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Agent Skill · 研究检索

retargeting-strategy(重定向策略)

retargeting-strategy 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。

retargeting-strategy 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,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 49,373。

总安装 654周安装 27GitHub Stars 66下载 214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:retargeting-strategy(重定向策略)
来源仓库:https://github.com/indranilbanerjee/digital-marketing-pro
仓库路径:skills/retargeting-strategy
安装命令:
npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill retargeting-strategy
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 retargeting-strategy

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。

用于查找、检索和筛选相关信息,支持基于关键词或任务场景快速定位结果。适用于需要从多来源线索中提取有效信息的场景。通过 npx skills add 命令从指定 GitHub 仓库安装使用。建议确认权限范围和维护状态,避免触发联网或文件读写操作。

retargeting-strategy 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/retargeting-strategy

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

retargeting-strategy 怎么安装?

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

retargeting-strategy 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。

retargeting-strategy 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。

retargeting-strategy 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。

retargeting-strategy 用的人多吗?

公开数据是累计安装 654 次,近一周安装 27 次,下载 214 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。

retargeting-strategy 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。
  • 需要处理研究检索类任务、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。

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
retargeting-strategy

重定向策略 · 本页

65466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

/dm:retargeting-strategy

Purpose

Design a cross-platform retargeting strategy with audience segmentation by funnel stage and behavior, creative sequencing, frequency management, and budget allocation. Produces a complete retargeting playbook ready for implementation across advertising platforms.

Input Required

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

  • Website traffic volume: Monthly unique visitors and page views (approximate is fine)
  • Conversion funnel stages: The key stages in the user journey (visit, product view, add to cart, checkout, purchase -- or equivalent for lead gen funnels)
  • Platforms in use: Which advertising platforms are active or available (Google Ads, Meta, LinkedIn, TikTok, programmatic DSPs, etc.)
  • Retargeting budget: Monthly budget allocated or available for retargeting campaigns
  • Product catalog: For dynamic retargeting -- whether a product feed exists and on which platforms it is configured
  • Average purchase cycle: Typical time from first visit to conversion (days, weeks, months)
  • Current retargeting setup: Any existing retargeting campaigns, pixel/tag status, audience definitions already in place, and current performance
  • Pixel and tracking status: Which pixels/tags are installed and firing correctly (Meta Pixel, Google Tag, LinkedIn Insight Tag, TikTok Pixel, etc.)

Process

  1. Load brand context: Read ~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Apply voice, compliance, industry context. Check guidelines/_manifest.json for restrictions, messaging, channel styles, voice-and-tone rules, and templates. If a template matching this command exists in ~/.claude-marketing/brands/{slug}/templates/, apply its format. If no brand exists, prompt for /dm:brand-setup or proceed with defaults.
  2. Check campaign history: Run python campaign-tracker.py --brand {slug} --action list-campaigns to review existing retargeting campaign performance and identify what has already been tested.
  3. Audit tracking infrastructure: Verify pixel and tag installation status across platforms. Identify gaps in tracking that would prevent audience building or conversion attribution before designing the strategy.
  4. Define retargeting audience segments: Create segments based on funnel stage (awareness visitors, product viewers, cart abandoners, past purchasers, lapsed customers), behavior signals (pages visited, time on site, visit frequency, content consumed), and recency windows (1-3 days, 4-7 days, 8-14 days, 15-30 days, 31-90 days). Size each segment based on traffic volume.
  5. Design creative sequence per segment: Map a messaging sequence for each audience segment that progresses the user toward conversion -- awareness segments get educational and value-prop messaging, consideration segments get social proof and differentiation, cart abandoners get urgency and incentive, past purchasers get upsell and cross-sell, and lapsed customers get re-engagement offers.
  6. Set frequency caps per platform: Define impression frequency limits per user per day and per week for each platform. Balance visibility against ad fatigue -- typically 3-5 impressions per day for display, 1-2 per day for social feed placements, and 15-20 per week maximum across all placements combined.
  7. Plan cross-platform coordination: Orchestrate retargeting across platforms so users see a coherent journey rather than redundant messages. Assign primary and secondary roles per platform (e.g., Meta for awareness retargeting, Google Display for mid-funnel, search remarketing for high-intent, LinkedIn for B2B decision-makers).
  8. Design exclusion lists: Define converter exclusion windows (exclude purchasers for 7-30 days post-conversion), cross-segment exclusions (prevent users from seeing both awareness and cart abandonment ads simultaneously), and negative audience rules to prevent waste and brand fatigue.
  9. Set budget allocation per segment: Distribute the retargeting budget across segments based on audience size, proximity to conversion, and expected ROAS. Bottom-funnel segments (cart abandoners) typically receive the highest per-user spend despite smaller audience sizes.
  10. Configure dynamic retargeting: If a product catalog is available, specify dynamic ad setup -- feed requirements, template design, product recommendation logic (viewed items, complementary products, best sellers), and fallback creatives for users without product-level data.
  11. Define KPIs and optimization triggers: Set success metrics per segment and platform (ROAS, CPA, view-through conversions, frequency, CTR). Define optimization triggers -- when to refresh creative, adjust bids, reallocate budget, or expand/contract audience windows.
  12. Create UTM structure for tracking: Build a UTM naming convention that enables granular tracking of retargeting performance by segment, platform, creative variant, and funnel stage in analytics.

Output

A structured retargeting strategy document containing:

  • Audience segment definitions with sizing estimates, recency windows, and behavioral criteria
  • Creative brief per segment with messaging themes, ad formats, and sequencing logic
  • Frequency cap recommendations per platform with rationale for each limit
  • Cross-platform coordination plan showing which platform serves which funnel role
  • Exclusion list definitions with converter suppression windows and cross-segment rules
  • Budget allocation table by segment and platform with expected ROAS targets
  • Dynamic retargeting setup guide with feed requirements and product recommendation logic
  • KPI framework with targets per segment, optimization triggers, and review cadence
  • UTM structure and naming conventions for retargeting campaign tracking
  • 30/60/90-day optimization roadmap with milestone checkpoints and scaling criteria
  • Privacy and compliance considerations (cookie consent, GDPR/CCPA audience restrictions, platform-specific privacy limitations)
  • Tracking infrastructure checklist with pixel/tag verification requirements per platform

Agents Used

  • media-buyer -- Audience segmentation, platform-specific retargeting setup, frequency management, budget allocation, bid strategy, dynamic retargeting configuration, and campaign structure design
  • marketing-strategist -- Creative sequencing strategy, cross-platform coordination, funnel-stage messaging architecture, and optimization roadmap planning

平台分布

Codex

32.89%
按下载量换算70

Claude

30.8%
按下载量换算66

Cursor

17.14%
按下载量换算37

Gemini CLI

10.17%
按下载量换算22

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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