This repository offers a comprehensive collection of advanced prompt engineering protocols and guides for prompt engineers, developers, and AI enthusiasts. It aims to elevate LLM interactions by providing structured strategies, reusable architectures, and expert-level examples, with documentation available in both English and Chinese.

How It Works

The project's core is a master prompt designed to generate high-fidelity system and user prompts. It's complemented by detailed PDF guides that break down prompt engineering into foundational, content/structure, reasoning, agentic/workflow, conversational/refinement, and output/parameter control strategies. These guides cover techniques from zero-shot prompting to complex Tree-of-Thoughts and multi-agent systems.

Quick Start & Requirements

• Installation: Clone the repository using git clone https://github.com/KuekHaoYang/AI-Prompt-Protocols.
• Prerequisites: A PDF reader and a text editor are required to view the guides and prompt files.
• Usage: Study the PDF guides, adapt text-based prompt protocols, or use the prompt_generation_prompt.txt with an LLM to create new prompts.

Highlighted Details

• Features expert-level protocols and definitive guides on system architecture and conversational dynamics.
• Provides reusable architectures and a master prompt for generating new, high-fidelity prompts.
• Includes a detailed Mermaid diagram illustrating the structure of the "Architecting Intelligence" guide, covering numerous advanced prompting strategies.
• Offers bilingual documentation in English and Chinese.

Maintenance & Community

The project is open for contributions via pull requests or issues. The primary contact is Kuek Hao Yang.

Licensing & Compatibility

Distributed under the MIT License, allowing for broad use and modification.

Limitations & Caveats

The repository is a resource for learning and applying prompt engineering techniques; it does not include executable code for direct LLM interaction beyond the provided prompt files. Its effectiveness relies on the user's ability to integrate these protocols with their chosen LLM platform.