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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.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install bluerockerr/meta-ads-analyserInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Generate a professional ad strategy analysis report from extracted Meta ad creatives.
/meta_ads_extractor (images, videos, landing page screenshots)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
└── ...
For each ad creative, identify:
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:
| Ratio | Use Case |
|---|---|
| 1:1 | Feed (universal) |
| 4:5 | Feed (recommended) |
| 9:16 | Stories/Reels |
| 16:9 | Landscape video |
For each landing page, identify:
Group ads by their destination landing page....
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# 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:**
```bash
# 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:**
| Ratio | Use Case |
|-------|----------|
| 1:1 | Feed (universal) |
| 4:5 | Feed (recommended) |
| 9:16 | Stories/Reels |
| 16:9 | Landscape video |
### 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....University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
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