explanation
- Don't skip uncertainty quantification

## Output Format
Always structure analysis as:
1. Executive Summary (2-3 sentences)
2. Key Findings (bullet points)
3. Detailed Analysis (with supporting data)
4. Limitations and Caveats
5. Recommendations (if applicable)

## Scope
- Financial data analysis only
- Historical and current data (not speculation)
- Quantitative analysis preferred
- Escalate to human analyst for strategic decisions
```

## Example 3: Few-Shot Prompt for Classification

```
You are a customer support ticket classifier. Classify each ticket into one of these categories:
- billing: Payment, invoice, or subscription issues
- technical: Software bugs, crashes, or technical problems
- feature_request: Requests for new functionality
- general: General inquiries or feedback

Examples:

Ticket: "I was charged twice for my subscription this month"
Category: billing

Ticket: "The app crashes when I try to upload files larger than 100MB"
Category: technical

Ticket: "Would love to see dark mode in the mobile app"
Category: feature_request

Now classify this ticket:
Ticket: "How do I reset my password?"
Category:
```

## Example 4: Chain-of-Thought Prompt for Complex Analysis

```
Analyze this business scenario step by step:

Step 1: Identify the core problem
- What is the main issue?
- What are the symptoms?
- What's the root cause?

Step 2: Analyze contributing factors
- What external factors are involved?
- What internal factors are involved?
- How do they interact?

Step 3: Evaluate potential solutions
- What are 3-5 viable solutions?
- What are the pros and cons of each?
- What are the implementation challenges?

Step 4: Recommend and justify
- Which solution is best?
- Why is it superior to alternatives?
- What are the risks and mitigation strategies?

Scenario: [YOUR SCENARIO HERE]
```

## Example 5: XML-Structured Prompt for Consistency

```xml
<prompt>
  <metadata>
    <version>1.0</version>
    <purpose>Generate marketing copy for SaaS products</purpose>
    <target_audience>B2B decision makers</target_audience>
  </metadata>

  <instructions>
    <objective>
      Create compelling marketing copy that emphasizes ROI and efficiency gains
    </objective>

    <constraints>
      <max_length>150 words</max_length>
      <tone>Professional but approachable</tone>
      <avoid>Jargon, hyperbole, false claims</avoid>
    </constraints>

    <format>
      <headline>Compelling, benefit-focused (max 10 words)</headline>
      <body>2-3 paragraphs highlighting key benefits</body>
      <cta>Clear call-to-action</cta>
    </format>

    <examples>
      <example>
        <product>Project management tool</product>
        <copy>
          Headline: "Cut Project Delays by 40%"
          Body: "Teams waste 8 hours weekly on status updates. Our tool automates coordination..."
        </example>
      </example>
    </examples>
  </instructions>
</prompt>
```

## Example 6: Prompt for Iterative Refinement

```
I'm working on a prompt for [TASK]. Here's my current version:

[CURRENT PROMPT]

I've noticed these issues:
- [ISSUE 1]
- [ISSUE 2]
- [ISSUE 3]

As a prompt engineering expert, please:
1. Identify any additional issues I missed
2. Suggest specific improvements with reasoning
3. Provide a refined version of the prompt
4. Explain what changed and why
5. Suggest test cases to validate the improvements
```

## Example 7: Anti-Pattern Recognition

### ❌ Ineffective Prompt
```
"Analyze this data and tell me what you think about it. Make it good."
```

**Issues:**
- Vague objective ("analyze" and "what you think")
- No format specification
- No success criteria
- Ambiguous quality standard ("make it good")

### ✅ Improved Prompt
```
"Analyze this sales data to identify:
1. Top 3 performing products (by revenue)
2. Seasonal trends (month-over-month changes)
3. Customer segments with highest lifetime value

Format as a structured report with:
- Executive summary (2-3 sentences)
- Key metrics table
- Trend analysis with supporting data
- Actionable recommendations

Focus on insights that could improve Q4 revenue."
```

## Example 8: Testing Framework for Prompts

```
# Prompt Evaluation Framework

## Test Case 1: Happy Path
Input: [Standard, well-formed input]
Expected Output: [Specific, detailed output]
Success Criteria: [Measurable criteria]

## Test Case 2: Edge Case - Ambiguous Input
Input: [Ambiguous or unclear input]
Expected Output: [Request for clarification]
Success Criteria: [Asks clarifying questions]

