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营销活动策划

端到端的营销活动策划与执行。涵盖受众调研、定位、活动角度定义、着陆页文案、邮件序列、社交媒体帖子、广告文案、短视频脚本和内容日历。用于多渠道产品发布的编排层。

营销活动策划 是什么?

该技能为AI代理提供了一套完整的营销活动策划与执行框架,从调研、定位到内容制作和审查,覆盖了整个活动周期。它通过定义清晰的阶段(调研、定位、内容制作、审查)和可交付成果,确保活动具有策略性和可执行性。该技能适用于任何需要策划和发布产品、功能或品牌活动的场景,支持着陆页、邮件、社交媒体、视频和广告等多种内容类型的生成。其核心价值在于强制要求先定位后创作、基于受众洞察驱动内容、并通过严格的质量门控确保所有渠道的文案一致且有效,避免空洞的营销话术。通过集成其他技能(如市场调研、品牌声音),它可以作为一个编排层来协调复杂的多渠道发布。

兼容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/ECC/tree/main/skills/marketing-campaign

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

营销活动策划 是做什么的?

策划并执行能够带来转化的发布活动——而不只是草草上线的活动。

何时激活

  • 规划产品或功能发布时
  • 从单一产品简报构建完整内容套件时
  • 在撰写任何文案前确定定位和活动角度时
  • 跨渠道编排多种内容类型时
  • 审查文案的转化质量和品牌一致性时

不可妥协的准则

  1. 在撰写任何文案前必须先确定定位。所有文案均需从角度出发。
  2. 在假设了解受众的语言或担忧之前,必须先进行受众调研。
  3. 每个可交付成果都必须在活动弧线中服务于一个明确的目标。
  4. 具体性在任何格式和任何渠道上都优于形容词。
  5. 相同的语气必须贯穿所有渠道和每篇内容。
  6. 未经质量门核查的文案不得发布。

活动工作流程

第一阶段:调研

使用 market-research 进行:

  • 勾勒目标受众画像(待完成的工作、担忧、语言、他们使用的替代方案)
  • 映射3个以上直接或相邻的竞争对手(定位、差距、信息传递弱点)
  • 确定1-3个活动角度将利用的受众洞察

可交付成果:一份简短的研究简报(受众画像 + 竞争对手总结 + 关键洞察)。

第二阶段:定位

产出:

  • 核心利益陈述(一句话,无功能列表,无行话)
  • 定位公式:「[产品]帮助[受众]通过[机制]实现[结果]」
  • 活动角度:整个活动所依托的具体张力、洞察或时刻
  • 语气档案:在开始写作前锁定(委托给 brand-voice 进行持久、可跨会话重复使用的语气捕获)

在定位和角度获得批准之前,不得撰写任何文案。

第三阶段:内容制作

按此顺序制作——每一层为下一层提供信息:

  1. 着陆页文案(所有部分:英雄区、问题、解决方案、功能、工作原理、证明、行动号召)
  2. 邮件序列(每封邮件有一个目的;遵循弧线:问题 → 教育 → 刺激 → 解决方案 → 证明 → 紧迫感 → 最终行动号召)
  3. 社交媒体帖子(通过 content-engine 实现平台原生;LinkedIn 和 X 是不同格式,而非简单调整大小的相同文案)
  4. 短视频脚本(按时间戳分块;为屏幕和耳朵而写,而非为页面)
  5. 广告文案变体(3-4个变体,测试不同角度或受众细分)
  6. 内容日历(逐日排期,包含渠道、类型、时间和依赖关系)

第四阶段:审查

对每个可交付成果进行门控:

  • 对所有英雄区 / 首屏文案进行5秒测试(明确目标受众、产品功能、立即行动原因)
  • 行动号召审计(每个内容一个,具体、有依据——而非强求)
  • 跨渠道语气一致性检查
  • 声明审计(每项声明具体且可支持)
  • 跨渠道一致性(广告声明与着陆页匹配;邮件正文与主题匹配)

输出合约

一次完整的活动应交付:

  1. 定位简报——角度、核心利益陈述、语气档案
  2. 着陆页文案——英雄区、问题、解决方案、功能、工作原理、证明、行动号召
  3. 邮件序列——每封邮件的主题 + 预览 + 正文 + 行动号召,按天和目的标记
  4. LinkedIn 帖子——3篇以上平台原生帖子,具有不同角度
  5. X 帖子——5篇以上独立帖子 + 1条话题串
  6. 短视频脚本——2个以上按时间戳分块的脚本,附视觉指导说明
  7. 广告文案变体——每个变体的短标题 / 长标题 / 正文
  8. 内容日历——逐日排期,包含渠道、内容类型、时间和依赖关系
  9. 文案审查总结——在内容上线前标记的问题和未决问题

质量门控

在交付任何内容之前:

  • 每份可交付成果听起来像出自同一作者
  • 无空洞的夸大之词或填充形容词
  • 每项行动号召具体且有依据(绝不用「了解更多」或「点击此处」)
  • 无跨平台逐字重复的文案
  • 英雄区文案通过5秒测试
  • 邮件主题与邮件正文匹配(无标题党)
  • 广告声明与着陆页声明完全一致
  • 无文案在其他同类产品中无需改动即可使用

严格禁止

删除并重写任何包含以下内容的文案:

  • 「颠覆性」「革命性」「世界级」「尖端」
  • 「在当今竞争激烈的环境中」
  • 没有真实截止日期支撑的虚假紧迫感
  • 无具体内容的虚假社会证明(「成千上万的用户信任我们」)
  • 通用行动号召(「了解更多」「查看更多」「点击此处」)
  • 可被直接拔插到竞争对手活动中且无需改动的文案

相关技能

  • brand-voice —— 源自素材的语气捕获(在内容制作前运行)
  • content-engine —— 平台原生内容制作
  • crosspost —— 多平台分发
  • market-research —— 受众与竞争情报
  • seo —— 着陆页文案的页面内优化

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/ECC

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-first-engineering

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

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