/ad-library-teardown

name: ad-library-teardown
description: Use when the user wants to analyze active ads from Meta/Facebook, Google, or LinkedIn ad libraries; tear down a competitor's messaging; extract hooks, offers, CTAs, video transcripts, landing page claims, and test ideas from public ads.
allowed-tools: Bash, Read, Write, WebFetch

version: 1.0.0
author: ScrapeCreators
license: MIT
homepage: https://scrapecreators.com
repository: https://github.com/ScrapeCreators/social-media-research-skills
metadata:
  openclaw:
    requires:
      env:
        - SCRAPECREATORS_API_KEY
    primaryEnv: SCRAPECREATORS_API_KEY
    homepage: https://scrapecreators.com
    tags:
      - social-media
      - research
      - scrapecreators

Ad Library Teardown

Overview

Analyze public ads to understand a competitor's messaging, offers, creative strategy, and testing angles. The output should be a practical teardown marketers can use to write better ads or decide what to test.

When to Use

Use this skill when the user asks to:

• analyze a competitor's active ads
• search Meta/Facebook, Google, or LinkedIn ad libraries
• extract ad hooks, CTAs, claims, offers, and landing page angles
• compare ad messaging across competitors
• summarize video ad transcripts
• generate ad test ideas from competitor ads

Data Sources

| Ad library | Search/list endpoint | Detail endpoint | Transcript endpoint | |---|---|---|---| | Meta/Facebook | `/v1/facebook/adLibrary/search/ads`, `/v1/facebook/adLibrary/company/ads`, `/v1/facebook/adLibrary/search/companies` | `/v1/facebook/adLibrary/ad` | `/v1/facebook/adLibrary/ad/transcript` | | Google | `/v1/google/adLibrary/advertisers/search`, `/v1/google/company/ads` | `/v1/google/ad` | n/a | | LinkedIn | `/v1/linkedin/ads/search` | `/v1/linkedin/ad` | n/a |

Workflow

1. **Find the advertiser**

• Use company search endpoints when the user provides only a brand name.
• Use domain/advertiser/page IDs when available.

2. **Fetch active ads**

• Prefer active ads unless the user asks for historical analysis.
• Capture platform, advertiser/page, ad ID, start date, creative type, text, headline, CTA, destination URL, and source URL.

3. **Fetch details for representative ads**

• Enrich the ads with detail endpoints.
• For video Meta ads, fetch transcripts when available.

4. **Cluster messaging** Group ads by:

• pain point
• persona
• offer
• proof/social proof
• feature/benefit
• objection handled
• comparison/alternative angle
• urgency/discount

5. **Extract swipeable elements**

• hooks
• headlines
• primary text patterns
• CTAs
• claims
• offers
• visual/creative concepts

6. **Recommend tests** Suggest tests based on repeated patterns and gaps, not random ideas.

Output Format

# Ad Library Teardown: {brand}

## Summary
- Ads analyzed: {count}
- Platforms: Meta / Google / LinkedIn
- Main positioning:
- Strongest repeated offer:

## Messaging Angles
| Angle | Evidence | Example ads | Notes |
|---|---|---|---|

## Hooks and Headlines Swipe File
- "..."
- "..."

## Offers and CTAs
| Offer | CTA | Platform | Example |
|---|---|---|---|

## Video Transcript Notes
- [Ad](url): summary, hook, best quote

## What They Appear to Be Testing
1. ...
2. ...

## Recommended Tests for Us
1. ...
2. ...
3. ...

## Sources
- [Ad](url)

Common Pitfalls

• Do not claim an ad is winning just because it is active. Say it is active or repeated; performance is not public unless the endpoint returns it.
• Do not ignore repeated ads. Repetition is often a useful signal.
• Do not invent spend, conversion rate, or targeting unless public data includes it.
• Do not skip video transcripts when the user asks for hooks or messaging from video ads.