## Test Case 3: Edge Case - Complex Scenario
Input: [Complex, multi-faceted input]
Expected Output: [Structured, comprehensive analysis]
Success Criteria: [Addresses all aspects]

## Test Case 4: Error Handling
Input: [Invalid or malformed input]
Expected Output: [Clear error message with guidance]
Success Criteria: [Helpful, actionable error message]

## Regression Test
Input: [Previous failing case]
Expected Output: [Now handles correctly]
Success Criteria: [Issue is resolved]
```

## Example 9: Skill Metadata Template

```yaml
---
name: analyzing-financial-statements
description: Expert guidance on analyzing financial statements, identifying trends, and extracting actionable insights for business decision-making
---

# Financial Statement Analysis Skill

## Overview
This skill provides expert guidance on analyzing financial statements...

## Key Capabilities
- Balance sheet analysis
- Income statement interpretation
- Cash flow analysis
- Ratio analysis and benchmarking
- Trend identification
- Risk assessment

## Use Cases
- Evaluating company financial health
- Comparing competitors
- Identifying investment opportunities
- Assessing business performance
- Forecasting financial trends

## Limitations
- Historical data only (not predictive)
- Requires accurate financial data
- Industry context important
- Professional judgment recommended
```

## Example 10: Prompt Optimization Checklist

```
# Prompt Optimization Checklist

## Clarity
- [ ] Objective is crystal clear
- [ ] No ambiguous terms
- [ ] Examples provided
- [ ] Format specified

## Conciseness
- [ ] No unnecessary words
- [ ] Focused on essentials
- [ ] Efficient structure
- [ ] Respects context window

## Completeness
- [ ] All necessary context provided
- [ ] Edge cases addressed
- [ ] Success criteria defined
- [ ] Constraints specified

## Testability
- [ ] Can measure success
- [ ] Has clear pass/fail criteria
- [ ] Repeatable results
- [ ] Handles edge cases

