A high-performance utility for extracting full text and metadata from WeChat Official Account (MP) articles.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install wechat-article-skill
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 wechat-article-skill 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 WeChat Article Fetcher?
The WeChat Article Fetcher is a specialized tool designed to bridge the gap between WeChat's closed ecosystem and AI processing. It enables Openclaw Skills to automatically detect links starting with mp.weixin.qq.com/s/ and convert them into clean, structured text that LLMs can easily consume.
Built with reliability in mind, it utilizes a dual-layered approach for content acquisition. It primarily uses an optimized Python script with authentic User-Agent spoofing to bypass common bot detection, falling back to browser-based automation only when necessary to ensure 100% success rates even against strict server-side checks.
WeChat Article Fetcher Use Cases
- Automatically summarizing long-form WeChat articles shared in a chat interface.
- Researching industry trends within the WeChat ecosystem for data analysis.
- Archiving official public account announcements into searchable knowledge bases.
- Extracting metadata like authors and publication dates for content curation.
How WeChat Article Fetcher Works
- Link Detection: The system monitors input for URLs matching the mp.weixin.qq.com/s/ pattern.
- Initial Retrieval: It first executes the get_content.py script which uses urllib and certifi with a real-world User-Agent.
- Validation: The tool checks the script's exit code; if successful, it passes the stdout directly to the AI model.
- Fallback Mechanism: If the script fails (returning a 403 or detection error), it triggers the browser tool to navigate and take a snapshot of the rendered page.
- Content Parsing: Key elements like #page-content and #activity-name are targeted to extract the clean article body and title.
WeChat Article Fetcher Setup
To integrate this capability into your Openclaw Skills environment, install the necessary Python dependencies:
# Install required dependencies
pip install -r requirements.txt
# Manual test of the fetcher script
python scripts/get_content.py --url "https://mp.weixin.qq.com/s/example_id"
WeChat Article Fetcher Data Schema & Taxonomy
The fetcher organizes extracted data by targeting specific DOM elements within the WeChat article structure:
| Element Type | CSS Selector / Source | Description |
|---|---|---|
| Article Body | #page-content |
The core text and internal HTML structure. |
| Title | #activity-name or h1 |
The headline of the article. |
| Author | .account_nickname |
The name of the WeChat Official Account. |
| Metadata | Page Metadata | Includes publication timestamps and original IDs. |
| Images | WeChat CDN | Specialized handling for WeChat-specific image domains. |
WeChat Article Fetcher Advanced Features
- Intelligent Retries: Built-in logic to attempt retrieval up to 3 times before failing.
- User-Agent Rotation: Uses authentic browser headers to minimize 403 Forbidden errors.
- Hybrid Execution Flow: Seamlessly switches between a headless script and a full browser environment based on anti-bot resistance.
- Error Diagnostics: Detailed stderr reporting that instructs the AI agent on when to switch tools.
SKILL.md
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