AI Prompt Generator

A free, rule-based AI prompt generator and system prompt generator for ChatGPT, Claude, Gemini, coding agents, structured output, and image generation. Fill in the form, click Generate, and get a ready-to-use prompt — plus compact, detailed, and template versions.

Prompt Mode

Everyday prompts for chat and task-based interactions.

Prompt Details

Task*

What do you want the AI to do?

Context

Background information the model should know.

Audience

Who will read or benefit from the output?

Tone

Output format

Constraints

One per line or comma-separated.

Examples

Optional — show the model what a good output looks like.

// Fill in the form and click "Generate Prompt" to see output here…

Prompt Modes Explained

General Prompt

Task, audience, tone, output format, and constraints. The starting point for most ChatGPT, Claude, and Gemini interactions.

System Prompt

Define an assistant's role, responsibilities, tone, allowed/disallowed behaviors, and fallback. Used in the system message of any AI API.

Developer Prompt

Coding-assistant style prompts for code generation, debugging, refactoring, explanation, review, and test writing.

Structured Output

Strict formatting prompts for JSON, CSV, markdown tables. Includes "return only valid JSON" rules and field validation instructions.

Agent Prompt

Goal-driven prompts with available tools, decision rules, stop conditions, and safety constraints for autonomous AI agents.

Image Prompt

Descriptive prompts for Midjourney, DALL-E, Stable Diffusion, and other image generators — subject, style, lighting, and negative prompt.

Tips for Better Prompts

Be specific about the task

Vague tasks produce vague outputs. Instead of "write something about climate", try "write a 3-paragraph explanation of how ocean acidification affects coral reefs, for a high school audience".

Name your audience

The same topic explained to a five-year-old vs. a PhD researcher requires completely different language. Always specify who will read or use the output.

Specify the output format

Tell the model exactly how to format its response: bullet points, numbered steps, a table, JSON, or a single paragraph. Without this, models choose their own format.

Add constraints

"Maximum 100 words", "no technical jargon", "Python only, no external libraries" — constraints prevent the model from going off-track or producing unusable output.

Provide examples for complex tasks

If the format you need is hard to describe, show an example (Input → Output). This is called few-shot prompting and dramatically improves consistency.

Set fallback behavior for system prompts

Always define what the assistant should do when it cannot answer. "Say I don't know and suggest contacting support" is far better than an unguided refusal.

Example Generated Prompts

System Prompt — Customer Support Assistant

You are a helpful customer support assistant for a SaaS analytics platform.

Your primary responsibility is to answer billing, account, and feature questions clearly and accurately.

Always respond in a friendly, professional, and concise tone.

Format all responses as plain text with numbered steps for multi-step instructions.

You may:
- Escalate complex issues to human support
- Provide product documentation links
- Ask clarifying questions

You must not:
- Access or modify user account data
- Make promises about future features
- Discuss competitors

If you are unsure or cannot complete a request: say "I'm not sure about that — let me connect you with our support team" and provide the support email

Developer Prompt — Generate TypeScript Component

Language/Stack: TypeScript + React 18

Generate the following code.

Context: This is a Next.js admin dashboard with a data table component

Constraints:
- Use functional components and hooks only
- No class components
- Follow the project's existing file structure

Expected output: A reusable Pagination component with props for currentPage, totalPages, and onPageChange

Respond with clean, working code. Add brief comments only where the logic is non-obvious. Do not include unnecessary boilerplate.

Structured Output Prompt — JSON User Extraction

Task: Extract user profile data from the given text

Context: Parsing user records from a CSV export of an HR system

Output format: JSON

Include the following fields:
- name
- email
- role
- department
- joinedAt (ISO date)
- isActive (boolean)

Use null for any missing or unavailable values.

Validation rules:
- email must be valid format
- role must be one of: admin, editor, viewer
- joinedAt must be a valid ISO 8601 date string

Return only valid, parseable JSON. Do not include any explanation, markdown code blocks, or extra text outside the JSON structure.

Strictly follow the schema. Do not add extra fields. Do not deviate from the specified structure.

Privacy: This tool runs in your browser. Your prompt details are not uploaded, stored, or sent to any server.

Frequently Asked Questions

Is this an AI-powered tool?

No. This is a rule-based prompt builder. It assembles structured prompts from your inputs using deterministic templates. No AI model, API, or LLM is involved. The same inputs always produce the same output.

What are the different prompt modes?

General: everyday chat and task prompts. System Prompt: assistant persona and behavior rules. Developer: code generation, debugging, review, and explanation. Structured Output: prompts that enforce JSON, table, CSV, or markdown formats. Agent: goal-driven prompts with tools, decision rules, and stop conditions. Image: descriptive prompts for Midjourney, DALL-E, Stable Diffusion, etc.

What is a system prompt?

A system prompt is a special instruction given to an AI model before the conversation begins. It defines the model's persona, responsibilities, tone, allowed and disallowed behaviors, and fallback responses. Most AI APIs (OpenAI, Anthropic, Google) support a dedicated system message role for this purpose.

What is the Template output tab?

The Template tab converts your generated prompt into a reusable template by wrapping placeholder-style values in {{double braces}}. You can copy this template and fill in the variables dynamically in your code or prompting workflow.

What are the four output versions?

Generated: the standard assembled prompt ready to use. Compact: a condensed version with section headings removed — useful for shorter context windows. Detailed: the prompt with explicit markdown section headings for each component. Template: the generated prompt with variable placeholders for reuse.

Why does the Structured Output mode include "return only valid JSON" rules?

Language models sometimes wrap JSON output in markdown code fences or add explanatory text. Including explicit instructions like "return only valid, parseable JSON" significantly reduces these formatting errors, especially for automated pipelines that parse the output programmatically.

How do I use an Agent prompt?

Fill in the agent's goal, the tools it has access to, decision rules for choosing between tools, a stop condition (when should it stop), and any safety constraints. The generated prompt can be used as a system message or initial user message for autonomous agent frameworks like LangChain, AutoGen, or a raw Claude/GPT-4o API call.

Is my data uploaded anywhere?

No. This tool runs entirely in your browser. Your prompt details are never sent to any server, logged, or stored. Everything is computed locally in your browser tab.

Prompt Tools