## Robustness
- [ ] Handles variations in input
- [ ] Graceful error handling
- [ ] Consistent output format
- [ ] Resistant to jailbreaks
```


title: Large teenage boy with shirt that says'rustle '

summary: Stable Diffusion prompt sampled from DiffusionDB (NSFW-, PII- and named-person-filtered).

kind: image

credit: From DiffusionDB (Wang et al., 2022), https://huggingface.co/datasets/poloclub/diffusiondb, CC0-1.0.

DiffusionDB

handle: diffusiondb

source: diffusiondb

sourceName: DiffusionDB

copyrightHolder: DiffusionDB contributors (Wang et al., 2022), dedicated to the public domain

contentRating: general

content: large teenage boy with shirt that says'rustle ', angry, digital art, finger hair short


ref: prompts-chat/whiteboard-diagrams

title: Whiteboard Diagrams

kind: text

credit: "Whiteboard Diagrams" by prompts.chat (https://incantory.ai/prompts-chat/whiteboard-diagrams), licensed CC0-1.0

prompts.chat

handle: prompts-chat

source: prompts-chat

copyrightHolder: prompts.chat contributors

title: Whiteboard Diagrams

content:
Steps to build an AI startup by making something people want:

{
  "style": {
    "name": "Whiteboard Sketch Diagram",
    "description": "Transform any concept into an elegant hand-drawn diagram. Clean, minimal, architectural in feel—like a smart person's quick sketch on a whiteboard."
  },
  "core_philosophy": {
    "essence": "Elegant simplicity—the lightest possible touch that still communicates clearly",
    "mindset": "An architect or designer explaining an idea with a fine pen",
    "goal": "Clarity through restraint and refinement"
  },
  "visual_foundation": {
    "canvas_structure": {
      "outer_background": "#FFFFFF",
      "card": {
        "size": "95-98% of canvas—minimal white margin",
        "color": "#FEFEFE",
        "corner_radius": "12-16px subtle roundness",
        "shadow": "NONE",
        "border": "NONE"
      }
    },
    "overall_aesthetic": {
      "feel": "Light, airy, intellectual, refined",
      "weight": "Delicate—everything feels thin and elegant",
      "space": "Generous white space everywhere"
    }
  },
  "line_work": {
    "critical_principle": "THIN AND DELICATE—not bold, not heavy, not chunky",
    "quality": {
      "weight": "Fine, thin lines—like a 0.5mm pen or fine-tip marker",
      "character": "Architectural, precise but hand-drawn",
      "consistency": "Uniform thin weight throughout"
    },
    "stroke_style": {
      "lines": "Thin, clean, slightly imperfect",
      "corners": "Sharp or slightly rounded, never bulky",
      "feel": "Drawn quickly but skillfully"
    }
  },
  "color_palette": {
    "exact_colors": {
      "card_background": {
        "hex": "#FEFEFE",
        "description": "Almost white, flat, neutral"
      },
      "primary_text": {
        "hex": "#020202",
        "description": "Near-black for text—crisp and readable"
      },
      "line_gray": {
        "hex": "#4A4B4B",
        "description": "Dark gray for all drawn lines, boxes, shapes—NOT pure black"
      },
      "accent_blue": {
        "hex": "#2C68B7",
        "description": "Clear medium blue—for arrows, connectors, brackets, some labels"
      },
      "accent_red": {
        "hex": "#B34952",
        "description": "Warm coral-red—for category labels, emphasis text"
      },
      "fill_blue": {
        "hex": "#2C68B7",
        "description": "Same blue for small filled squares/shapes"
      },
      "fill_gray": {
        "hex": "#4A4B4B",
        "description": "Dark gray for filled grid cells"
      }
    },
    "usage": {
      "text": "Primary text in #020202 black, categories in #E54B54 red",
      "lines_and_shapes": "All outlines in #4A4B4B gray—NOT black",
      "arrows_and_flow": "#2C68B7 blue—thin and elegant",
      "fills": "Small filled squares in blue or gray—never large solid areas"
    }
  },
  "typography": {
    "style": {
      "type": "Elegant italic handwriting",
      "weight": "Light to medium—never bold or heavy",
      "slant": "Natural italic lean",
      "character": "Fluid, intelligent, like architect's lettering"
    },
    "colors": {
      "titles": "#020202 black, italic",
      "category_labels": "#E54B54 red",
      "annotations": "#2C68B7 blue or #020202 black"
    }
  },
  "diagram_elements": {
    "boxes_and_rectangles": {
      "stroke": "THIN #4A4B4B gray outline—1-2px weight max",
      "fill": "Empty/transparent—never solid filled large boxes",
      "corners": "Slightly rounded or sharp, hand-drawn",
      "style": "Light, airy, not heavy containers"
    },
    "grids_and_matrices": {
      "stroke": "Thin gray lines",
      "cells": "Small—may contain small filled squares or numbers",
      "fills": "Small squares filled blue or gray to show data"
    },
    "arrows": {
      "critical": "THIN, ELEGANT, SIMPLE—not chunky PowerPoint arrows",
      "stroke": "Thin #2C68B7 blue line—same weight as other lines",
      "heads": "Small, simple, minimal—just two short angled lines forming a point",
      "style": "Like hand-drawn with a fine pen, not a thick marker",
      "types": [
        "Simple thin straight arrows",
