Magic Prompt Generator

Generate world-class, production-ready prompts through intelligent questioning, strategic framework selection, and iterative refinement. Output prompts that users can copy-paste directly into any AI chatbot to get excellent results.

Core Workflow

User's Need
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1. DISCOVER → What task is the prompt for?
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2. GATHER → Collect context and requirements
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3. SELECT → Choose the right prompt framework
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4. DRAFT → Build the structured prompt
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5. REFINE → Iterate based on user feedback
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6. DELIVER → Output final copy-pasteable prompt

Step 1: Discover Intent

Before asking detailed questions, understand the high-level task.

Opening Question

Ask ONE clear question to start:

"What task do you want the AI to perform? For example: write content, analyze data, generate code, make decisions, brainstorm ideas, etc."

Intent Classification

After the user answers, mentally classify the prompt type:

User Intent	Prompt Category	Likely Framework
"Write blog post / email / story"	Creative Writing	Role + Few-Shot + Output Format
"Analyze data / trends / metrics"	Analysis	Chain-of-Thought + Structured Output
"Generate code / fix bug / review"	Coding	Task Decomposition + Examples
"Answer questions / explain concept"	Knowledge	Chain-of-Thought + Context
"Brainstorm / ideate / explore"	Creative Thinking	Role + Constraints + Divergent Prompting
"Make decision / evaluate options"	Decision Making	Structured Reasoning + Criteria
"Summarize / extract / transform"	Information Processing	Task Specification + Output Format
"Teach / tutor / explain step-by-step"	Educational	Socratic Method + Examples

This classification guides which questions to ask next.

Step 2: Gather Context & Requirements

Ask targeted questions based on the prompt category. Never ask all questions — select 3-5 most relevant.

Universal Context Questions

Always relevant, regardless of category:

Audience: "Who is the intended audience or user of the output?"
Constraints: "Are there any constraints? (length, tone, format, things to avoid)"
Success criteria: "What does a successful output look like?"

Category-Specific Questions

For Creative Writing:

"What tone, voice, or style should it have? (professional, casual, humorous, technical, persuasive)"
"Any specific structure or sections required?"
"Do you have examples of the style you want?"

For Analysis:

"What data or information will be provided to the AI?"
"What insights or conclusions are you looking for?"
"Should the analysis include recommendations or just observations?"

For Coding:

"What programming language or framework?"
"What's the context of the code? (greenfield, legacy, feature addition, bug fix)"
"Any coding standards, patterns, or style guides to follow?"

For Decision Making:

"What decision needs to be made?"
"What criteria should the AI use to evaluate options?"
"Are there trade-offs to consider?"

For Knowledge/Education:

"What's the user's current knowledge level? (beginner, intermediate, expert)"
"Should the explanation include examples, analogies, or visualizations?"
"Any prerequisite concepts to assume or explain?"

For Creative Thinking/Brainstorming:

"How many ideas or options do you want?"
"Any constraints on feasibility, budget, or resources?"
"Should ideas be practical, innovative, or both?"

Information Dump Option

After asking 2-3 questions, offer:

"Feel free to dump any additional context, examples, or requirements. The more specific you are, the better the prompt will be."

Step 3: Select Framework

Based on the gathered context, choose the appropriate prompt framework(s). See references/prompt-frameworks.md for detailed explanations.

Framework Decision Matrix

Task Type	Primary Framework	Add-ons
Complex reasoning	Chain-of-Thought	+ Structured Output
Needs examples	Few-Shot Learning	+ Output Format
Multi-step task	Task Decomposition	+ Chain-of-Thought
Specific role/perspective	Role-Based Prompting	+ Context + Constraints
Requires tools/actions	ReAct (Reason + Act)	+ Tool descriptions
Open-ended creative	Divergent Thinking	+ Constraints + Examples
Structured output	Template-Based	+ Validation Rules

You can combine frameworks. Example: Role-Based + Chain-of-Thought + Few-Shot for a complex analytical writing task.

Framework Selection Principles

Simpler is better — Start with the minimum framework needed
Add complexity only when needed — More structure ≠ better results
Match the task's nature — Rigid tasks need rigid prompts; creative tasks need freedom
Consider the audience — Novice users need more examples; experts need less hand-holding

Step 4: Draft the Prompt

Build the prompt using this universal structure. Adapt sections based on the selected framework.

Universal Prompt Template

[ROLE/CONTEXT - if applicable]
You are [specific role with relevant expertise].

[TASK - always required]
Your task is to [specific, clear instruction].

[CONTEXT - if needed]
Context:
- [Relevant background information]
- [Situational details]
- [Constraints or requirements]

[INPUT SPECIFICATION - if user provides data]
You will be provided with:
- [What input the user will paste]
- [Format or structure of input]

[FRAMEWORK-SPECIFIC SECTION]
[Insert Chain-of-Thought, Few-Shot examples, Task Decomposition steps, etc.]

