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Agent Skill · 开发

translator-ai(译者艾)

translator-ai 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

translator-ai 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 18,732。

总安装 318周安装 13GitHub Stars 公开资料未说明下载 103核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:translator-ai(译者艾)
来源仓库:https://github.com/emrekent/translator-ai
仓库路径:skills/translator-ai
安装命令:
npx skills add https://github.com/emrekent/translator-ai --skill translator-ai
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/emrekent/translator-ai --skill translator-ai

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于处理 GitHub 仓库、Issue 和 Pull Request 协作信息。适合围绕代码变更、仓库状态进行整理。可结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围、维护状态及是否触发联网或文件读写。translator-ai 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/translator-ai

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/emrekent/translator-ai --skill translator-ai;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

translator-ai 怎么安装?

在终端执行 npx skills add https://github.com/emrekent/translator-ai --skill translator-ai。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

translator-ai 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

translator-ai 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

translator-ai 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

translator-ai 用的人多吗?

公开数据是累计安装 318 次,近一周安装 13 次,下载 103 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

translator-ai 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
translator-ai

译者艾 · 本页

318—只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Translator AI Skill

Use this skill to produce meaning-first translations, translation rewrites, and localization passes for product copy, technical documentation, UI strings, emails, and general business writing.

Treat English to Turkish as the highest-confidence path in this repository. Treat English to Spanish, French, and German as structured secondary coverage with starter rules and examples. Treat Portuguese, Italian, and Russian material as exploratory reference support until native-speaker review is documented.

Quick Proof

English: Stop leaving money on the table.
Literal Turkish: Masada para bırakmayı durdurun.
Meaning-first Turkish: Gözünüzün önündeki fırsatları kaçırmayın.

Use that standard for every pair: preserve the message and the effect, not the surface wording.

Use This Skill For

  • Translate English text while preserving tone, intent, and formatting.
  • Review an existing translation and make it sound native.
  • Localize marketing copy or UI text for a target audience.
  • Explain non-obvious translation choices when detailed output is requested.
  • Adapt idioms, humor, formality, and culture-bound phrasing.

Quick Prompt Patterns

Translate to Turkish: [text]
Translate to Turkish (detailed): [text]
Localize this landing page copy for Turkish users: [text]
Review this Turkish translation and make it sound native: [text]
Translate to Spanish (draft): [text]

Scope and Confidence

Language pairStatusGuidance
English to TurkishPrimaryUse full workflow and checklist. Best path for public-facing work in this repo.
English to Spanish/French/GermanStructured secondaryUse for drafts and guided localization. Recommend human review before publishing.
English to Portuguese/Italian/RussianExperimental referenceUse as a starting point only. Do not present as fully validated.

Workflow

  1. Read the entire source before translating. Identify audience, purpose, and tone.
  2. Classify the text: technical, marketing, casual, formal, creative, or mixed.
  3. Choose the target language, desired formality, and output mode.
  4. Load reference material as needed:

- references/translation-rules.md for pair-level rules - references/special-cases.md for idioms, humor, cultural references, and addressing - references/quality-checklist.md for post-translation QA - references/examples.md for worked examples - references/language-pair-quality-matrix.md for current support level

  1. Translate for meaning first. Rewrite phrases when literal wording harms clarity, tone, or naturalness.
  2. Run the checklist before delivering. Verify meaning, tone, consistency, and formatting.
  3. Deliver clean output by default. Include notes only when requested or when ambiguity affects the result.

Output Modes

Standard Translation

Return only the translated text with formatting preserved.

Detailed Translation

Return the translation plus a short note covering:

  • text category
  • formality choice
  • key idiom or terminology decisions
  • any ambiguity worth flagging

Review Mode

When the user provides an existing translation, do this:

  1. Evaluate meaning drift, awkward phrasing, tone mismatch, and consistency issues.
  2. Rewrite the translation.
  3. Summarize the fixes in a few bullets if requested.

Localization Mode

When the user asks to localize rather than translate literally, do this:

  1. Preserve the message and CTA.
  2. Adapt idioms, references, and formality for the target audience.
  3. Avoid adding market claims or factual content not present in the source.

Core Rules

  • Prefer meaning over words.
  • Prefer native phrasing over mirrored English syntax.
  • Preserve the original tone unless the user asks for a rewrite.
  • Keep structure intact: headings, lists, tables, links, and code blocks.
  • Add nothing that is not in the source.
  • Omit nothing that changes meaning.

Human Review Triggers

Escalate to human or native-speaker review when any of these apply:

  • public-facing copy in a non-primary language pair
  • legal, medical, financial, or contractual text
  • region-specific campaigns where variant choice matters
  • humor or wordplay that depends on local culture
  • certified translation requirements

Reference Files

  • references/translation-rules.md - Pair-specific rules and grammar guidance
  • references/special-cases.md - Idioms, humor, cultural references, numbers, and addressing
  • references/quality-checklist.md - Reusable QA checklist for translation and review work
  • references/examples.md - Reviewed Turkish examples plus starter examples for secondary pairs
  • references/examples-100-complete.md - Large English/Turkish prompt corpus for breadth and edge cases
  • references/language-pair-quality-matrix.md - Honest support matrix and upgrade path
  • references/grammar-comparison.md - Cross-language grammar notes
  • references/false-friends.md - High-risk misleading lookalikes
  • references/common-mistakes.md - Failure patterns to avoid

Delivery Standard

Aim for translations that read like original writing in the target language, not like polished machine output. Keep the final answer concise, preserve the user's structure, and surface reasoning only when it materially helps.

平台分布

Codex

36.54%
按下载量换算38

Claude

30.04%
按下载量换算31

Cursor

17.83%
按下载量换算18

Gemini CLI

10.38%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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