        "Thin curved arrows for flow",
        "Never: block arrows, 3D arrows, gradient arrows, thick arrows"
      ]
    },
    "brackets": {
      "style": "Thin hand-drawn curly braces in blue",
      "weight": "Same thin line weight as everything else"
    },
    "dots_and_markers": {
      "style": "Small filled circles or squares",
      "size": "Tiny—proportional to the thin line aesthetic",
      "colors": "Blue or red for emphasis"
    }
  },
  "visual_language": {
    "shapes_vocabulary": {
      "rectangles": "Thin outlined boxes—vertical or horizontal orientation",
      "grids": "Small matrices with tiny filled cells",
      "lists": "Simple dashed or bulleted items inside boxes",
      "flow": "Thin arrows connecting elements left-to-right"
    },
    "composition_patterns": {
      "typical_layout": "2-4 main elements arranged horizontally with arrows between",
      "spacing": "Generous gaps between elements",
      "alignment": "Rough but intentional alignment",
      "hierarchy": "Titles above boxes, labels below or beside"
    },
    "proportions": {
      "line_weight_to_space": "Very thin lines in very open space",
      "text_to_diagram": "Text is secondary, diagram dominates",
      "fill_to_empty": "Mostly empty, fills are small accents"
    }
  },
  "elegance_principles": {
    "lightness": "Everything should feel like it could float away",
    "restraint": "Use the minimum to communicate the idea",
    "refinement": "Quality of line over quantity of elements",
    "intelligence": "Looks like a smart person drew it quickly",
    "breathing": "White space is as important as the marks"
  },
  "avoid": [
    "Thick, heavy, bold lines",
    "Chunky PowerPoint-style arrows",
    "Block arrows or 3D arrows",
    "Large solid filled areas",
    "Dense, cluttered layouts",
    "Bold or heavy typography",
    "Drop shadows or gradients",
    "Corporate clip-art aesthetic",
    "Rounded bubble shapes",
    "Any line weight that feels 'heavy'",
    "Pure black (#000000) for lines—use #4A4B4B gray",
    "Decorative elements",
    "Overly complex diagrams"
  ]
}


title: A surreal neon dancing mushroom baby

creditLine: From DiffusionDB (Wang et al., 2022), https://huggingface.co/datasets/poloclub/diffusiondb, CC0-1.0.

title: A surreal neon dancing mushroom baby

content: a surreal neon dancing mushroom baby


title: Cm punk working at a record store

title: Cm punk working at a record store

content: cm punk working at a record store


title: Blurry and dreamy screencap of a character from 9 0 s satoshi kon anime

content: blurry and dreamy screencap of a character from 9 0 s satoshi kon anime, glitchy vhs tape, abstract background, perfect blue color palette, noisy film grain effect, blurry image


title: Realistic Mirror-Selfie Scene Creation

summary: “Mirror-selfie scene in a modern apartment interior. A young woman with long, naturally wavy light-brown hair wears a dark baseball cap (strap visible at the back), a black short-sleeve football…

credit: "Realistic Mirror-Selfie Scene Creation" by prompts.chat (https://incantory.ai/prompts-chat/realistic-mirror-selfie-scene-creation), licensed CC0-1.0

title: Realistic Mirror-Selfie Scene Creation

content:
“Mirror-selfie scene in a modern apartment interior. A young woman with long, naturally wavy light-brown hair wears a dark baseball cap (strap visible at the back), a black short-sleeve football jersey with pink lettering and the number ‘10’, and black high-waist leggings. She is turned back to camera, facing the mirror; her face is mostly not visible (rear/three-quarter from behind).
She holds a black smartphone in her right hand at shoulder height, elbow bent ~90°, wrist straight, the rear camera facing the mirror so the phone screen in the mirror shows the same scene (phone-within-phone recursion). Left arm relaxed down by her side.
Camera & composition: shot as a mirror selfie from behind; lens ~26–28mm equivalent, eye-level camera height; portrait orientation; framed from mid-thigh to above the head, centered on the jersey text and number. Subtle soft daylight from the room; no harsh shadows.
Environment: white door on the left with metal lever handle, narrow wall section, open doorway leading to a minimal kitchen (tall fridge/oven column visible), pale neutral walls, light flooring. Background slightly soft but readable.
Wardrobe details to preserve: jersey text “MESSI” in rounded pink letters above a large pink “10”; pink line style consistent; jersey fit slightly loose; cap color dark; leggings matte black; hair length reaches mid-back with a few loose curls.
Pose & micro-angles: head slightly tilted right, cap brim angled slightly downward; shoulders relaxed; pelvis square to mirror; spine neutral. Right hand grip firm with fingertips visible at the phone’s far edge; phone edges parallel to mirror frame; phone centered roughly over the spine line.
Lighting: soft natural indoor light, neutral white balance, no flash, no color cast. Reflections are physically correct with no duplication or misalignment.
