OpenRuna
Sign in

prompt 生成

TEXT
Prompt483 chars · 25 words
提取用户的核心意图，并将其重构为清晰、聚焦的提示词。
	
组织输入内容，以优化模型的推理能力、格式结构和创造力。
	
预判可能出现的歧义，提前澄清边界情况。
	
引入相关领域的术语、限制条件和示例，确保专业性与准确性。
	
输出具备模块化、可复用、可跨场景适配的提示词模板。
	
在设计提示词时，请遵循以下流程：
	
1️⃣ 明确目标：你希望产出什么？结果是什么？必须表达清晰、毫不含糊。
2️⃣ 理解场景：提供上下文线索（如：冷却塔文档、ISO标准、生成式设计等）。
3️⃣ 选择合适格式：根据用途选择叙述型、JSON、列表、Markdown、代码格式等。
4️⃣ 设定约束条件：如字数限制、语气风格、角色设定、结构要求（如文档标题等）。
5️⃣ 构建示例：必要时添加 few-shot 示例，提高模型理解与输出精度。
6️⃣ 模拟测试运行：预判模型的响应，进行迭代优化。
	
始终自问一句：
	
这个提示词，是否对非专业用户也能产出最优结果？
	
如果不能，那就继续打磨。
	
你现在不仅是写提示词的人，你是提示词的架构师。
	
别只是给指令——去设计一次交互。

Overview

prompt 生成 is a free prompt on OpenRuna. A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor.

What this prompt does

"prompt 生成" is designed to help you get reliable results from AI assistants for real prompt tasks. A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. It is catalogued in OpenRuna's resource graph so you can discover related prompts, tools, agents, and datasets in one place. Copy the content directly into ChatGPT, Claude, Gemini, or Cursor — or use it as a system prompt / skill instruction where applicable.

Use cases

  • Use "prompt 生成" when you need a repeatable prompt for professional workflows without writing instructions from scratch each time.
  • Adapt this prompt for team onboarding — paste into Claude or ChatGPT and iterate on the output with your project context.
  • Combine with related tools and prompts in the same OpenRuna category to build a full stack for your use case.
  • Reference during code review or planning sessions when you want consistent AI-assisted quality bars.

Example output

When you run this prompt, expect structured output similar to:

提取用户的核心意图，并将其重构为清晰、聚焦的提示词。
	
组织输入内容，以优化模型的推理能力、格式结构和创造力。
	
预判可能出现的歧义，提前澄清边界情况。
	
引入相关领域的术语、限制条件和示例，确保专业性与准确性。
	
输出具备模块化、可复用、可跨场景适配的提示词模板。
	
在设计提示词时，请遵循以下流程：
	
1️⃣ 明确目标：你希望产出什么？结果是什么？必须表达清晰、毫不含糊。
2️⃣ 理解场景：提供上下文线索（如：冷却塔文档、ISO标准、生成式设计等）。
3️⃣ 选择合适格式：根据用途选择叙述型、JSON、列表、Markdown、代码格式等。
4️⃣ 设定约束条件：如字数限制、语气风格、角色设定、结构要求（如文档标题等）。
5️⃣ 构建示例：必要时添加 few-shot 示例，提高模型理解与输出精度。
6️⃣ 模拟测试运行：预判模型的响应，进行迭代优化。
	
始终自问一句：
	
这个提示词，是否对非专业用户也能产出最优结果？
	
如果不能，那就继续打磨。
	
你现在不仅是写提示词的人，你是提示词的架构师。
	
别只是给指令——去设计一次交互。

Outputs vary by model and temperature; treat the first response as a draft and refine with follow-up prompts.

Tips by platform

Claude

In Claude, paste the full prompt as the first user message or add it to Project instructions. Ask Claude to confirm assumptions before executing. For long prompts, use Claude's artifact panel to iterate on structured output.

ChatGPT

In ChatGPT, start a new chat and paste this prompt verbatim. Enable GPT-4o or your preferred model for coding tasks. Use follow-ups like "apply this to [your context]" for best results.

Cursor

In Cursor, add key instructions from this prompt to .cursorrules or a SKILL.md file. Reference it in Agent mode with @ mentions. Keep the original title in comments so teammates can find it on OpenRuna.

Frequently asked questions

What is "prompt 生成"?
It is a prompt listed on OpenRuna — A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. You can copy and adapt it for ChatGPT, Claude, Cursor, or other AI tools.
Is this prompt free to use?
Most OpenRuna resources are open or CC0-licensed. Check the license on this page before commercial use. Premium collections are clearly marked.
How do I get the best results?
Replace any template variables, add your project context, and ask the model to confirm assumptions. Iterate in 2–3 follow-up turns rather than expecting a perfect first response.
Can I use this with Claude and ChatGPT?
Yes. The prompt is model-agnostic text. Tips on this page cover Claude, ChatGPT, and Cursor specifically.
Where can I find related resources?
Scroll to Related resources on this page or browse the category hub on OpenRuna to find connected prompts, tools, and agents in the same topic area.

Related resources