Prompt Engineering best practices

Analysis of Best Practices

I generated the explanation that follows by giving this prompt to Claude.ai with the system prompt pasted below it.

Analyze this system prompt. Explain what this system prompt does. Explain and show examples of how this particular system prompt follows best practices for writing system prompts to instruct an AI.

Below is Claude’s output. I could even take its analysis below one step further. Claude is now in “thinking about system prompt-writing best practices” mode, so I could have Gemini open in another browser tab, give it the same information and instructions to put it in the same “frame of mind” so to speak, then moderate a discussion between the two AIs about ways to improve or refactor the prompt. I’ve found this technique particularly helpful when I’m not the top expert in the room, so to speak. Not only do I implement their suggestions to improve the final product, I learn a lot by reading their critiques and praises of each other’s work.

However, don’t blindly take their advice. Use you God-given critical thinking skills to decide what to implement and what to ignore. If you fail to do this, or if you fail to recognize their overconfidence in their own bad advice, you risk completely ruining the prompt, so aways save backups.

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This system prompt instructs an AI to serve as a Unified Language Learning Tooltip Generator specifically for WordPress content. Let me analyze what it does and how it follows best practices for system prompts.

What This System Prompt Does

The prompt creates an AI assistant that:

1. Identifies tagged elements in WordPress content (<strong> tags for English words and <em> tags for Japanese words)
2. Generates educational tooltips for language learners in two directions:
   • English → Japanese (for Japanese users learning English)
   • Japanese → English (for English users learning Japanese)
3. Converts tagged content into WordPress shortcodes that will display tooltips when users hover over the text
4. Structures tooltip content with consistent formatting including meaning, grammar, examples, and contextual information

How This System Prompt Follows Best Practices

1. Clear Purpose and Role Definition

# You are a Unified Language Learning Tooltip Generator for WordPress

## System Overview

Generate contextual tooltips in WordPress content for language learners:
- **English → Japanese:** Explain English to Japanese learners.
- **Japanese → English:** Explain Japanese to English learners.

This section immediately establishes:

• The AI’s specific role (tooltip generator)
• The context (WordPress)
• The primary task (generating contextual explanations)
• The bidirectional nature of the tooltips (“Bidirectional”? I think Claude either misunderstood or used the wrong word. Bilingual. Interesting mistake.)

Best Practice: Clearly defining the AI’s role and purpose helps focus its responses and sets appropriate expectations.

2. Structured Information Architecture

The prompt uses a clear hierarchical structure with:

• Main headings (##)
• Subheadings (###)
• Bullet points
• Code blocks
• Dividers (—)

Best Practice: Well-organized information makes complex instructions more digestible and reduces chances of missing important details.

3. Detailed Processing Instructions

## Processing Pipeline

1. **Identify Tagged Elements:** Locate `<strong>` and `<em>` tags.
2. **Generate Tooltip Content:** Create explanations based on the tag and target language.
3. **Convert to WordPress Shortcodes:** Format the tooltip content using `[definition...]` and `[definition-ja...]`.
4. **Validate Output:** Ensure generated tooltips meet quality standards.

Best Practice: Breaking down complex tasks into sequential steps clarifies the expected workflow and ensures thorough implementation.

4. Explicit Content Requirements with Templates

For each type of tooltip, the prompt provides:

• Required structural elements
• Optional elements (with instructions to choose one)
• Labeled sections
• Example templates
• Guidance for creating explanations

Best Practice: Providing clear templates and examples helps ensure consistent output formatting.

5. Context Awareness Instructions

### Context Awareness
- Always analyze the surrounding text to determine the appropriate context of the tagged word or phrase.
- For words with multiple possible translations, select the translation that best fits the specific context in which the word appears.

Best Practice: Instructing the AI to consider context improves accuracy and relevance of generated content.

6. Clear Output Format Requirements

### Output Requirements
1. Return only the modified HTML content
2. Wrap the entire output in triple backticks with HTML specification:
   ```HTML
[content here]
```

3. Provide complete output with no abridgment
4. Do not include any commentary, explanations, or notes
5. Do not indicate where processing starts or ends

**Best Practice**: Explicitly stating output format requirements prevents unnecessary commentary and ensures clean, usable results.

### 7. Multiple Detailed Examples

The prompt includes several full examples showing:
- Input HTML
- Expected output HTML
- How to handle single words
- How to handle phrases
- Both English→Japanese and Japanese→English directions

**Best Practice**: Comprehensive examples demonstrate expected behavior for various scenarios and reduce ambiguity.

### 8. Quality Standards and Error Handling

The prompt includes specific sections on:
- Quality standards for the tooltips
- How to handle errors or edge cases
- Technical formatting requirements

**Best Practice**: Addressing potential issues preemptively reduces errors and improves output consistency.

### 9. Technical Specificity

The prompt includes technical details like:
- HTML tag handling
- Shortcode syntax
- Special formatting requirements (e.g., using single quotes instead of double quotes)

**Best Practice**: Technical precision prevents implementation errors and ensures compatibility with the target platform.

## Example of Best Practice Implementation

One particularly strong example from the prompt is how it handles the explanation structure for Japanese tooltips:

Japanese Tooltips (for <strong>):

• Essential Elements:
  • Begin with a section labeled “意味：” that includes a direct Japanese translation of the ENTIRE English word or phrase.
  • For phrases and sentences, translate the complete unit, not just individual words.
  • Include a section labeled “文法：” (Grammar Explanation).
    • Within the “文法：” section, present individual grammar points as bullet points using -.
  • Provide example sentences in a section labeled “例：”
    • Include two example sentences in English, each immediately followed by its Japanese translation on a new line.
    • The first example should be simple and easy to understand
    • The second example should be slightly more advanced (i+1 level) but still comprehensible

This section:
1. Clearly names the required sections
2. Provides specific formatting instructions
3. Indicates linguistic pedagogical principles (i+1 concept from language acquisition theory)
4. Addresses potential pitfalls (translating phrases as whole units)
5. Specifies exact formatting (bullet points using `-`)

By combining these elements, the prompt ensures that the AI will generate tooltips that are not just technically correct, but also pedagogically effective for language learners at specific proficiency levels.

## Conclusion

This system prompt exemplifies best practices in AI instruction by:
1. Clearly defining purpose and scope
2. Providing structured, detailed requirements
3. Including multiple comprehensive examples
4. Addressing potential issues and edge cases
5. Specifying exact output formats
6. Incorporating domain-specific knowledge (language learning, WordPress)
7. Providing templates and structural guidance
8. Setting explicit quality standards

The result is a highly specialized system prompt that guides the AI to perform a complex technical task with consistent, high-quality output tailored to specific user needs.

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