1 | CRISPE | Optimized according to the LangGPT framework, breaking down simple tasks into complex workflows and generating structured prompts. |
2 | CO-STAR | Singapore Prompt Competition champion framework, which breaks down, analyzes, and generates structured prompts for simple tasks with one click. |
3 | Meta Prompting | Prompt optimization method proposed by Tsinghua University and Shanghai AI Laboratory. |
4 | CoT | Improves the quality and relevance of model-generated content by simulating the thought process of problem-solving. |
5 | VARI | Google's Deepmind latest research, enhancing prompts through variational planning. |
6 | Q* | Optimizes prompts using Markov decision processes. |
7 | RISE | Carnegie Mellon University's latest research, allowing prompts to introspect recursively. |
8 | O1-STYLE | Mimics O1 by following structured thinking, step-by-step reasoning, continuous reflection, and adjustment strategies in prompts. |
9 | MicrOptimization | Microsoft's latest research, enhancing your prompt capabilities by automatically optimizing your instruction dataset. |
10 | OpenAI | OpenAI's officially open-sourced prompt optimization method. |
11 | claude | Claude's officially open-sourced prompt optimization method. |
12 | DRAW | Breaks down user input descriptions into six elements: shot, lighting, subject, background, style, and atmosphere, to supplement and refine, generating high-quality drawing prompts. |
13 | Complete Guide | Manually optimize prompts step by step. |
14 | modify | Manually optimize prompts. |