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Agent Skill · 研究检索

localize-campaign(本地化活动)

localize-campaign 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

localize-campaign 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 50,488。

总安装 612周安装 25GitHub Stars 66下载 198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:localize-campaign(本地化活动)
来源仓库:https://github.com/indranilbanerjee/digital-marketing-pro
仓库路径:skills/localize-campaign
安装命令:
npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill localize-campaign
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/indranilbanerjee/digital-marketing-pro --skill localize-campaign

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

localize-campaign 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果时使用。适用于数字营销活动中的区域化内容策划与市场策略参考。可协助收集竞品案例、本地化文案模板或渠道投放数据。

安装命令为 npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill localize-campaign。注意所涉信息可能包含商业机密,需遵守数据使用协议与隐私政策。

来源仓库内路径:skills/localize-campaign

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/indranilbanerjee/digital-marketing-pro --skill…;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

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

localize-campaign 怎么安装?

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

localize-campaign 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。

localize-campaign 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

localize-campaign 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。

localize-campaign 用的人多吗?

公开数据是累计安装 612 次,近一周安装 25 次,下载 198 次,GitHub 66 星。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。

localize-campaign 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
localize-campaign

本地化活动 · 本页

61266调用外部服务未明确有提醒

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

/dm:localize-campaign

Purpose

Full campaign localization across multiple target markets. This command takes all campaign assets — emails, ads, social posts, landing pages, video scripts, push notifications — and adapts them for each target market. It goes far beyond translation: cultural references are adjusted, compliance elements are modified per region, SEO is localized, creative recommendations are adapted, and assets are prepared for multilingual publishing.

This is the comprehensive localization workflow for market expansion. Where /dm:translate-content handles a single piece of content, /dm:localize-campaign orchestrates the localization of an entire campaign across multiple markets simultaneously. It coordinates translation service routing per language, transcreation for emotional content, market-specific compliance additions, cultural adaptation based on Hofstede cultural dimensions, localized SEO, RTL formatting for applicable languages, and produces a deployment-ready package per market with quality scores and publishing checklists.

Input Required

The user must provide (or will be prompted for):

  • Campaign assets: Content for localization, provided as:

- File paths per asset type (e.g., "emails: /campaign/email-welcome.html, /campaign/email-follow-up.html; ads: /campaign/fb-ad.txt, /campaign/google-ad.txt; social: /campaign/ig-post.txt") - A campaign directory (e.g., "/campaign-q1/") — all files will be categorized by type based on naming conventions or metadata - Inline content blocks with asset type labels

  • Target markets: One or more market codes in language-region format (e.g., hi-IN, de-DE, ja-JP, fr-FR, ar-SA, pt-BR, es-MX). Each code specifies both the language and the cultural/regulatory context
  • Campaign brief or strategy document: Optional — provides campaign objectives, messaging hierarchy, key themes, and audience segments. Used to inform transcreation decisions and ensure localized versions maintain strategic alignment
  • Market-specific compliance requirements: Optional — additional regulatory, legal, or industry requirements per market beyond what is already in the brand profile (e.g., "Germany requires Impressum link", "India requires MRP display", "Saudi Arabia prohibits alcohol imagery references")
  • Budget allocation per market: Optional — if provided, influences prioritization (higher-budget markets get full transcreation and deeper cultural adaptation; lower-budget markets get quality translation with standard adaptation)
  • Priority markets: Optional — markets to process first and with the most thorough adaptation. Other markets receive standard localization
  • Asset priority: Optional — which asset types are most important (e.g., "landing pages are highest priority, social posts are secondary"). Affects depth of review and transcreation effort

