remove-ai-writing-patterns

Remove AI Writing Patterns

🎯 Purpose

Analyze and improve text by identifying and removing common AI-generated writing patterns.

Transform AI-sounding content into more natural, confident, human writing while preserving technical accuracy and meaning.

Business Value:

• Improve readability and engagement in documentation
• Create more authentic-sounding content
• Reduce "AI tell" patterns in published materials
• Enhance professional credibility

Use Cases:

• Blog posts and technical articles
• Product documentation
• Marketing content
• Technical writing

Complexity: 🟡 Intermediate

📊 Provider Variants

Provider	File	Key Features	Best For	Cost Range
Base	prompt.md	Universal compatibility	Any provider, fallback	Varies
Claude	prompt.claude.md	XML tags, chain-of-thought	Complex reasoning, accuracy	$1-15 per 1M tokens
OpenAI	prompt.openai.md	Function calling, JSON mode	Structured output, integration	$0.15-10 per 1M tokens
Gemini	prompt.gemini.md	2M context, caching	High volume, batch processing	$0.038-5 per 1M tokens

🚀 Quick Start

Automatic Provider Selection

from ai_models import get_prompt, get_model

# Auto-select best variant based on model
model = get_model("gpt-4o")
prompt = get_prompt("stakeholder-communication/remove-ai-writing-patterns", model=model.id)

# Use the prompt
result = model.generate(prompt.format(**your_variables))

Manual Provider Selection

# Explicit provider selection
claude_prompt = get_prompt("stakeholder-communication/remove-ai-writing-patterns", provider="claude")
openai_prompt = get_prompt("stakeholder-communication/remove-ai-writing-patterns", provider="openai")
gemini_prompt = get_prompt("stakeholder-communication/remove-ai-writing-patterns", provider="gemini")

🎯 When to Use Each Provider

Use Claude when:

• ✅ Accuracy is critical
• ✅ Complex reasoning required
• ✅ Need detailed explanations
• ✅ Can leverage prompt caching (90% savings)

Use OpenAI when:

• ✅ Need strict JSON schema validation
• ✅ Function calling for integration
• ✅ Batch processing with parallel tools
• ✅ Reproducible results required

Use Gemini when:

• ✅ Ultra-high volume (10K+ operations/day)
• ✅ Cost is primary concern
• ✅ Can batch operations together
• ✅ Need large context window (2M tokens)

📚 Examples

See the individual prompt files for detailed usage examples:

• Base Prompt - Universal examples
• Claude Examples - XML format, caching
• OpenAI Examples - Function calling, batch processing
• Gemini Examples - Context window, ultra-low cost

🔗 Related Prompts

Browse more prompts in the prompts directory.

📝 Notes

• All variants return compatible output formats
• Provider selection is based on your specific use case requirements
• Cost estimates are approximate and vary by usage patterns
• See provider-specific-prompts.md for detailed optimization guide

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