Aesthetic: clean, realistic, unfiltered, true-to-life skin and fabric textures, sharp focus on jersey lettering and phone; minimal grain.
Crop & aspect: primary 3:4 (portrait); safe alternatives 9:16 and 4:5 maintaining full jersey text and number in frame.”
Consistency Locks (do not alter):
Same woman: hair length, color, wave pattern; dark baseball cap with back strap; black jersey with pink “MESSI” + “10”; black leggings; right-hand phone hold at shoulder height; left arm relaxed; mirror-selfie from behind; apartment/kitchen layout; door with metal lever handle; overall camera height ≈ eye level; phone recursion visible on screen.
Keep proportions and body type; no slimming/lengthening.
Keep colors and typography of jersey lettering exactly; no restyling.
Maintain environment geometry and object placement.


title: Everything is going according to plan

title: Everything is going according to plan

content: everything is going according to plan, blue and red colours, cinematic. acrylic painting,


title: Graphic design print ad for nextran truck centers magazine electric vehicles

content: graphic design print ad for nextran truck centers magazine electric vehicles


ref: prompts-chat/american-comic

title: American Comic

summary: story: a child superman and a child batman joins their forces together in a forest. it's a beautiful day in the forest and they see a stick shelter and want to check out. they see a fox and for…

credit: "American Comic" by prompts.chat (https://incantory.ai/prompts-chat/american-comic), licensed CC0-1.0

title: American Comic

content:
story: a child superman and a child batman joins their forces together in a forest. it's a beautiful day in the forest and they see a stick shelter and want to check out. they see a fox and for several seconds both fox and kids don't know what to do. they think first. then they all decide to run in opposite directions

instructions: {
  "style": {
    "name": "American Comic Book",
    "description": "Bold, dynamic comic book page in the classic American superhero tradition. Deliver your narrative as a fully realized comic page with dramatic panel layouts, cinematic action, and professional comic book rendering."
  },
  "visual_foundation": {
    "medium": {
      "type": "Professional American comic book art",
      "tradition": "DC/Marvel mainstream superhero comics",
      "era": "Modern age (2000s-present) with classic sensibilities",
      "finish": "Fully inked and digitally colored, publication-ready"
    },
    "page_presence": {
      "impact": "Each page should feel like a splash-worthy moment",
      "energy": "Kinetic, explosive, larger-than-life",
      "tone": "Epic and dramatic, never static or mundane"
    }
  },
  "panel_architecture": {
    "layout_philosophy": {
      "approach": "Dynamic asymmetrical grid with dramatic variation",
      "pacing": "Panel sizes reflect story beats—big moments get big panels",
      "flow": "Clear left-to-right, top-to-bottom reading path despite dynamic layout",
      "gutters": "Clean white gutters, consistent width, sharp panel borders"
    },
    "panel_variety": {
      "hero_panel": "Large central or full-width panel for key action moment",
      "establishing": "Wide panels for scale and environment",
      "reaction": "Smaller panels for faces, dialogue, tension beats",
      "inset": "Occasional overlapping panels for emphasis or simultaneity"
    },
    "border_treatment": {
      "standard": "Clean black rectangular borders",
      "action_breaks": "Panel borders may shatter or be broken by explosive action",
      "bleed": "Key moments may bleed to page edge for maximum impact"
    }
  },
  "artistic_rendering": {
    "line_work": {
      "quality": "Bold, confident, professional inking",
      "weight_variation": "Heavy outlines on figures, medium on details, fine for texture",
      "contour": "Strong silhouettes readable at any size",
      "hatching": "Strategic crosshatching for form and shadow, not overworked",
      "energy_lines": "Speed lines, impact bursts, motion trails for kinetic action"
    },
    "anatomy_and_figures": {
      "style": "Heroic idealized anatomy—powerful, dynamic, exaggerated",
      "musculature": "Detailed muscle definition, anatomy pushed for drama",
      "poses": "Extreme foreshortening, dramatic angles, impossible dynamism",
      "scale": "Figures commanding space, heroic proportions",
      "expression": "Intense, readable emotions even at distance"
    },
    "environmental_rendering": {
      "destruction": "Detailed rubble, debris clouds, structural damage",
      "atmosphere": "Rain, smoke, dust, particle effects for mood",
      "architecture": "Solid perspective, detailed enough for scale reference",
      "depth": "Clear foreground/midground/background separation"
    }
  },
  "color_philosophy": {
    "approach": {
      "style": "Modern digital coloring with painterly rendering",
      "depth": "Full modeling with highlights, midtones, shadows",
      "mood": "Color supports emotional tone of each panel"
    },
    "palette_dynamics": {
      "characters": "Bold, saturated colors for heroes/main figures",
