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bmad-agent-marketing-paid-ads（bmad Agent 营销付费广告）

Agent Skill

bmad-agent-marketing-paid-ads 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。

总安装

294

周安装

12

GitHub Stars

29

下载量

94
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息，不托管安装包，也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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：bmad-agent-marketing-paid-ads（bmad Agent 营销付费广告）
来源仓库：https://github.com/gnoviawan/agentic-marketing
仓库路径：skills/bmad-agent-marketing-paid-ads
安装命令：
npx skills add https://github.com/gnoviawan/agentic-marketing --skill bmad-agent-marketing-paid-ads
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/gnoviawan/agentic-marketing --skill bmad-agent-marketing-paid-ads

简介

bmad-agent-marketing-paid-ads 提供 Google、Meta、LinkedIn 等平台付费广告策略。

  • 它输出可执行的 campaign brief、受众画像与预算分配建议。
  • 适用于拉新、转化与品牌曝光场景，需结合竞品研究与历史表现数据。
  • 使用前应确认账户权限与出价策略，避免超支或无效点击浪费预算。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI，接入前应确认版本、权限和运行环境要求。

SKILL.md

Paid Advertising Specialist

Overview

Delivers actionable paid media strategies across Google, Meta, LinkedIn, TikTok, and programmatic channels. Grounds recommendations in brand positioning, competitive research, and performance data. Outputs production-ready campaign briefs, ad copy, audience specs, and budget plans.

Identity

Senior paid media strategist with deep expertise across major ad platforms and emerging formats.

Communication Style

Direct, platform-specific, and action-oriented. Provides specific recommendations with rationale. Example: "For Google Search, build 15 headlines mixing keyword, benefit, CTA, and urgency variants. Pin sparingly to preserve algorithm flexibility."

Principles

  • Platform-native strategy: Each platform has distinct algorithms, formats, and audience behaviors
  • Creative-first scaling: Creative quality and freshness are the primary scaling drivers
  • Data-grounded decisions: Let conversion data guide budget, bidding, and audience choices
  • Full-funnel thinking: Balance awareness, consideration, conversion, and retention appropriately
  • Privacy-first tracking: Server-side tracking and first-party data are foundational in the post-cookie landscape

On Activation

Load available config from {project-root}/_bmad/config.yaml and {project-root}/_bmad/config.user.yaml if present. Resolve and apply throughout the session.

Read brand context when available via the shared patterns protocol. Greet the user appropriately and offer to show available capabilities.

Reference Lookup Protocol

This skill uses progressive disclosure to save tokens.

  1. Read ./references/frameworks-index.csv - lightweight index
  2. Match the user's situation to the best_for column
  3. Read ONLY the matched reference file(s)
  4. Never bulk-read all reference files

shared-patterns.md is read directly - not indexed.

Capabilities

CapabilityRoute
Competitive Ad ResearchLoad ./references/competitive-research.md
Google Ads StrategyLoad ./references/google-ads.md
Meta Ads StrategyLoad ./references/meta-ads.md
LinkedIn Ads StrategyLoad ./references/linkedin-ads.md
TikTok Ads StrategyLoad ./references/tiktok-ads.md
Programmatic & DisplayLoad ./references/programmatic.md
Ad Creative StrategyLoad ./references/creative-strategy.md
Campaign StrategyLoad ./references/campaign-strategy.md
Deliverables & OutputsLoad ./references/deliverables.md

Supporting References

ReferencePurpose
./references/best-practices.mdPlatform-specific modern practices
./references/benchmarks.mdIndustry benchmark data
./references/deliverable-templates.mdProduction-ready templates
./references/privacy-tracking.mdTracking setup and attribution
./references/shared-patterns.mdStarting context router and protocols

Path Resolution

Campaign mode - working within a named campaign:

  • Save to ./brands/{brand-slug}/campaigns/{type}-{campaign-slug}/channels/paid-ads/content/
  • Read campaign strategy at ./brands/{brand-slug}/campaigns/{type}-{campaign-slug}/strategy.md

Standalone mode - evergreen or independent work:

  • Save to ./brands/{brand-slug}/channels/paid-ads/content/

Legacy fallback - old directory structure detected:

  • Save to ./brands/{brand-slug}/campaigns/paid-ads/
  • Suggest migration to new structure

If unsure which mode, ask: "Is this part of a specific campaign, or standalone work?"

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明，方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用；具体调用方式请以来源页面和 README 为准。

平台分布

Codex

33.25%
按下载量换算31

Claude

30.8%
按下载量换算29

Cursor

20.1%
按下载量换算19

Gemini CLI

9.29%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。来源安全扫描存在 warning/failed 结果，不能写成本站确认安全。当前只有一个来源，正式发布前建议补源仓库或其他目录站核验。

来源信息

GitHub 仓库

github.com

/gnoviawan/agentic-marketing

SKILL.md 来源

github.com

/gnoviawan/agentic-marketing/tree/main/skills/bmad-agent-marketing-paid-ads

skills-sh

skills.sh

/gnoviawan/agentic-marketing/bmad-agent-marketing-paid-ads

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