Bug Triage Assistant
Convert scattered bug notes, Slack messages, or user complaints into structured engineering tasks with reproduction steps, severity, and root cause hypothesis.
View Workflow →Prompt Builders
System Prompt Generator
Configure role, behavior rules, and output structure for your AI system. Generates a structured system prompt ready to paste into any AI model. Runs entirely in your browser.
Applies light formatting and structure adjustments for different AI models.
Behaviors the AI must consistently follow. One rule per line.
Hard limits and out-of-scope behaviors. One rule per line.
When the AI should express uncertainty or defer to a human.
Show the AI what good input and expected output look like.
Response Style
Word limit adds an instruction for future AI replies — it does not shorten this generated prompt.
Generated Prompt
Try with:
AI Workflow Library
Workflow starters that customize this tool
Code Review Assistant
Turn AI into a structured pull request reviewer that catches risky changes, flags maintainability issues, and suggests missing test coverage.
View Workflow →Customer Support Agent
Configure AI to answer support questions within your actual policy boundaries — not generic best-guess answers.
View Workflow →Escalation Response Assistant
Structure the escalation decision for a high-risk support situation — consistent criteria, clear rationale, and a ready brief for the team taking over.
View Workflow →How it works
Fill in the role and objective, describe the operational context, and choose tone and output format. The Advanced section lets you specify must-do rules, hard restrictions, escalation handling, and example inputs/outputs. Click Generate Prompt to produce a structured system prompt from your inputs. Everything runs in your browser — nothing is sent to a server.
Use cases
- Configuring consistent AI behavior for engineering review workflows
- Building support agent prompts that stay within documented policy boundaries
- Defining research synthesis instructions that preserve source attribution
- Generating starting-point prompts for internal tools, prototypes, or team use
Pro tips
- Role and Objective work together — the role defines what the AI is, the objective defines what it's trying to accomplish in this specific context.
- The Must Not Do section is often more valuable than Must Do. Explicit restrictions prevent the AI from improvising in ways you haven't anticipated.
- Use the Example Inputs/Outputs field to anchor abstract instructions. A concrete example does more to shape output quality than three extra rules.
- For Claude, the XML Tags format reduces hallucination on structured tasks. For ChatGPT, Markdown Sections tends to produce clean output.
FAQ
Does this tool send my inputs to an AI model?
No. All prompt generation happens in your browser using JavaScript. Nothing is sent to a server or external API.
What is the difference between Must Do and Rules?
They're the same thing — Must Do instructions become the Rules section in your generated prompt. The field name describes the intent: behaviors your AI system must consistently follow.
Which models work with the generated prompts?
The Target Model selector formats output for Claude, ChatGPT/OpenAI, Gemini, or a generic format that works with any standard instruction-following model. The content is model-agnostic — the format differs slightly.
Can I edit the generated prompt after it's produced?
Yes. The output area is fully editable. Adjust the generated prompt directly before copying or downloading.
What does the token estimate mean?
The token count is an approximation using a 1 token ≈ 4 characters heuristic. Actual counts vary by model and tokenizer — treat it as a rough guide, not a precise measurement.
What does Prompt Depth mean?
Depth is a heuristic that reflects how many sections of the form are filled. Basic means only role is defined. Solid means role, context, and some rules. Detailed means role, context, rules, restrictions, and additional guidance are all populated.