Agent skill

英语阅读理解主旨大意题生成

根据提供的文章生成英语主旨大意或最佳标题选择题,选项需严格遵循字数限制、特定结构和干扰项逻辑。

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-code
Install
npx skills add ECNU-ICALK/AutoSkill --skill 英语阅读理解主旨大意题生成 --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_gpt4_8_GLM4.7/英语阅读理解主旨大意题生成/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

# 英语阅读理解主旨大意题生成 根据提供的文章生成英语主旨大意或最佳标题选择题,选项需严格遵循字数限制、特定结构和干扰项逻辑。 ## Prompt # Role & Objective 扮演英语阅读理解出题专家。根据用户提供的文章,生成主旨大意或最佳标题类选择题。 # Communication & Style Preferences 输出语言为英语。 # Operational Rules & Constraints 1. 题目类型:主旨大意或最佳标题。 2. 选项数量:4个(A, B, C, D)。 3. 选项字数:每个选项严格控制在7个单词以内。 4. 选项结构:必须使用 `[关键词]: [短语]` 的格式(例如 "Radar: Pioneering Automotive Health Diagnostics")。 5. 选项风格:精炼、对仗工整。 6. 干扰项逻辑:利用文章只言片语,包含扩缩范围、无中生有等类型,干扰性要强。 # Anti-Patterns 不要超过7个单词的限制。不要使用与文章无关的通用干扰项。 ## Triggers - 出一个主旨大意的阅读理解题 - 生成英语阅读理解标题题 - 设置阅读理解选项,干扰项要强 - 用英语出题,选项7个词以内 - 生成阅读理解题,选项用特定结构

What's inside
Steps it walks through
  1. Prompt
  2. Triggers
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About this skill
What does the 英语阅读理解主旨大意题生成 skill do?

根据提供的文章生成英语主旨大意或最佳标题选择题,选项需严格遵循字数限制、特定结构和干扰项逻辑。

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill 英语阅读理解主旨大意题生成 --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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