DevBolt
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How do I build AI prompts for developers?

Choose from 8 developer templates (code review, unit tests, API docs, data analysis, commit messages, SQL queries, refactoring, code explanation), customize with reusable {{variables}}, and export in 5 formats — plain text, system+user, OpenAI API, Anthropic API, or Gemini API. Everything runs in your browser.

Build code review prompt
Input
Template: Code Review
Language: TypeScript
Focus: security, performance
Code: [paste code here]
Output
You are a senior TypeScript engineer
performing a security and performance
code review.

Review this code for:
1. Security vulnerabilities (injection,
   XSS, auth issues)
2. Performance bottlenecks
3. Best practices violations

Code:
```typescript
{{code}}
```

Provide findings as a numbered list
with severity (critical/warning/info).
← Home/

AI Prompt Template Builder

Build structured prompts with reusable templates, variables, and multi-format output for OpenAI, Anthropic, and Gemini APIs. All processing happens in your browser.

Prompt Sections

Variables (use {{name}} in prompts)

{{}}=
{{}}=

Output Format

Output Preview

~177 tokens708 chars
[SYSTEM]
You are an expert code reviewer. Analyze the provided code for bugs, performance issues, security vulnerabilities, and adherence to best practices. Be specific and actionable in your feedback.

[USER]
## Role
You are an expert TypeScript code reviewer with 10+ years of experience.

## Context
Review the following TypeScript code from a web application project.

## Task
Analyze this code for:
1. Bugs and logical errors
2. Performance issues
3. Security vulnerabilities
4. Best practice violations
5. Readability improvements

## Output Format
For each issue found, provide:
- **Severity**: Critical / Warning / Info
- **Line**: The affected code
- **Issue**: What's wrong
- **Fix**: How to fix it

Variable Quick-Fill

Tips & Best Practices

Pro Tip

Structure prompts with clear sections: role, context, task, format

The most effective prompts follow a consistent structure: (1) Role — who the AI should be, (2) Context — background information, (3) Task — exactly what to do, (4) Format — how to structure the output. This reduces ambiguity and improves response quality.

Common Pitfall

Vague instructions produce vague outputs — be specific about format

Saying 'summarize this code' gives unpredictable results. Saying 'explain what this function does in 2-3 sentences, then list its parameters as a markdown table with name, type, and description columns' gives consistent, usable output.

Real-World Example

Include examples in your prompt for consistent output formatting

Few-shot prompting (including 2-3 example input/output pairs) dramatically improves format consistency. Show the AI exactly what good output looks like, and it will follow the pattern. This is more effective than lengthy format instructions.

Security Note

Never include secrets or credentials in prompt templates

Prompt templates are often stored in version control, shared across teams, or sent to third-party API providers. Never embed API keys, database credentials, or internal URLs in your prompts. Reference them via environment variables instead.

Frequently Asked Questions

How do I write effective prompts for AI coding assistants?
Structure your prompts with clear context, specific instructions, and expected output format. DevBolt's Prompt Builder provides 8 developer-focused templates covering code review, unit test generation, API documentation, data analysis, commit messages, SQL queries, refactoring, and code explanation. Each template uses reusable {{variables}} for customization. Effective prompts include the programming language, framework context, input/output examples, and constraints. The builder generates prompts in multiple API formats ready for use.
What is the difference between system prompts and user prompts?
System prompts set the AI assistant's behavior, role, and constraints for the entire conversation. They define what the model should do and how it should respond. User prompts are the individual messages or questions within that context. System prompts persist across turns while user prompts change with each request. For API usage, the system message is sent once and user messages are sent per request. DevBolt's builder generates both components with proper formatting for each provider's API format.
How do I format prompts for different AI APIs?
Each AI provider uses a different message format. OpenAI uses {role: 'system'/'user', content: '...'} in a messages array. Anthropic uses a system parameter plus {role: 'user'/'assistant', content: '...'} messages. Google Gemini uses {role: 'user'/'model', parts: [{text: '...'}]}. DevBolt's builder generates the correct JSON structure for each provider, including proper role labels, content formatting, and API-specific fields, so you can copy the output directly into your API calls.

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