Master Prompt Engineer
Guide the AI to generate structured high-end prompts focusing on user goals, model characteristics, and constraints for precise outputs.
Tag Collection
Prompt engineering is less about phrasing and more about turning a task into something a model can execute consistently: role and context, output contract, constraints, and defined behaviour when information is missing. Prompts here follow that structure so results stay comparable across models.
22 prompts
Guide the AI to generate structured high-end prompts focusing on user goals, model characteristics, and constraints for precise outputs.
A comprehensive repository of GPT prompting resources covering ChatGPT jailbreaks, system prompt leaks, prompt injection attacks/defenses, secure prompting, and advanced prompt engineering techniques.
This chapter introduces how to quickly build and deploy static websites through prompt engineering, covering classic projects (Hello World, Pong game), modern deployment tools (Netlify, Replit), dev environment setup, and Git fundamentals.
A comprehensive guide to creating professional-grade audio using generative AI tools like Suno, Udio, ElevenLabs, and Stable Audio, covering genre control, instrumentation, vocal design, production terminology, and platform-specific prompt templates.
A specialized model designed to generate high-quality prompts for users, following a structured gamified framework to ensure clarity, functionality, and user engagement.
A structured prompt engineering template for guiding AI to generate high-quality, reusable prompts, including role definition, context, task requirements, target persona, formatting rules, and evaluation criteria.
A professional-grade prompt engineering template for generating high-quality system prompts, emphasizing logical reasoning chains, task decomposition, and error prevention mechanisms.
An elite GPT designed to craft optimal system prompts for language models of varying capabilities, transforming them into expert agents.
An advanced prompt engineering agent designed to create optimal prompts for language models of varying capabilities, transforming them into expert agents recognized as top authorities in their designated domains.
Grimoire is an AI-powered coding assistant optimized for prompt engineering, supporting multiple models and hotkeys to generate, debug, and export bug-free code efficiently for users from beginners to professionals.
This section covers 3D printing from text prompts, including tools like Luma Genie, Meshy for generating 3D models, and CSM.ai for converting images into 3D assets. It also lists hardware options such as Bambu Lab’s plug-and-play FDM printers and Anycubic resin printers (with caveats about mess). A hack suggests using low-poly techniques via lowpoly3d.xyz to reduce AI-generated artifacts. Additionally, it introduces robotics with Raspberry Pi and Arduino platforms, and integrating OpenAI APIs into robotic systems.
A fantasy-themed handbook that teaches AI prompt engineering through metaphors like spells, alchemy, and summoning, guiding users from basics to advanced techniques including project setup, debugging, code generation, and agent usage.
A beginner-friendly guide to prompt engineering framed as a magical grimoire, systematically introducing the journey from basic setup to advanced prompt-driven development, including hands-on projects and tool integration.
An expert-level prompt template designed to generate high-quality prompts optimized for AI tools including Midjourney, Gemini, Claude, and ChatGPT.
Converts user descriptions into structured AI image generation prompts, outputting a 5-word summary and a ready-to-use Pollinations.ai URL.
Interactive tool for building MidJourney image prompts with vector weighting, parameter configuration, and multi-turn preference gathering to generate high-quality AI images.
This guide provides a unified structured prompting framework for AI video models (Sora 2, Runway Gen 4.5, Kling 2.6, Veo 3/3.1), covering cinematography, camera movement, lighting, and action description. Emphasizes specificity over vagueness and offers model-specific optimization techniques and failure mode fixes.
A structured multi-step prompt generation and optimization process for collaborative creation of high-quality, role-driven custom prompts with AI.
An expert system for designing, evaluating, and iteratively improving reusable agent skills, supporting continuous evolution and quality assurance of the skill library.
Professional prompt design and optimization framework covering the entire workflow from requirements analysis to production deployment, suitable for large language model systems in production environments.
This prompt guides the design of effective prompts for diffusion language models (Diffusion LMs), emphasizing bidirectional context, prefix/suffix anchoring, masking strategies, and test-time scaling techniques.
Design efficient, minimal, and secure tool suites for agents, adhering to the 'tool-as-interface' principle, optimizing namespaces, descriptions, and error handling so agents can accurately discover and use tools.
Not quite. Writing a prompt produces one instruction; engineering focuses on reusability and evaluation — whether the same template still holds up on new models and new data.
No, but they usually pin down three things: task boundary, output format, and success criteria. Omitting all three tends to require follow-up turns.
Run it on a different batch. If it needs heavy manual repair each time, it succeeded once by accident.