      "environments": "More muted, atmospheric tones to push figures forward",
      "contrast": "Strong value contrast between subjects and backgrounds",
      "temperature": "Strategic warm/cool contrast for depth and drama"
    },
    "atmospheric_coloring": {
      "sky": "Dramatic gradients—stormy grays, apocalyptic oranges, moody blues",
      "weather": "Rain rendered as white/light blue streaks against darker values",
      "fire_energy": "Vibrant oranges, yellows with white-hot cores, proper glow falloff",
      "smoke_dust": "Layered opacity, warm and cool grays mixing"
    },
    "lighting_effects": {
      "key_light": "Strong dramatic source creating bold shadows",
      "rim_light": "Edge lighting separating figures from backgrounds",
      "energy_glow": "Bloom effects on power sources, eyes, weapons",
      "environmental": "Bounce light from fires, explosions, energy blasts"
    }
  },
  "typography_and_lettering": {
    "speech_bubbles": {
      "shape": "Classic oval/rounded rectangle balloons",
      "border": "Clean black outline, consistent weight",
      "tail": "Pointed tail clearly indicating speaker",
      "fill": "Pure white interior for maximum readability"
    },
    "dialogue_text": {
      "font": "Classic comic book lettering—bold, clean, uppercase",
      "size": "Readable at print size, consistent throughout",
      "emphasis": "Bold for stress, italics for whispers or thoughts"
    },
    "sound_effects": {
      "style": "Large, dynamic, integrated into the art",
      "design": "Custom lettering matching the sound—jagged for explosions, bold for impacts",
      "color": "Vibrant colors with outlines, shadows, or 3D effects",
      "placement": "Part of the composition, not just overlaid"
    },
    "captions": {
      "style": "Rectangular boxes with subtle color coding",
      "placement": "Top or bottom of panels, clear hierarchy"
    }
  },
  "action_and_dynamics": {
    "motion_rendering": {
      "speed_lines": "Radiating or parallel lines showing movement direction",
      "motion_blur": "Selective blur on fast-moving elements",
      "impact_frames": "Starburst patterns at point of collision",
      "debris_scatter": "Rocks, glass, rubble flying with clear trajectories"
    },
    "impact_visualization": {
      "collision": "Visible shockwaves, ground cracks, structural deformation",
      "energy_attacks": "Bright core fading to colored edges with atmospheric scatter",
      "physical_force": "Bodies reacting realistically to impossible forces"
    },
    "camera_dynamics": {
      "angles": "Extreme low angles for power, high angles for scale",
      "foreshortening": "Aggressive perspective on approaching figures/fists",
      "dutch_angles": "Tilted frames for tension and unease",
      "depth_of_field": "Suggested focus through detail level and blur"
    }
  },
  "atmospheric_elements": {
    "weather": {
      "rain": "Diagonal streaks, splashes on surfaces, wet reflections",
      "lightning": "Bright forks illuminating scenes dramatically",
      "wind": "Debris, hair, capes showing direction and force"
    },
    "destruction_aesthetic": {
      "rubble": "Detailed concrete chunks, rebar, shattered glass",
      "dust_clouds": "Billowing, layered, atmospheric perspective",
      "fire": "Realistic flame shapes with proper color temperature gradient",
      "smoke": "Rising columns, drifting wisps, obscuring backgrounds"
    },
    "scale_indicators": {
      "buildings": "Damaged structures showing massive scale",
      "vehicles": "Cars, tanks as size reference objects",
      "crowds": "Smaller figures emphasizing main subject scale"
    }
  },
  "technical_standards": {
    "composition": {
      "focal_point": "Clear visual hierarchy in every panel",
      "eye_flow": "Deliberate path through panels via placement and contrast",
      "balance": "Dynamic asymmetry that feels intentional, not chaotic"
    },
    "consistency": {
      "character_models": "Consistent design across all panels",
      "lighting_logic": "Light sources make sense across the page",
      "scale_relationships": "Size ratios maintained throughout"
    },
    "print_ready": {
      "resolution": "High resolution suitable for print reproduction",
      "color_space": "Vibrant colors that work in CMYK",
      "bleed_safe": "Important elements away from trim edges"
    }
  },
  "page_composition": {
    "no_border": {
      "edge_treatment": "NO frame around the page—panels extend to image edge",
      "bleed": "Page IS the comic page, not a picture of one",
      "presentation": "Direct comic page, not photographed or framed"
    }
  },
  "avoid": [
    "Any frame or border around the entire page",
    "Photograph-of-a-comic-page effect",
    "Static, stiff poses without energy",
    "Flat lighting without dramatic shadows",
    "Muddy, desaturated coloring",
    "Weak, scratchy, or inconsistent line work",
    "Confusing panel flow or layout",
    "Tiny unreadable lettering",
    "Sound effects as plain text overlay",
    "Anatomically incorrect figures (unless stylized intentionally)",
    "Empty, boring backgrounds",
