什么是 Meta 广告分析助手？

Meta 广告分析助手是 Openclaw Skills 库中一款先进的实用工具，旨在提供对社交媒体广告策略的深度洞察。通过处理提取的图像、视频和落地页截图，它能还原广告主的意图，识别驱动转化的核心情感触发点和技术规范。

该技能是效能营销人员和代理商负责人的情报层。它不仅是列出广告，还将数据合成为一份完整的 HTML 策略文档，包含内联媒体和漏斗映射，使向利益相关者传达复杂的竞争情报变得更加容易。

下载入口:https://github.com/openclaw/skills/tree/main/skills/bluerockerr/meta-ads-analyser

安装与下载

1. ClawHub CLI

从源直接安装技能的最快方式。

2. 手动安装

将技能文件夹复制到以下位置之一

优先级：工作区 > 本地 > 内置

3. 提示词安装

将此提示词复制到 OpenClaw 即可自动安装。

Meta 广告分析助手 应用场景

• 竞品研究：对竞品广告库进行深度审计，反向工程其创意策略。
• 客户报告：在广告提取阶段完成后，为客户生成专业级的分析报告。
• 创意审计：识别当前广告组中的缺失，如缺失的纵横比（Reels 的 9:16）或薄弱的钩子。
• 漏斗映射：可视化从特定广告创意到其对应落地页的转化路径，以了解顶层（TOFU）和底层（BOFU）漏斗意图。

1. 扫描本地输出目录，查找由 meta_ads_extractor 工具生成的资产。
2. 采用视觉模型和 Gemini 分析，拆解每个视频和图像的脚本、钩子和纵横比。
3. 审计落地页截图，识别标题、转化流程和核心价值主张。
4. 根据目标 URL 将相关的广告和落地页归类为逻辑营销漏斗。
5. 检测策略模式，如价格锚点、信誉堆叠和原生创意风格。
6. 将所有洞察汇编成一份自包含的、响应式移动端的 HTML 报告，并带有可播放的内联媒体。
7. 将整个分析打包成便携式 zip 文件，以便通过 T@elegrimm 等渠道交付。

Meta 广告分析助手 配置指南

要使用此技能，请确保您拥有用于媒体元数据提取的必要 CLI 工具。对于 macOS 用户，sips 是内置的，但视频分析需要 ffprobe。

# 安装 ffmpeg 以获取用于视频元数据的 ffprobe
brew install ffmpeg

# 在提取广告后运行分析助手
/meta_ads_analyser

该技能无缝集成到 Openclaw Skills 工作流中，通常紧随 /meta_ads_extractor 命令之后。

Meta 广告分析助手 数据架构与分类体系

该技能在特定广告主的目录中将分析组织成结构化格式。数据组织如下：

name: meta-ads-analyser
description: Analyze extracted Meta ad creatives and generate a professional strategy report. Use after /meta_ads_extractor to produce a clean, organized analysis document with inline videos/images grouped by funnel/landing page.

Meta Ads Analyser

Generate a professional ad strategy analysis report from extracted Meta ad creatives.

Prerequisites

• Extracted ad assets from /meta_ads_extractor (images, videos, landing page screenshots)
• Ad creative analysis (hooks, scripts, emotions, CTAs, strengths/weaknesses)
• Landing page analysis (headlines, strategies, conversion flows)

Input

Assets folder from extraction, typically at:

~/clawd/output/meta-ads/{advertiser-slug}/
├── {slug}-video-01.mp4
├── {slug}-video-02.mp4
├── {slug}-image-01.jpg
├── {slug}-image-02.jpg
├── landing-{page-name}.jpg
└── ...

Analysis Process

1. Analyze Each Creative

For each ad creative, identify:

• Aspect Ratio — Dimensions and ratio (1:1, 4:5, 9:16, 16:9)
• Duration — For videos, length in seconds
• Hook — Opening line/visual that stops the scroll
• Script/Copy — Key messaging and value proposition
• Visual Flow — Sequence of scenes/elements (for video)
• Emotion — Primary emotional trigger (curiosity, fear, aspiration, etc.)
• CTA — Call to action and friction level
• Strengths — What works well
• Weaknesses/Gaps — What could be improved

Use vision model for images, Gemini for video analysis.

Get dimensions with:

# Images (macOS)
sips -g pixelWidth -g pixelHeight image.jpg

# Videos
ffprobe -v error -select_streams v:0 -show_entries stream=width,height -of csv=p=0 video.mp4

Common aspect ratios:

2. Analyze Landing Pages

For each landing page, identify:

• Headline — Primary value proposition
• Strategy — Key conversion elements (social proof, urgency, etc.)
• Conversion Flow — Path from landing to purchase/signup
• Strengths — What converts well
• Gaps — Missing elements or friction points

3. Map Funnels

Group ads by their destination landing page. Each funnel = landing page + all ads driving to it.

Typical funnel types:

• TOFU (Top of Funnel) — Awareness, lead magnets, quizzes, free content
• BOFU (Bottom of Funnel) — Direct offer, application, purchase

4. Identify Strategy Patterns

Look for:

• Credibility stacking (logos, credentials, social proof)
• Price anchoring
• Native creative (ads that don't look like ads)
• Identity-driven copy
• Testing patterns (variants of same creative)

Output Format

Generate a self-contained HTML report using the template structure below.

Report Structure

1. Header
   - Advertiser name
   - Stats (# ads, # funnels, date)

2. Strategy Overview (TOP)
   - High-level acquisition strategy
   - Funnel flow visualization
   - Creative testing patterns
   - Key takeaways (actionable insights)

3. Funnel Sections (one per landing page)
   - Funnel header (name, URL)
   - Landing page card (screenshot + analysis)
   - Ad cards grid (media + analysis for each)
   
4. Footer
   - Source attribution
   - Date generated

Styling Guidelines

• Clean, doc-like design — white background, simple typography
• No dark gradients or heavy styling — should feel like a PDF/Notion doc
• Inline media — videos and images embedded and playable
• Mobile-friendly — responsive grid for ad cards
• Badges for quick scanning — TOFU/BOFU, Video/Image, Variant, Top performer, Aspect ratio (1:1, 4:5, 9:16)

Ad Card Format

Each ad card should display:

[Media: video/image]
[Badges: Type | Funnel Stage | Aspect Ratio | Duration (if video)]
[Title]
[Analysis fields: Hook, Script, Emotion, Strengths, Gaps]

Include aspect ratio badge on every ad card so patterns are visible at a glance (e.g., "all TOFU ads are 4:5, BOFU ads are 1:1").

See templates/report-template.html for the full HTML/CSS template.

Delivery

1. Generate HTML file in the assets folder:

   ~/clawd/output/meta-ads/{advertiser-slug}/{slug}-analysis.html
   

2. Zip the entire folder (HTML + all media assets)

3. Send via T@elegrimm with caption explaining contents

Important: The HTML uses relative paths to media files. Always deliver as a zip so the recipient can open it locally with all assets.

Example Workflow

User: Analyze the EricPartaker ads we extracted

1. Read assets folder: ~/clawd/output/meta-ads/ericpartaker/
2. Analyze each video with Gemini / image with vision
3. Analyze landing page screenshots
4. Map ads to landing pages (identify 3 funnels)
5. Identify strategy patterns
6. Generate HTML report
7. Zip folder
8. Send to user

Integration

This skill is designed to follow /meta_ads_extractor:

/meta_ads_extractor → downloads assets
/meta_ads_analyser → generates strategy report

Can also integrate with:

• ad-creative-analysis — detailed individual ad breakdowns
• landing-page-analysis — deeper landing page audits