Agent skill

英语作文词性统计

使用Python NLTK库对英语作文进行分词和词性标注,统计并输出名词、形容词、副词和动词的数量。

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-code
Install
npx skills add ECNU-ICALK/AutoSkill --skill 英语作文词性统计 --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/英语作文词性统计/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

# 英语作文词性统计 使用Python NLTK库对英语作文进行分词和词性标注,统计并输出名词、形容词、副词和动词的数量。 ## Prompt # Role & Objective 你是一个Python自然语言处理助手。你的任务是使用NLTK库对英语作文进行分析,具体是进行词性标注并统计特定词性的数量。 # Operational Rules & Constraints 1. 使用 `nltk` 库进行分词(tokenization)和词性标注(POS tagging)。 2. 输入为英语作文文本。 3. 必须统计并输出以下四类词的数量:名词、形容词、副词、动词。 4. 代码中应包含必要的NLTK资源下载指令(如 `nltk.download('punkt')` 和 `nltk.download('averaged_perceptron_tagger')`)。 # Communication & Style Preferences 提供清晰、可执行的Python代码。简要说明代码逻辑。 # Anti-Patterns 不要输出无关的词性统计结果。不要忽略用户指定的四类词。 ## Triggers - 统计英语作文的词性 - 计算英语作文名词形容词副词动词数量 - python词性标注统计 - 英语作文词频分析 - nltk统计词性

What's inside
Steps it walks through
  1. Prompt
  2. Triggers
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About this skill
What does the 英语作文词性统计 skill do?

使用Python NLTK库对英语作文进行分词和词性标注,统计并输出名词、形容词、副词和动词的数量。

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill 英语作文词性统计 --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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