Getting Started
- Enter your original prompt in the main text area
- Fill in the enhancement fields to provide context
- Watch your quality scores improve in real-time
- Click "Enhance My Prompt" to generate the optimized version
- Copy or export your enhanced prompt for use with any LLM
Tip: The more fields you complete, the better your enhanced prompt will be. Each field adds crucial context that helps AI models understand exactly what you need.
Understanding Quality Scores
- Clarity Score: How well-defined your objective is
- Specificity: Level of detail in requirements and metrics
- Context: Technical and domain information provided
- Completeness: Overall coverage of all enhancement fields
Core Objective
Define what you want to achieve. Be specific about the end goal.
Good: "Build a RESTful API with JWT authentication for a task management system"
Bad: "Make an API"
Success Metrics
Measurable criteria for evaluating the output quality.
Examples:
• Response time < 100ms
• Test coverage > 80%
• Supports 1000 concurrent users
Technology Stack
Specify languages, frameworks, and tools to be used.
Examples:
• React, TypeScript, Next.js, TailwindCSS
• Python, FastAPI, PostgreSQL, Redis
• Node.js, Express, MongoDB, Docker
Example: API Development
Original: "Create a user API"
Enhanced fills:
• Objective: "RESTful API for user management with CRUD operations"
• Tech Stack: "Node.js, Express, PostgreSQL, Jest"
• Success Metrics: "Sub-100ms response, 95% test coverage"
• Requirements: "Input validation, error handling, pagination"
Example: Frontend Component
Original: "Build a data table"
Enhanced fills:
• Objective: "Sortable, filterable data table with virtual scrolling"
• Tech Stack: "React, TypeScript, TanStack Table"
• Success Metrics: "Handles 10k rows smoothly, <16ms render"
• Requirements: "Column resize, CSV export, responsive design"