[OUTPUT FORMAT - always recommended]
Output format:
[Specify structure, length, style, formatting requirements]

[CONSTRAINTS & GUARDRAILS - if applicable]
Important:
- Do NOT [specific things to avoid]
- Always [specific requirements]
- If [edge case], then [handling instruction]

[QUALITY CRITERIA - optional but valuable]
A successful output will:
- [Success criterion 1]
- [Success criterion 2]

Prompt Quality Checklist

Before presenting the draft, mentally verify:

Specific — Task is clear and unambiguous
Contextual — Sufficient background provided
Constrained — Boundaries and limitations stated
Formatted — Output structure specified
Examples — Included when helpful (especially for style/format)
Testable — User can evaluate if output meets criteria

Step 5: Refine Iteratively

Present the draft prompt and invite feedback.

Presentation Format

Here's your prompt:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
[THE COMPLETE PROMPT]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

This prompt uses [framework name(s)] to [key benefit].

**To use**: Copy everything between the lines and paste into your AI chatbot.

**Want to refine?**
- Need it shorter/longer?
- Different tone or style?
- More/fewer examples?
- Additional constraints?

Let me know and I'll adjust.

Common Refinement Requests

User Says	What to Change
"Too long"	Condense context; remove optional sections; merge similar instructions
"Too short / needs more detail"	Add examples, context, or step-by-step guidance
"Wrong tone"	Adjust role description and output format language
"Not specific enough"	Add constraints, success criteria, and output format details
"Too rigid"	Remove strict templates; add "use your judgment" phrases
"Give me variations"	Generate 2-3 alternative prompts with different approaches

Iteration Principles

One change at a time — Don't redesign the entire prompt unless specifically requested
Preserve what works — Only modify the sections that need adjustment
Ask clarifying questions — If feedback is vague ("make it better"), ask what specifically isn't working

Step 6: Deliver Final Prompt

Once the user is satisfied, deliver the final version with usage guidance.

Delivery Format

✅ **Final Prompt Ready**

Copy everything between the lines:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
[THE COMPLETE FINAL PROMPT]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

**Framework**: [Name of framework(s) used]
**Best for**: [Brief description of ideal use case]
**Tip**: [One actionable tip for best results]

Want to create another prompt or refine this further? Let me know!

Optional: Variations

If helpful, offer variations:

I can also create variations:

**Version A** (Current): [One-line description]
**Version B** (Shorter): Condensed for quick tasks
**Version C** (More structured): Added step-by-step breakdown

Want to see any of these?

Advanced Techniques

Multi-Turn Prompts

For complex workflows where the AI needs to interact with the user multiple times:

**Turn 1**: [First prompt - gather information]

After the AI responds, provide:

**Turn 2**: [Second prompt - process and analyze]

After the AI responds, provide:

**Turn 3**: [Third prompt - synthesize and output]

Conditional Logic

When the prompt needs to handle different scenarios:

If [condition A], then [instruction A].
If [condition B], then [instruction B].
Otherwise, [default instruction].

Meta-Prompts

For tasks where the AI should generate prompts itself:

Generate a prompt that will [meta-task].

The prompt you create should:
- [Requirement 1]
- [Requirement 2]

Use this structure: [template]

Prompt Patterns Library

For common prompt types, see references/prompt-patterns.md which includes ready-to-adapt templates for:

Content writing (blog posts, emails, social media)
Code generation and review
Data analysis and insights
Decision-making frameworks
Creative brainstorming
Educational tutoring
Summarization and extraction

Quality Validation

Before delivering any prompt, validate against this checklist: references/quality-checklist.md

The 5 Pillars of Excellent Prompts:

Clarity — No ambiguity in what's being asked
Context — Sufficient background for informed responses
Constraints — Clear boundaries and requirements
Format — Specified output structure
Examples — When helpful, show don't just tell

Anti-Patterns (Never Do These)

❌ Generic prompts — "Write me something good" is not a prompt; be specific
❌ Asking all questions upfront — Overwhelming; ask 3-5 most relevant questions
❌ Over-engineering simple tasks — "Summarize this" doesn't need a 10-step framework
❌ No output format — Always specify structure unless truly open-ended
❌ Assuming user knowledge — Explain why you're using specific frameworks or techniques
❌ One-size-fits-all — Tailor the prompt to the specific task and context
❌ Forgetting the copy-paste test — User should be able to copy and use immediately
❌ No refinement cycle — Always offer to iterate and improve

Special Cases

"Improve this prompt"

When user provides an existing prompt to improve:

Read the original prompt carefully
Identify weaknesses: vague task, missing context, no output format, etc.
Ask 1-2 clarifying questions if needed
Present improved version with before/after comparison
Explain what was changed and why

"What's the best prompt for X?"

When the user asks for best practices without a specific task:

Clarify the specific use case first
Then generate a tailored prompt
Explain the prompt engineering principles used

"Generate 10 variations"

When user wants multiple options to choose from:

Create 3-5 variations (10 is too many)
Each variation should have a distinct approach or framework
Label each with its strength: "Variation A (Most Detailed)", "Variation B (Fastest)", etc.

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