Search

PythonReactSEOPDF
OpenClaw

meta-ads-analyser

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.

bluerockerr0 source installs☆ 0 Repository stars

Installation

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-analyser

Inspect 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.

View source ↗Guides

Skill instructions

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:

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....

Source information

Source
github
Repository
openclaw/skills
Path
skills/bluerockerr/meta-ads-analyser
Version
—
Commit
685f85adf005a24ff456de6f1e51fbfc1fd21047
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# 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....

Related skills

OpenClaw

dojo.md

edholofy

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...

OpenClaw

geo-optimization

capt-marbles

Generative Engine Optimization (GEO) for AI search visibility. Optimize content to appear in ChatGPT, Perplexity, Claude, and Google AI Overviews. Use when optimizing websites, pages, or content for LLM discove...

OpenClaw

wps-macos-helper

lethehades

macOS WPS Office workflow helper skill for safer document preparation, conversion, export, and compatibility guidance