    "Inconsistent character scale between panels",
    "Manga-style effects in American comic aesthetic",
    "Overly rendered to the point of losing graphic punch",
    "Weak impact moments—every action should have weight"
  ]
}


title: Modern Web Development Assistant

summary: Act as an expert full-stack web developer and UI/UX designer. Help me build modern, responsive, and professional websites using HTML, CSS, JavaScript, React, Node.js, and databases when needed…

credit: "Modern Web Development Assistant" by Karunyareddy49 (https://incantory.ai/prompts-chat/modern-web-development-assistant), licensed CC0-1.0

title: Modern Web Development Assistant

content: Act as an expert full-stack web developer and UI/UX designer. Help me build modern, responsive, and professional websites using HTML, CSS, JavaScript, React, Node.js, and databases when needed. Generate clean, optimized, and well-structured code with proper comments and best practices.


summary: upscale this photo and make it look amazing. make it transparent background. fix broken objects. make it good

credit: "Photo Enhancement and Repair with Transparent Background" by prompts.chat (https://incantory.ai/prompts-chat/photo-enhancement-and-repair-with-transparent-background), licensed CC0-1.0


ref: prompts-chat/car-navigation-system

title: Car Navigation System

summary: I want you to act as a car navigation system. You will develop algorithms for calculating the best routes from one location to another, be able to provide detailed updates on traffic conditions…

credit: "Car Navigation System" by devisasari (https://incantory.ai/prompts-chat/car-navigation-system), licensed CC0-1.0

originalAuthor: devisasari

copyrightHolder: devisasari

title: Car Navigation System

content: I want you to act as a car navigation system. You will develop algorithms for calculating the best routes from one location to another, be able to provide detailed updates on traffic conditions, account for construction detours and other delays, utilize mapping technology such as Google Maps or Apple Maps in order to offer interactive visuals of different destinations and points-of-interests along the way. My first suggestion request is "I need help creating a route planner that can suggest alternative routes during rush hour."


title: "University Website Section Designer"

summary: Act as a University Web Designer. You are tasked with designing a modern and functional website for {{universityname}}.

credit: ""University Website Section Designer"" by prompts.chat (https://incantory.ai/prompts-chat/university-website-section-designer), licensed CC0-1.0

title: "University Website Section Designer"

type: string

content:
Act as a University Web Designer. You are tasked with designing a modern and functional website for {{university_name}}.

Your task is to:
- Identify and outline key sections for the website such as Admissions, Academics, Research, Campus Life, and Alumni.
- Ensure each section includes essential subsections like:
  - Admissions: Application process, Financial aid, Campus tours
  - Academics: Departments, Courses, Faculty profiles
  - Research: Research centers, Publications, Opportunities
  - Campus Life: Student organizations, Events, Housing
  - Alumni: Networking, Events, Support

Rules:
- Focus on creating a user-friendly interface.
- Ensure accessibility standards are met.
- Provide a responsive design for both desktop and mobile users.

Variables:
- {{university_name}} - Name of the university
- {{additional_sections}} - Additional sections as required


title: Minions in old photo 1 9 0 0 s

title: Minions in old photo 1 9 0 0 s

content: minions in old photo 1 9 0 0 s


title: A large sci fi headress made of sci final carbon fibre panels

content: a large sci fi headress made of sci final carbon fibre panels, concept art, high detail, digital painting, illustration


ref: prompts-chat/the-missing-woman

title: The Missing Woman

credit: "The Missing Woman" by hamitabis (https://incantory.ai/prompts-chat/the-missing-woman), licensed CC0-1.0

originalAuthor: hamitabis

copyrightHolder: hamitabis

title: The Missing Woman

content:
image-generation:
  main: "An 1980s-style woman walking with a cat beside her, both in the foreground."
  clothes: "worn jacket, blanket and old pants."
  faces: "Not visible or turned away"

  environment:
    streets: "Tree-lined, single-story houses, dead-end street."
    time: "Nightfall"
    atmosphere: "Rainy, cloudy"

  techniques:
    style: "Photorealistic, like captured by a real camera"
    focus: "Shallow depth of field, bokeh and rim lighting"
    light: "subject is well-lit, background is cold"
    colors: "background is blue and focus is red"

  composition:
    type: "Wide shot landscape"
    background: "Woodlands, lawns, gardens."

  mood:
    - "Depressive"
    - "Tearful"

  negative:
    - "HDR"
    - "Sketch"
    - "Black white"
    - "Low Resolution"
    - "Cloudy"


title: White fox under a sakura tree with kyoto in the background

content: white fox under a sakura tree with kyoto in the background


ref: diffusiondb/communist-propaganda-poster

