A powerful utility for scraping and converting WeChat Official Account articles into multiple offline formats with full asset preservation.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install wechat-article-conversion
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-conversion 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 within the Openclaw Skills ecosystem designed to bypass the ephemeral nature of web-based articles. It allows developers and researchers to scrape WeChat Official Account content and convert it into high-fidelity local files. By directly requesting data from the source, it eliminates the need for complex login states or cookie management.
This skill excels at preserving the original visual integrity of articles. It doesn't just grab text; it downloads images and CSS, localizing them into a structured directory. Whether you need a clean Markdown file for your personal knowledge base or a complete HTML snapshot for offline reading, this tool ensures the content is captured accurately with all metadata intact.
WeChat Article Fetcher Use Cases
- Archiving WeChat Official Account articles for long-term offline storage.
- Converting social media content into Markdown for integration into Obsidian or Notion.
- Batch downloading research materials from multiple WeChat links into structured JSON or Excel formats.
- Creating high-fidelity HTML mirrors of articles including localized images and styles.
How WeChat Article Fetcher Works
- The user provides a WeChat article URL or a list of multiple links.
- The agent prompts the user to select one or more output formats (Markdown, HTML, Text, JSON, or Excel).
- The skill executes a Python-based scraping script that sends a request to the WeChat domain with specialized headers (Chrome UA and Referer).
- Content is parsed using html5lib, identifying the article body, metadata (author, date), and lazy-loaded images.
- Assets such as CSS and images are downloaded concurrently (up to 8 threads) and deduplicated based on content hashes.
- The final files are organized and saved to the user's desktop in a structured folder named after the article title and ID.
WeChat Article Fetcher Setup
To use this feature within Openclaw Skills, ensure you have the necessary dependencies installed:
pip install html5lib
No browser login or cookies are required for standard scraping, as the script handles requests directly via the WeChat Official Accounts domain.
WeChat Article Fetcher Data Schema & Taxonomy
The skill organizes exported data into specific directory structures to ensure asset persistence:
| Format | Extension | Description |
|---|---|---|
| Markdown | .md | Includes title, author, date, and source link metadata. |
| HTML | .html | Independent webpage with localized CSS and images in an assets/ folder. |
| Excel | .xlsx | Tabular data containing metadata and the full article text. |
| JSON | .json | Structured raw data including all metadata fields. |
| Text | .txt | Plain text content without formatting. |
HTML Directory Structure:
ArticleTitle_ID/index.html(Main entry)assets/(Localized images and CSS files)
WeChat Article Fetcher Advanced Features
- Multi-format concurrent export: Select multiple formats (e.g., 1,3,5) in a single request.
- Intelligent Asset Management: CSS files are automatically inlined if under 500KB or linked externally if larger to prevent file bloat.
- Batch Processing: Submit a file containing multiple URLs for automated, sequential scraping.
- Visual Preservation: Specifically handles WeChat's lazy-loading (
data-src) and hidden content styles to ensure no blank pages. - Deduplication: Uses content hashing to ensure the same image or stylesheet is only stored once across the export.
SKILL.md
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