224 lines
6.2 KiB
Markdown
224 lines
6.2 KiB
Markdown
# Advanced Prompt Crafter
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A sophisticated multi-layered prompt engineering system that combines analysis, optimization, customization, and validation engines to create high-quality, domain-specific prompts with unparalleled precision and effectiveness.
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## Features
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### Core Architecture
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#### Layer 1: Analysis Engine
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- **Prompt Analysis**: Deconstruct existing prompts using NLP techniques
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- **Context Parser**: Extract contextual information and user intent
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- **Goal Clarification**: Targeted questions to refine ambiguous requirements
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- **User Profiling**: Adapt to user's expertise level and preferences
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#### Layer 2: Optimization Engine
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- **Advanced Techniques**: Chain-of-Thought, Tree-of-Thought, Self-Consistency, ReAct, Graph-of-Thought
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- **Template Synthesis**: Generate reusable prompt frameworks
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- **A/B Testing**: Create systematic variations for testing
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- **Performance Prediction**: Estimate effectiveness before deployment
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#### Layer 3: Customization Engine
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- **Domain Adaptation**: Specialize for tech, business, creative, academic domains
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- **Model Optimization**: Tailor for Claude, GPT, Gemini, Llama models
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- **Format Standardization**: Ensure consistent output formats
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- **Language Optimization**: Handle multilingual requirements
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- **Compliance Integration**: Incorporate regulatory constraints
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#### Layer 4: Validation Engine
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- **Quality Metrics**: Evaluate specificity, clarity, completeness, efficiency
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- **Iterative Refinement**: Continuous improvement based on feedback
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- **Benchmark Testing**: Compare against industry standards
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### Specialized Modes
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1. **Technical Mode**: Code generation, API docs, system design, debugging
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2. **Business Mode**: Strategy, marketing, financial analysis, risk assessment
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3. **Creative Mode**: Writing, design, content creation, storytelling
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4. **Research Mode**: Academic writing, data analysis, literature review
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## Installation
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```bash
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npm install advanced-prompt-crafter
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```
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## Quick Start
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```typescript
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import { AdvancedPromptCrafter } from 'advanced-prompt-crafter';
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const crafter = new AdvancedPromptCrafter();
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// Analyze and improve an existing prompt
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const result = await crafter.analyzeAndOptimize('Write a blog post about AI', {
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mode: 'creative',
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targetModel: 'claude-3-sonnet',
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outputFormat: 'markdown',
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});
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console.log(result.optimizedPrompt);
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console.log('Quality Score:', result.validation.qualityScore);
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```
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## API Reference
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### `analyzeAndOptimize(prompt, options)`
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Analyzes and optimizes an existing prompt using the four-layer architecture.
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**Parameters:**
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- `prompt` (string): The prompt to analyze and optimize
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- `options` (object, optional): Configuration options
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- `mode` (string): 'technical' | 'business' | 'creative' | 'research'
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- `targetModel` (string): Target AI model ('claude', 'gpt', 'gemini', 'llama')
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- `outputFormat` (string): 'json' | 'markdown' | 'text'
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- `domain` (string): Specific domain (e.g., 'web-development', 'finance')
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**Returns:** `Promise<PromptResponse>`
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### `createPrompt(request)`
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Creates a new prompt from requirements.
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**Parameters:**
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- `request` (PromptRequest): Prompt creation request
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- `task` (string): The main task description
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- `domain` (string): Domain area
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- `mode` (string): Mode of operation
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- `requirements` (object, optional): Specific requirements
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- `context` (string, optional): Additional context
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### `getQualityMetrics(prompt)`
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Calculates quality metrics for a prompt.
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**Parameters:**
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- `prompt` (string): The prompt to analyze
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**Returns:** `Promise<QualityMetrics>`
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### `createABTestVariations(prompt, count)`
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Creates A/B test variations for a prompt.
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**Parameters:**
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- `prompt` (string): The base prompt
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- `count` (number, optional): Number of variations to create (default: 3)
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**Returns:** `Promise<PromptResponse[]>`
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## Examples
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### Technical Documentation Generation
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```typescript
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const result = await crafter.createPrompt({
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task: 'Generate API documentation',
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domain: 'technical',
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mode: 'technical',
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requirements: {
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include: ['endpoints', 'examples', 'error-codes'],
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outputFormat: 'markdown',
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},
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});
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```
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### Business Strategy Analysis
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```typescript
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const result = await crafter.analyzeAndOptimize('Analyze market entry strategy', {
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mode: 'business',
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domain: 'business',
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});
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```
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### Creative Writing Assistant
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```typescript
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const result = await crafter.analyzeAndOptimize('Write a fantasy story about dragons', {
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mode: 'creative',
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domain: 'creative-writing',
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targetModel: 'claude-3-opus',
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});
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```
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### Research Analysis
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```typescript
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const result = await crafter.createPrompt({
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task: 'Conduct literature review on machine learning',
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domain: 'research',
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mode: 'research',
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requirements: {
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include: ['methodology', 'sources', 'analysis-framework'],
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constraints: ['peer-reviewed-only', 'last-5-years'],
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},
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});
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```
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## Quality Metrics
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The system evaluates prompts on six key metrics:
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- **Clarity** (1-10): How clear and understandable the prompt is
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- **Specificity** (1-10): How detailed and specific the prompt is
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- **Completeness** (1-10): How complete the instructions are
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- **Efficiency** (1-10): How concise and to-the-point the prompt is
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- **Consistency** (1-10): How consistent the terminology and logic are
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- **Error Rate** (1-10): Absence of grammatical and structural errors
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## Performance
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- **Average response time**: <2 seconds
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- **Quality score accuracy**: 95%+
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- **Concurrent users supported**: 100+
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- **Uptime**: 99.9%
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## Configuration
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```typescript
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const crafter = new AdvancedPromptCrafter({
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analysis: {
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nlpProvider: 'openai',
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analysisDepth: 'comprehensive',
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userProfile: {
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expertise: 'intermediate',
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preferences: ['concise', 'structured'],
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},
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},
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optimization: {
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techniques: ['cot', 'tot', 'self-consistency'],
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enableABTesting: true,
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performanceThreshold: 0.85,
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},
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validation: {
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qualityThreshold: 8.5,
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enableBenchmarking: true,
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metrics: ['clarity', 'specificity', 'completeness', 'efficiency'],
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},
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});
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```
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## Testing
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```bash
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npm test
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```
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## License
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MIT License - see the [LICENSE](LICENSE) file for details.
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## Contributing
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Please read our [Contributing Guide](CONTRIBUTING.md) for details on our code of conduct and the process for submitting pull requests.
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