Formatting your Prompts

Proper formatting of prompts is crucial for effective communication with AI models. Here are some tips and tricks on using the formatting languages of the GPT models in markdown and the anthropic models in xml.

Key Concepts

Emphasis

Highlight important information using various text styling techniques.

Structure

Organize your prompt with headings, lists, and nested elements.

Formatting Techniques

Here is everything you need to craft effective prompts in markdown and xml formatting:

Markdown

Basic Formatting

*Italic text* for mild emphasis
**Bold text** for strong emphasis
***Bold and italic*** for extra strong emphasis
`Code-style text` for technical terms or commands

Headings and Structure

# Main Prompt Title
## Section 1: Context
### Background Information
### Current Situation
## Section 2: Task Description

Lists and Steps

1. First step
2. Second step
3. Third step
- Bullet point 1
- Bullet point 2
- Sub-point A
- Sub-point B

Code Blocks

```python
def example_function():
    return "This is an example"

```json
{
  "key": "value",
  "array": [1, 2, 3]
}

XML

Basic Structure

 <prompt>
   <context>This is the context</context>
   <instruction>This is the main instruction</instruction>
   <important>This is crucial information</important>
   <example>This is an example</example>
 </prompt>

Roles and Dialogue

<conversation>
  <human>What's the weather like today?</human>
  <assistant>I don't have real-time weather data. Please check a reliable weather website or app for your location.</assistant>
</conversation>

Nested Structures

<prompt>
  <context>
    <background>Relevant background information goes here.</background>
    <current_situation>Description of the current scenario.</current_situation>
  </context>
  <task>
    <primary_objective>Main goal of the task</primary_objective>
    <secondary_objectives>
      <objective1>First secondary objective</objective1>
      <objective2>Second secondary objective</objective2>
    </secondary_objectives>
  </task>
</prompt>

Attributes and CDATA

<instruction type="main" priority="high" tone="professional">
  Craft a response addressing the user's concern.
</instruction>
<example_code>
<![CDATA[
def complex_function(x, y):
    return x * y + (x / y) if y != 0 else "Error: Division by zero"
]]>
</example_code>

Always test your formatted prompts to ensure they produce the desired results with your specific AI model.

Advanced Formatting Tips

1. Combine Formats

   For complex prompts, consider using a combination of Markdown and XML techniques to leverage the strengths of both formats.

2. Model-Specific Formatting

   Some AI models have specific formatting preferences:

   • GPT models typically work well with Markdown
   • Anthropic models are designed to interpret XML Always consult the model’s documentation for best results.
3. Test and Iterate

   Experiment with different formatting styles and structures. Test your prompts with the target AI model and refine based on the results.

By mastering these formatting techniques and utilizing appropriate structures, you can create highly effective prompts that clearly communicate your intentions to AI models, resulting in more accurate and useful responses.

Now that you know the proper formatting, read our comprehensive guide on how to write your system prompt.