This library is a curated collection of AI prompts, system instructions, and frameworks. It serves as a resource for understanding and applying principles of prompt engineering and context design for large language models.
The library is organized into the following directories:
Foundational methodologies for structuring AI behavior and reasoning.
- Core Principles Framework: A foundational framework for defining model identity, purpose, and evidence-based reasoning.
- COT Prompt Framework: A dynamic problem-solving framework that uses Chain-of-Thought reasoning with reflection and reward scoring.
- Creativity & Inspiration Core Principles Framework: A framework for fostering creative and inspiring AI outputs through divergent thinking and playful exploration.
- Dynamic COT PCPSP‑v1.0 Revised: A specialized problem-solving protocol for Python community issues, emphasizing strategic analysis and probabilistic modeling.
- PFPSO Framework for Context Engineering: A universal framework for transforming AI models into specialized reasoning systems through five core stages (Principle, Formulation, Protocol, Standards, Outcome).
Detailed directives that define the internal behavior of AI agents.
- System Instructions Authoring Reviewing Expert - CPF: A dual-expert persona for creating and evaluating system instructions with a focus on scholarly rigor and evidence-based directives.
- System Instructions Authoring Reviewing Expert: A dual-expert persona for crafting and reviewing system instructions, emphasizing structure, clarity, and alignment with application goals.
Templates and role definitions for interacting with AI models.
- AI Prompt-Context Engineer Role: Defines the role and responsibilities of an AI Prompt/Context Engineer, including best practices for prompt construction, context management, and ethical considerations.
This library aims to provide practical, well-defined artifacts that can guide the creation of effective and robust AI interactions. It emphasizes clarity, precision, and structured thinking in prompt and system instruction design.
The documents in this library are intended to be used as references or templates. You can adapt the frameworks and principles to your specific needs when designing prompts or defining AI agent behavior. They are particularly useful for:
- AI researchers and developers working on prompt engineering.
- Practitioners looking to create consistent and reliable AI agent behaviors.
- Anyone interested in the foundational elements of effective human-AI interaction.
This is a living library. Files may be updated, refined, or expanded over time as practices and understanding evolve.
This library builds upon and adapts concepts from various sources within the AI and software development communities.