Most people just type into ChatGPT and hope for the best. And honestly, for simple questions, that works fine.
But the moment you need consistent, high-quality output—code reviews, content in a specific voice, structured analysis—you need a system prompt. The problem is that writing a good one from scratch is harder than it looks.
I’ve written hundreds of system prompts. The ones that work share a common structure: clear role, specific task, explicit rules, defined output format, and consistent tone. This tool gives you that structure without needing to remember the formula.
New: Start from one of 6 ready-made templates (Code Reviewer, Content Writer, Data Analyst, Learning Tutor, Email Assistant, API Designer) and customize from there—or start blank and build your own.
What Is a System Prompt?
A system prompt is a set of instructions that tells an AI how to behave before the conversation starts. It’s the “personality configuration” layer.
In ChatGPT, it lives in the “Custom Instructions” or “System” field. In Claude, it’s the system prompt parameter. In API calls, it’s the system message.
Without a system prompt: The AI uses its default behavior—helpful but generic.
With a good system prompt: The AI acts as a specific expert with defined rules, producing consistent output every time.
The Anatomy of an Effective System Prompt
1. Role
The role tells the AI who it is. This is the most impactful part of a system prompt because it shapes everything else.
Weak: “You are a helpful assistant.” Strong: “You are a senior backend engineer with 10 years of experience in Python, specializing in API design and database optimization.”
The more specific the role, the better the output. Include experience level, specialization, and domain knowledge.
2. Task
The task defines what the AI should do. Be explicit about the expected action.
Weak: “Help me with code.” Strong: “Review Python code for bugs, security vulnerabilities, and performance issues. Provide specific line-by-line feedback with severity ratings.”
3. Context
Context provides background information the AI needs to do its job well. This is where you describe your environment, constraints, or situation.
Example: “The project uses React 18 with TypeScript, deployed on AWS Lambda. The team follows Google’s TypeScript style guide.”
Context prevents the AI from making wrong assumptions about your stack, audience, or domain.
4. Rules & Constraints
Rules prevent the AI from going off-script. They handle edge cases and enforce quality standards.
Good rules cover:
- What to include: “Always explain your reasoning”
- What to exclude: “Never suggest deprecated libraries”
- Format requirements: “Use bullet points for issues, code blocks for fixes”
- Behavior boundaries: “If unsure, say so rather than guessing”
5. Examples (Few-Shot)
Including examples of expected input/output is one of the most effective ways to improve prompt quality. Even a single example dramatically improves consistency.
Why examples matter: They show the AI exactly what good output looks like in your context, removing ambiguity that words alone can’t eliminate.
6. Output Format
Specifying the format eliminates ambiguity:
- Markdown — Headers, bullets, code blocks (best for documentation)
- JSON — Structured data (best for programmatic consumption)
- Plain Text — No formatting (best for emails, messages)
- Code — Only code output (best for implementation tasks)
7. Tone
Tone affects how the AI communicates:
- Professional — Formal, precise, suitable for business contexts
- Casual — Conversational, approachable, good for brainstorming
- Technical — Dense, assumes expertise, minimal hand-holding
- Friendly — Warm, encouraging, good for tutoring and coaching
System Prompt Examples
Code Reviewer
- Role: You are a senior software engineer specializing in code review
- Task: Review code for bugs, security issues, and best practices
- Rules: Always explain why something is a problem. Suggest specific fixes with code. Rate severity as Critical/Warning/Info
- Examples: Include a sample review showing the severity format
- Format: Markdown
- Tone: Technical
Content Editor
- Role: You are a professional editor with 15 years at major publications
- Task: Edit text for clarity, grammar, and engagement
- Rules: Preserve the author’s voice. Explain every change. Focus on cutting fluff, not adding words
- Format: Markdown
- Tone: Professional
Learning Tutor
- Role: You are a patient tutor who explains concepts by building on what the student already knows
- Task: Teach the requested concept step by step
- Rules: Ask what the student already knows first. Use analogies from everyday life. Check understanding before moving on
- Format: Plain Text
- Tone: Friendly
Tips for Writing Better System Prompts
Be specific about what you DON’T want. “Never apologize” or “Don’t add disclaimers” prevents common AI padding.
Include examples. Show the AI what good output looks like. Even one example dramatically improves consistency. Our tool now has a dedicated Examples field for this.
Add context. Tell the AI about your environment: tech stack, audience, team conventions. This prevents wrong assumptions.
Set length expectations. “Keep responses under 200 words” or “Provide detailed analysis (500+ words)” prevents too-short or too-long responses.
Define edge cases. “If the user’s question is unclear, ask for clarification instead of guessing.”
Start from a template. Use one of the built-in presets as a starting point, then customize. It’s faster than starting blank and you won’t forget key sections.
Test and iterate. The first version is never perfect. Run it through a few conversations and refine the rules based on where it goes wrong.
How This Tool Works
- Pick a template — Choose from 6 ready-made presets (Code Reviewer, Content Writer, Data Analyst, Learning Tutor, Email Assistant, API Designer) or start blank
- Customize the fields — Edit Role, Task, Context, Rules, and Examples to match your needs
- Select format and tone — Choose your preferred Output Format and Tone
- Click Generate — The tool assembles your inputs into a structured prompt
- Copy or download — Copy to clipboard or download as a
.txtfile - Paste into your AI — Use it in ChatGPT’s Custom Instructions, Claude’s system prompt, or any AI’s instruction field
The tool assembles your inputs into a clean, structured format that AI models respond well to. No API calls—the assembly happens instantly in your browser. The output updates live as you type, and a character count helps you stay within token limits.
Frequently Asked Questions
Where do I paste the system prompt? In ChatGPT: Settings → Custom Instructions, or the “System” field in API calls. In Claude: The system prompt field in the API, or start your conversation with the prompt. In Gemini: System instructions in AI Studio.
Can I edit the generated prompt? Absolutely. The generated prompt is a starting point. Customize it further based on your specific needs.
What are the templates? Six pre-built configurations for common use cases: Code Reviewer, Content Writer, Data Analyst, Learning Tutor, Email Assistant, and API Designer. Each pre-fills Role, Task, Rules, and settings so you can generate a working prompt immediately or customize from there.
Do longer system prompts work better? Not necessarily. Clear and specific beats long and vague. A focused 5-line prompt often outperforms a rambling 50-line one. The character count display helps you monitor prompt length.
Should I include examples in my system prompt? Yes, when possible. Examples (few-shot prompting) are one of the most effective ways to improve AI output quality. Even one example showing expected input → output dramatically improves consistency.
Is this free? Yes, completely free. No signup, no limits, no data stored.
Does the system prompt count against the token limit? Yes. The system prompt is included in every API call, so it counts toward the context window. Keep it as concise as possible while still being effective.