A server-side scraping tool designed to extract text from the first post of a given social media URL.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install facenot
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 facenot 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 Facebook Post Reader?
The Facebook Post Reader is a specialized skill designed to bridge the gap between social media content and AI analysis. By providing a direct URL, this skill attempts to scrape and return the primary text content from profiles or specific posts. It is a foundational utility for developers using Openclaw Skills who need to integrate real-time social data into their AI agents.
While primarily functioning as a server-side scraping tool, it provides a structured JSON response that makes it easy for LLMs to interpret and process web data. It is particularly useful for public-facing pages where content is accessible without complex authentication headers.
Facebook Post Reader Use Cases
- Automating the collection of public status updates for sentiment analysis.
- Monitoring specific profiles for content changes within Openclaw Skills workflows.
- Gathering raw text from social links to summarize or translate using AI agents.
- Speeding up research tasks by extracting text without manual copying and pasting.
How Facebook Post Reader Works
- The AI agent receives a URL as an input parameter.
- The skill triggers a Python script that performs a server-side request to the target page.
- The script identifies the specific HTML elements containing the first post content.
- Extracted text is cleaned and packaged into a JSON object.
- The skill returns the structured data to the agent for further processing or display.
Facebook Post Reader Setup
To integrate this skill into your environment, follow these steps:
# Navigate to your skills directory
cd skills/facebook-post-reader
# Install the required Python libraries
pip install -r requirements.txt
Ensure that your manifest.json is correctly configured to point to the scripts/skill.py execution path.
Facebook Post Reader Data Schema & Taxonomy
The skill utilizes a simple but effective schema for data exchange:
| Attribute | Type | Description |
|---|---|---|
| url | string | The input URL of the Facebook post or profile. |
| status | string | Returns "success" or "error" based on the scrape result. |
| content | string | The extracted text content or a descriptive error message. |
File Structure:
- scripts/skill.py: The core logic for data extraction.
- manifest.json: Metadata defining the skill for Openclaw Skills agents.
- references/schema.md: Detailed data structure documentation.
Facebook Post Reader Advanced Features
- Modular Python backend allowing for easy replacement of the scraping logic with Playwright or Puppeteer.
- JSON-ready output specifically formatted for seamless integration with other Openclaw Skills.
- Extensible schema to include metadata like timestamps or engagement counts in future updates.
- Lightweight footprint requiring minimal server resources for basic HTML parsing.
SKILL.md
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