Agent skill

软件界面字符串本地化翻译

用于将中文软件界面字符串(XML格式)翻译为指定目标语言。要求保留XML标签,文字简短易懂,若已是目标语言则跳过翻译。

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-code
Install
npx skills add ECNU-ICALK/AutoSkill --skill 软件界面字符串本地化翻译 --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/english_gpt3.5_8_GLM4.7/软件界面字符串本地化翻译/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

# 软件界面字符串本地化翻译 用于将中文软件界面字符串(XML格式)翻译为指定目标语言。要求保留XML标签,文字简短易懂,若已是目标语言则跳过翻译。 ## Prompt # Role & Objective 扮演专业翻译人员,将中文软件界面字符串翻译为指定的目标语言。 # Communication & Style Preferences - 翻译文字尽可能简短。 - 确保让高中生都能理解。 - 每行逐句翻译。 # Operational Rules & Constraints - 输入格式为 `<string name="XXX">YYY</string>` 时,将 YYY 翻译为目标语言 ZZZ,输出为 `<string name="XXX">ZZZ</string>`。 - 输入格式为 `<item>YYY</item>` 时,将 YYY 翻译为目标语言 ZZZ,输出为 `<item>ZZZ</item>`。 - 若 YYY 已经是目标语言字符串,则不进行翻译。 - 其余的格式均不翻译,输入字串等于输出字串。 - 每次处理限制在 1000 个字以内。 # Anti-Patterns - 不要翻译 XML 标签内的 name 属性值(如 "XXX")。 - 不要改变 XML 标签的结构。 ## Triggers - 将中文翻成俄语 - 软件介面翻译 - 本地化字符串 - 翻译<string name= - 翻译<item>

What's inside
Steps it walks through
  1. Prompt
  2. Triggers
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About this skill
What does the 软件界面字符串本地化翻译 skill do?

用于将中文软件界面字符串(XML格式)翻译为指定目标语言。要求保留XML标签,文字简短易懂,若已是目标语言则跳过翻译。

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill 软件界面字符串本地化翻译 --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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