title: Communist propaganda poster

title: Communist propaganda poster

content: communist propaganda poster, liquid chrome, y 2 k aesthetic


credit: "Creative Image Generation for Digital Art" by prompts.chat (https://incantory.ai/prompts-chat/creative-image-generation-for-digital-art), licensed CC0-1.0

content:
Act as a creative digital artist. You are skilled in generating unique and visually appealing images for digital use.

Your task is to:
- Create original and imaginative images that capture attention
- Focus on artistic style, color harmony, and visual storytelling
- Ensure images are suitable for digital platforms and social media

You will:
- Use vibrant colors and innovative designs
- Adapt styles based on provided themes or prompts
- Maintain high resolution and quality standards

Rules:
- Avoid using copyrighted elements
- Ensure all images are appropriate for a general audience


title: A capybara wearing wire rimmed sun glasses with a rainbow behind him

content: a capybara wearing wire rimmed sun glasses with a rainbow behind him, head and shoulders, laughing at a crossroads


title: Freddy fazbear in the Vietnam war black and white


credit: "Act as an FTTH Telecommunications Expert" by prompts.chat (https://incantory.ai/prompts-chat/act-as-an-ftth-telecommunications-expert), licensed CC0-1.0

topic

default: FTTH Basics

content:
Act as an FTTH Telecommunications Expert. You are a specialist in Fiber to the Home (FTTH) technology, which is a key component in modern telecommunications infrastructure.

Your task is to provide comprehensive information about FTTH, including:
- The basics of FTTH technology
- Advantages of using FTTH over other types of connections
- Implementation challenges and solutions
- Future trends in FTTH technology

You will:
- Explain the workings of FTTH in simple terms
- Compare FTTH with other broadband technologies
- Discuss the impact of FTTH on internet speed and reliability

Rules:
- Use technical language appropriate for an audience familiar with telecommunications
- Provide clear examples and analogies to illustrate complex concepts

Variables:
- {{topic|FTTH Basics}} - Specific aspect of FTTH to focus on
- {{context}} - Any additional context or specific questions from the user


title: Lord vetinari, detailed portrait, sharp focus, masterpiece, intricate…

content: lord vetinari, detailed portrait, sharp focus, masterpiece, intricate environment, dramatic lighting, 1 7 th century, oil painting


title: A cyberpunk ice cube floating in the sky

content: a cyberpunk ice cube floating in the sky, octane render, artistic, cinema 4 d, dark horror,


title: A monochromatic sepia photograph of a delorean in a group of covered wagons

content: a monochromatic sepia photograph of a delorean in a group of covered wagons,


ref: prompts-chat/structured-text-captioning

title: Structured Text Captioning

summary: You are a text processor. Take the provided text and extract the following information: Genre and content tags (e.g. fantasy, isekai, horror) A list of characters or people who appear in the text…

credit: "Structured Text Captioning" by prompts.chat (https://incantory.ai/prompts-chat/structured-text-captioning), licensed CC0-1.0

title: Structured Text Captioning

content:
You are a text processor. Take the provided text and extract the following information:
- Genre and content tags (e.g. fantasy, isekai, horror)
- A list of characters or people who appear in the text (if any)
- A list of tropes utilized in the text (if any)
- A list of writing style patterns, described precisely to desribe *how* the author arrived to evoke a certain style (e.g. a particular sentence construction, like "Heavy use of simple Subject-Verb-Object constructions" or "short, staccato sentence fragments")
- A description of how the text progresses (e.g. plot progression or plot threads)
- A comprehensive summary of the text

Follow this format:

<output_format>
## Tags
[If applicable]

## Characters
[Briefly name who appears if applicable]

## Tropes
[If applicable]

## Writing Style
[If applicable]

## Content Progression
[If applicable]

## Comprehensive Summary
[A summary of what appeared in the text]
</output_format>


ref: prompts-chat/text-based-adventure-game

title: Text Based Adventure Game

summary: I want you to act as a text based adventure game. I will type commands and you will reply with a description of what the character sees. I want you to only reply with the game output inside one…

credit: "Text Based Adventure Game" by heroj04 (https://incantory.ai/prompts-chat/text-based-adventure-game), licensed CC0-1.0

title: Text Based Adventure Game

content: I want you to act as a text based adventure game. I will type commands and you will reply with a description of what the character sees. I want you to only reply with the game output inside one unique code block, and nothing else. do not write explanations. do not type commands unless I instruct you to do so. when i need to tell you something in english, i will do so by putting text inside curly brackets {like this}. my first command is wake up