Process

  1. Load brand context: Read ~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Extract full language configuration — do_not_translate terms, translation_preferences, locale_formatting rules per market, approved markets list. Load compliance rules for every target market from skills/context-engine/compliance-rules.md. Check for guidelines at ~/.claude-marketing/brands/{slug}/guidelines/_manifest.json — if present, load voice-and-tone rules, messaging hierarchy, channel style guides, and any market-specific brand guidelines. Check for custom templates at ~/.claude-marketing/brands/{slug}/templates/ — localized templates may already exist for some markets. Check for agency SOPs at ~/.claude-marketing/sops/. If no brand exists, ask: "Set up a brand first (/dm:brand-setup)?" — or proceed with defaults.
  2. Inventory all campaign assets: Enumerate every asset from the provided sources. Categorize each by type (email, ad, social post, landing page, video script, push notification, SMS, blog post). For each asset, analyze the content to classify it as:

- Factual/informational: Product descriptions, specifications, terms, pricing — suitable for direct translation - Emotional/creative: Headlines, CTAs, slogans, hero copy, storytelling — requires transcreation - Compliance-sensitive: Disclaimers, consent language, legal text, privacy notices — requires market-specific adaptation - SEO-dependent: Landing pages, blog posts, meta content — requires localized keyword research Report the full inventory to the user: total asset count, breakdown by type, breakdown by content classification, and estimated processing scope per market.

  1. For each target market, execute the following localization pipeline: a. Route translation service: Run python scripts/language-router.py --action route --source "{source_lang}" --target "{market_lang}" to select the optimal translation service for this language pair. Log the selected service. b. Translate factual content: Process all factual/informational assets through the routed translation service via the appropriate MCP server (deepl, sarvam-ai, google-cloud-translation, or lara-translate). Pass do-not-translate terms, glossary entries, formality settings, and formatting preservation flags. Score each translation via python scripts/language-router.py --action score. c. Transcreate emotional content: For all emotional/creative assets, apply the transcreation methodology from skills/context-engine/transcreation-framework.md. Produce 2-3 creative adaptation options per piece, each with:

- The adapted content in the target language - Back-translation for review - Intent-preservation score - Cultural fit assessment for this specific market - Tone alignment with the original Mark the recommended option but preserve all alternatives for client review. d. Adapt cultural elements: Reference the cultural dimension mapping in skills/context-engine/multilingual-execution-guide.md (Hofstede framework) to adapt: - Social proof style: Testimonials (individualist markets) vs. community endorsements (collectivist markets) vs. authority citations (high power-distance markets) - Urgency tactics: Direct scarcity (Western markets) vs. relationship-based urgency (Asian markets) vs. group-benefit urgency (collectivist markets) - Trust signals: Certifications and data (Germanic markets) vs. relationship and reputation (Asian markets) vs. authority endorsement (Middle Eastern markets) - Visual/imagery recommendations: Color associations, gesture meanings, modesty considerations, seasonal references per market - Humor and tone: Adjust or remove humor that does not translate culturally; adapt tone to match market expectations for formality e. Localize compliance: For each market, add or modify: - Market-specific disclaimers and legal notices - Data consent and privacy language per regional regulation (GDPR for EU, DPDPA for India, PIPA for Japan, LGPD for Brazil, etc.) - Industry-specific regulatory statements - Required disclosures (pricing, advertising standards, influencer disclosure) - User-provided market-specific compliance requirements Reference skills/context-engine/compliance-rules.md for the regulatory framework per market. f. Localize SEO (for landing pages, blog posts, and web content): Provide localized keyword suggestions based on the original keyword targets, generate hreflang tag specifications for multi-language site setup, create localized meta titles and meta descriptions, and adapt URL slug recommendations for the target language. g. Adjust formatting: Apply locale-specific formatting: - RTL text direction for Arabic (ar), Hebrew (he), Urdu (ur), Persian (fa) — flag any layout elements that need RTL adaptation - Date formats per locale (DD/MM/YYYY vs. MM/DD/YYYY vs. YYYY-MM-DD) - Number formatting (decimal separators, thousands separators) - Currency symbols and positioning - Measurement units (metric vs. imperial) - Phone number formats with country codes - Address format conventions

