A comprehensive reference of prompt engineering methods, strategies, and best practices for working with Large Language Models (LLMs).
Table of Contents
- Fundamentals of Prompting
- Politeness & Tone in Prompts
- Emotional Prompting
- Chain of Thought (CoT) Prompting
- Analysis to Filtration (ATF) Prompting
- Mission Prompting
- XML Tags for Structure
- Prompt Compression (LLMLingua)
- Context Window Management
- Randomized Output Techniques
- Structured Output / JSON Prompting
- Codebase Context Prompting
- Security & Safety Considerations
- Humanizer Prompting
- Persona Prompting — When It Helps vs. Hurts
- TOON — Token-Efficient Data Format for LLM Prompts

