An automated tool to scan the Meta Ad Library and extract real-time advertising intelligence for any brand or domain.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install meta-ads-collector-adarsh
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install meta-ads-collector-adarsh using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Meta Ads Collector Skill?
The Meta Ads Collector Skill is a specialized data gathering tool designed to interface directly with the Meta Ad Library API. It enables AI agents to programmatically retrieve insights into a brand's current advertising presence across Facebook, Instagram, and Messenger. By integrating this into your Openclaw Skills library, you can automate the discovery of active campaigns, creative formats, and historical ad performance.
This skill is a foundational component for building comprehensive marketing audit pipelines or competitive analysis agents. It focuses on transforming raw API responses into structured metrics like total active ads, creative diversity, and campaign longevity. Using Openclaw Skills like this ensures your AI workflows have access to verified, real-world marketing data without manual searching.
Meta Ads Collector Skill Use Cases
- Competitor Benchmarking: Compare the volume and duration of active Meta ads across multiple industry rivals.
- Marketing Audit Pipelines: Automatically populate the Paid Ads Strategy section of a brand audit report.
- Creative Trend Analysis: Identify whether a brand is prioritizing video, carousel, or static image formats in their current strategy.
- Longevity Tracking: Find the longest-running ads to identify high-performing evergreen creative assets.
How Meta Ads Collector Skill Works
- The skill receives a brand name and optional domain as input triggers from the agent.
- It authenticates with the Meta Graph API using the provided access tokens and environment variables.
- A search query is executed against the Meta Ad Library, filtering strictly for currently active advertisements.
- If a domain is provided, the skill filters the results to ensure high relevance and accuracy for the specific brand.
- The system calculates key metrics including the total ad count and the number of days the oldest ad has been running.
- Creative metadata is parsed to categorize ad formats such as video, image, or dynamic collections.
- The structured data is returned to the agent, providing a clean JSON response for downstream analysis.
Meta Ads Collector Skill Setup
To utilize this within your Openclaw Skills environment, you need a Facebook Developer App with Ad Library API access. Configure the following environment variables in your project:
export META_ACCESS_TOKEN="your_access_token"
export META_APP_ID="your_app_id"
export META_APP_SECRET="your_app_secret"
Ensure the Meta Ads Service is initialized within your repository to handle the core API communication.
Meta Ads Collector Skill Data Schema & Taxonomy
The skill returns a structured MetaAdsData object. Below is the organizational taxonomy for the collected data:
| Field | Type | Description |
|---|---|---|
| activeAds | number | Total count of currently active advertisements. |
| formatsUsed | string[] | Array of creative types (e.g., image, video, carousel). |
| longestRunningAdDays | number | Age in days of the oldest active campaign. |
| adTypes | string[] | Categories such as POLITICAL_AND_ISSUE_ADS or OTHER. |
| estimatedSpend | string | Optional range of spend (available for specific categories). |
| error | string | Error message if the collection process fails. |
Meta Ads Collector Skill Advanced Features
- Domain-Level Filtering: Improve precision by matching ad content against specific brand domains to avoid naming collisions.
- Graceful Degradation: The skill is designed to never block a pipeline; it returns zeroed data with clear error flags rather than throwing exceptions.
- Multi-Format Detection: Automatically classifies complex ad types including dynamic ads and collection ads based on snapshot URLs.
- Pagination Support: Capable of processing the first 100 results per request to provide a representative sample for audits.
- Seamless Workflow Integration: Designed to work within larger Openclaw Skills ecosystems for automated marketing reporting and real-time dashboard updates.
SKILL.md
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