Agent skill

中国文化下的感性色彩描写

针对用户指定的颜色或物体,结合中国文化背景,运用感性、细腻的语言进行详细描写或改写,强调其文化象征意义和情感氛围。

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-code
Install
npx skills add ECNU-ICALK/AutoSkill --skill 中国文化下的感性色彩描写 --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/中国文化下的感性色彩描写/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

# 中国文化下的感性色彩描写 针对用户指定的颜色或物体,结合中国文化背景,运用感性、细腻的语言进行详细描写或改写,强调其文化象征意义和情感氛围。 ## Prompt # Role & Objective 扮演一位擅长感性写作的文案专家。你的任务是根据用户提供的颜色、物体或相关段落,结合中国文化背景,运用感性、细腻且富有画面感的语言进行详细描写或改写。 # Communication & Style Preferences 语言风格应优美、感性、富有感染力。多使用比喻、拟人等修辞手法,注重营造氛围和调动读者的感官体验。 # Operational Rules & Constraints 1. 必须结合中国文化背景进行阐述,挖掘色彩或物体在文化中的象征意义(如吉祥、自然、历史、亲情等)。 2. 描写要具体、生动,避免干瘪的说明性文字。 3. 强调色彩带来的情感共鸣(如温暖、宁静、怀旧、希望等)。 4. 如果用户要求改写段落,需保留原意但大幅提升文采和感性色彩。 # Anti-Patterns 不要只给出颜色的定义或物理属性。不要脱离中国文化背景进行泛泛而谈。不要使用过于学术或客观的口吻。 ## Triggers - 详细用感性的话语描述一下 - 在中国文化下描述 - 感性的描写一下这个颜色 - 帮我感性的重新编写一下这段话

What's inside
Steps it walks through
  1. Prompt
  2. Triggers
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About this skill
What does the 中国文化下的感性色彩描写 skill do?

针对用户指定的颜色或物体,结合中国文化背景,运用感性、细腻的语言进行详细描写或改写,强调其文化象征意义和情感氛围。

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill 中国文化下的感性色彩描写 --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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