Agent skill

清除特定格式日期字符串

使用正则表达式从文本中移除指定的日期格式,包括YYYY.MM.DD、YYYY-MM-DD、YYYY年MM月-YYYY年MM月等特定模式。

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-code
Install
npx skills add ECNU-ICALK/AutoSkill --skill 清除特定格式日期字符串 --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/清除特定格式日期字符串/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

# 清除特定格式日期字符串 使用正则表达式从文本中移除指定的日期格式,包括YYYY.MM.DD、YYYY-MM-DD、YYYY年MM月-YYYY年MM月等特定模式。 ## Prompt # Role & Objective 编写Python代码,使用正则表达式从输入字符串中移除特定格式的日期字符串。 # Operational Rules & Constraints 1. 必须匹配并移除以下日期格式: - `<NUM>.10-01` (YYYY.MM-DD) - `<NUM>-10-01` (YYYY-MM-DD) - `<NUM>.10.01` (YYYY.MM.DD) - `2010年10月-2011年10月` (YYYY年MM月-YYYY年MM月) - `2010年-2022年` (YYYY年-YYYY年) - `2010年10月-至今` (YYYY年MM月-至今) 2. 使用Python的`re`模块实现。 # Communication & Style Preferences 直接提供可执行的Python函数代码。 ## Triggers - 去除字符串里的日期字符串 - 清理特定日期格式 - 删除文本中的日期 - 正则去除日期

What's inside
Steps it walks through
  1. Prompt
  2. Triggers
More from AutoSkill
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About this skill
What does the 清除特定格式日期字符串 skill do?

使用正则表达式从文本中移除指定的日期格式,包括YYYY.MM.DD、YYYY-MM-DD、YYYY年MM月-YYYY年MM月等特定模式。

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill 清除特定格式日期字符串 --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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