  1. Score each localized asset: Run python scripts/language-router.py --action score on every translated/transcreated asset to assess translation quality (length ratio, formatting preservation, key term consistency, placeholder integrity, completeness).
  2. Evaluate localized content quality: Run python scripts/eval-runner.py --brand {slug} --action run-quick --text "{localized_content}" --content-type "{type}" on each localized asset to assess overall content quality in the target language. This catches issues beyond translation accuracy — readability, persuasion, brand alignment in the target language.
  3. Run brand voice check: Execute python scripts/brand-voice-scorer.py --brand {slug} --text "{localized_content}" on key assets (headlines, hero copy, email subject lines) to verify brand voice preservation across languages.
  4. Create per-market delivery package: For each target market, assemble:

- All localized assets organized by type - Translation quality scores per asset - Content quality scores per asset - Transcreation options for emotional content (with recommended option marked) - Cultural adaptation notes explaining what was changed and why - Compliance additions with regulatory references - SEO recommendations (keywords, hreflang, meta content) - Formatting notes (RTL flags, date/number/currency formats applied) - Deployment checklist specific to this market

  1. Generate cross-market consistency report: Verify that core brand messaging, campaign themes, and value propositions remain consistent across all localized versions. Flag any market where the localized messaging diverges significantly from the campaign strategy. Check that do-not-translate terms are consistently preserved across all markets. Verify that visual/imagery recommendations are consistent where appropriate and diverge where culturally necessary.
  2. Produce localization summary: Compile the full overview — all markets, all assets, all scores, all flags — into a single summary document with a quality scoreboard (markets as rows, assets as columns, scores in cells) and an overall campaign localization health score.

Output

A comprehensive campaign localization package containing:

  • Per-market asset package: For each target market:

- All localized content organized by asset type (email, ad, social, landing page, etc.) - Translation quality score per asset with dimension breakdown - Content quality score per asset (eval-runner assessment) - Brand voice score for key assets

  • Transcreation options: For all emotional/creative content across all markets — 2-3 options per piece with back-translations, intent-preservation scores, cultural fit notes, and recommended option marked
  • Cultural adaptation notes: Per-market summary of what was adapted and why — social proof style, urgency tactics, trust signals, humor adjustments, imagery recommendations, with Hofstede dimension references
  • Compliance additions per market: Every disclaimer, consent statement, regulatory notice, and required disclosure added for each market, with regulatory references (GDPR Article X, DPDPA Section Y, etc.)
  • Localized SEO recommendations: Per-market keyword suggestions, hreflang tag specifications, localized meta titles and descriptions, URL slug recommendations
  • RTL and formatting notes: For applicable markets — RTL layout flags, date/number/currency format specifications, measurement unit conversions, address and phone format conventions
  • Cross-market consistency report: Verification that brand messaging, campaign themes, and value propositions are coherent across all markets, with flags for significant divergences
  • Quality scoreboard: Matrix of all markets (rows) by all assets (columns) with translation quality scores, content quality scores, and overall grades — provides an at-a-glance view of campaign localization health
  • Deployment checklist per market: Market-specific steps for publishing — platform settings, language targeting, geo-targeting, compliance approvals needed, QA review points, go-live sequence
  • Campaign localization health score: Single aggregate score reflecting overall localization quality, consistency, and completeness across all markets
  • Recommendations: Priority items for human review (low-scoring assets, culturally sensitive transcreation decisions, compliance items requiring legal sign-off), process improvements for future localization runs, and terms to add to the brand glossary

Agents Used

  • localization-specialist -- Manages the end-to-end localization pipeline including translation service routing, transcreation execution, cultural adaptation using Hofstede dimensions, compliance localization, quality scoring, cross-market consistency verification, and per-market package assembly
  • content-creator -- Generates transcreation options for emotional and creative content, produces culturally adapted headlines and CTAs, creates localized meta descriptions and SEO copy, and ensures marketing effectiveness is preserved across languages
  • execution-coordinator -- Coordinates the multi-market publishing workflow, manages deployment checklists, sequences go-live across markets and channels, tracks approval status per market, and ensures all compliance sign-offs are obtained before publishing

平台分布

Codex

38.8%
按下载量换算77

Claude

28.26%
按下载量换算56

Cursor

17.49%
按下载量换算35

Gemini CLI

9.34%
按下载量换算18

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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