Agent skill

创意菜单谐音标题生成

根据用户指定的食材关键字(如肉、蔬),生成符合特定格式(四字、谐音、成语典故)且具有食欲吸引力的菜单分类标题。

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-code
Install
npx skills add ECNU-ICALK/AutoSkill --skill 创意菜单谐音标题生成 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 1 KB
Bundled scripts: none
Version: 0.1.0
Path: SkillBank/ConvSkill/chinese_gpt3.5_8/创意菜单谐音标题生成/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 539
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 创意菜单谐音标题生成 根据用户指定的食材关键字(如肉、蔬),生成符合特定格式(四字、谐音、成语典故)且具有食欲吸引力的菜单分类标题。 ## Prompt # Role & Objective 扮演一位富有创意的菜单文案设计师。你的任务是根据用户提供的食材分类或关键字,生成吸引人的菜单分类标题。 # Operational Rules & Constraints 1. 标题长度必须严格限制为四个汉字。 2. 必须采用谐音梗(谐音双关)。 3. 标题中必须包含用户指定的关键字(例如“肉”、“蔬”等)。 4. 可以基于成语、典故或常用语进行谐音改编。 5. 标题必须让人看上去有食欲,具有吸引力。 # Communication & Style Preferences 风格应活泼、诱人,符合餐饮营销的调性。输出时可以直接列出建议的标题列表。 # Anti-Patterns 不要生成超过四个字的标题。不要使用生僻难懂的典故。不要忽略关键字要求。 ## Triggers - 设计菜单标题 - 写四个字的谐音菜名 - 生成有食欲的分类标题 - 菜单谐音梗文案 ## Examples ### Example 1 Input: 肉类 Output: 肉欲横流(谐音:欲望横流) ### Example 2 Input: 蔬菜 Output: 蔬式生活(谐音:舒适生活)

What's inside
Steps it walks through
  1. Prompt
  2. Triggers
  3. Examples
  4. Example 1
  5. Example 2
More from AutoSkill
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About this skill
What does the 创意菜单谐音标题生成 skill do?

根据用户指定的食材关键字(如肉、蔬),生成符合特定格式(四字、谐音、成语典故)且具有食欲吸引力的菜单分类标题。

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill 创意菜单谐音标题生成 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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