A production-grade tool for crawling and parsing WeChat Official Account articles with high precision and automated content cleaning.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install read-wechat-article
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 read-wechat-article 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 Reader?
This skill provides a robust solution for developers and AI agents to programmatically access WeChat Official Account content. By performing server-side HTML requests rather than browser rendering, it ensures rapid response times while intelligently stripping away advertisements, social buttons, and non-essential metadata. It is an essential addition to any developer's collection of Openclaw Skills for handling Chinese social media content.
The tool is designed for performance and reliability, featuring built-in retry mechanisms and support for multiple output formats including HTML, Markdown, and plain text. It transforms messy web pages into structured data suitable for LLM processing, research, or archival.
WeChat Article Reader Use Cases
- Automated research and data gathering from WeChat Official Accounts for market analysis.
- Building knowledge bases or RAG systems using high-quality social media content.
- Converting WeChat articles into clean Markdown for personal documentation or PKM systems.
- Programmatic monitoring of specific authors or publications for updates.
How WeChat Article Reader Works
- The system validates and cleans the provided WeChat article URL to remove tracking parameters and ensure compatibility.
- It initiates a high-performance HTTP request using persistent connections to retrieve the raw HTML content.
- A precision parser identifies core metadata such as the author, title, and publication timestamp.
- An automated cleaning sequence removes scripts, styles, ad blocks, and social engagement elements like like-counts and share buttons.
- The cleaned content is converted into the requested format (e.g., Markdown) while calculating metrics like word count and estimated reading time.
WeChat Article Reader Setup
To integrate this into your workflow, first install the necessary dependencies via pip:
pip install requests beautifulsoup4 markdownify
To use it as a standalone script for your Openclaw Skills projects, run:
python read_wechat_article.py "[YOUR_WECHAT_URL]" -o output.json
WeChat Article Reader Data Schema & Taxonomy
The skill returns a structured JSON object containing the following fields:
| Field | Type | Description |
|---|---|---|
| title | string | The headline of the parsed article |
| author | string | The name of the content creator |
| publish_time | string | The timestamp when the article was published |
| content_markdown | string | The full body content cleaned and converted to Markdown |
| images | array | A list of URLs for all images found in the article |
| word_count | integer | Total character count for length analysis |
| read_time_minutes | integer | Estimated time required to read the article |
WeChat Article Reader Advanced Features
- Server-side HTML parsing for maximum speed without the overhead of headless browsers.
- Intelligent content cleaning that targets specific WeChat-specific CSS classes and ad structures.
- Multi-format output support including Markdown, JSON, and raw text.
- Robust error handling with configurable retry delays and network timeout settings.
- Built-in compliance guidelines to ensure the ethical use of Openclaw Skills according to platform rules.
SKILL.md
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