A specialized browser automation tool designed to bypass JS-rendering hurdles and extract full content from WeChat public account articles.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install wechat-reader
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-reader 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 Reader?
The WeChat Reader is a technical solution for AI agents within the Openclaw Skills ecosystem to overcome the limitations of standard web fetching. Because WeChat public account articles (mp.weixin.qq.com) are heavily dependent on JavaScript rendering and implement anti-scraping measures, traditional tools often fail to retrieve anything beyond the page title.
By leveraging dedicated browser automation, this skill allows an agent to fully render the page, bypass simple bot detection, and capture the complete text of an article. This ensures that users can interact with WeChat content for summarization, translation, or data extraction without leaving their AI environment.
WeChat Reader Use Cases
- Summarizing long-form technical or news articles shared from WeChat public accounts.
- Translating Chinese WeChat content into English or other languages for international researchers.
- Extracting text data from JS-rendered mobile-first web pages that block standard scrapers.
- Monitoring specific public accounts for content updates or archival purposes.
How WeChat Reader Works
- Link Detection: The agent identifies a WeChat URL (mp.weixin.qq.com) within the conversation.
- Browser Initialization: The skill triggers a browser instance using a specific profile to navigate to the URL.
- Content Rendering: It waits for the JavaScript-heavy page to fully load the article body.
- Snapshot Capture: The agent executes a snapshot action to extract the DOM content into a readable text format.
- Cleanup: The browser tab is closed to preserve system resources.
- Final Processing: The extracted text is then passed to the LLM for summarization or analysis based on the user's prompt.
WeChat Reader Setup
To integrate this capability into your Openclaw Skills workflow, ensure your environment has the browser automation tool configured. Use the following logic within your agent prompts or tool definitions:
# Example logic for triggering the reader
browser(action="open", url="<wechat_url>", profile="openclaw")
browser(action="snapshot", targetId=<id>, maxChars=15000)
Ensure that the openclaw browser profile is properly initialized to handle session management if necessary.
WeChat Reader Data Schema & Taxonomy
The WeChat Reader organizes extracted data into a structured format for the LLM to process. Below is the metadata taxonomy used during the snapshot phase:
| Attribute | Description |
|---|---|
url |
The original mp.weixin.qq.com source link |
content |
The full-text output extracted from the JS-rendered body |
maxChars |
The character limit for the snapshot (default 15,000, expandable to 30,000) |
status |
Reports 'content removed' or 'login wall' if the page is inaccessible |
WeChat Reader Advanced Features
- High-Capacity Snapshots: Support for up to 30,000 characters for exceptionally long editorial pieces.
- Image Context Awareness: Captures alt text and image captions to provide visual context during summarization.
- Anti-Scraping Resilience: Uses a persistent browser profile to better navigate WeChat's rendering constraints.
- Error Handling: Built-in detection for removed content or mandatory login walls to provide clear feedback to the user.
SKILL.md
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