WeChat Article Processor for Openclaw

An automated tool to crawl WeChat articles, extract structured data, and export them directly to Feishu documents.

hoyaryyj
v1.0.0
Apr 1, 2026
0
736
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install wechat-article-processor

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install wechat-article-processor 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 Processor?

The WeChat Article Processor is a specialized automation tool designed for the Openclaw Skills ecosystem. It streamlines the process of capturing high-quality content from WeChat Official Accounts by automatically crawling full articles, extracting key metadata, and organizing the content into a clean, structured format.

By converting these articles into Feishu (Lark) documents, it enables seamless knowledge management and team collaboration. This skill is particularly valuable for researchers, marketers, and knowledge workers who need to archive social media content in a professional document format without the manual burden of copying and pasting.

WeChat Article Processor Use Cases

  • Archiving important industry insights from WeChat Official Accounts to a centralized team knowledge base.
  • Converting long-form social media articles into structured Markdown for easier reading and editing in Feishu.
  • Automatically generating summaries and key takeaways from WeChat content to save time on research.
  • Triggering document creation instantly just by sharing a WeChat article link with your AI agent.

How WeChat Article Processor Works

  1. The skill detects a WeChat article link shared by the user within the Openclaw Skills environment.
  2. It utilizes a browser automation tool to access the URL and fetch the full webpage content.
  3. The system extracts specific metadata including the article title, author, publication date, and source URL.
  4. Content is parsed and structured using Markdown, generating summaries, key points, and hierarchical headings.
  5. Finally, it uses the Feishu API to create a new document containing the structured content and returns the link to the user.

WeChat Article Processor Setup

To get started with this skill, ensure you have the following prerequisites configured:

  • Ensure your AI agent has the Openclaw Skills environment properly configured.
  • Authorize the Feishu integration (feishu_create_doc) within your environment to allow document creation.
  • Make sure the browser automation tool is accessible to the agent.
  • To start, simply provide a WeChat article URL in the chat:
# Example trigger input
https://mp.weixin.qq.com/s/example-article-id

WeChat Article Processor Data Schema & Taxonomy

The skill organizes data into a structured format before exporting. The resulting Feishu document follows this schema:

Component Description Format
Title Original article headline Heading 1
Metadata Author, publication date, and source link Key-Value List
Summary AI-generated key takeaways and core viewpoints Bulleted List
Content Full article body with hierarchical headings Structured Markdown
Quotes Classic quotes or essential content from the original text Blockquotes

WeChat Article Processor Advanced Features

  • Automatic extraction of core viewpoints and classic quotes for quick skimming and referencing.
  • Hierarchical structuring of long-form content using multi-level headings for better document navigation.
  • Intelligent paragraph simplification to highlight essential information while maintaining the original context.
  • Error handling for login requirements or CAPTCHAs, providing user prompts when manual intervention is needed.

SKILL.md


Loading

Related Openclaw Skills

METADATA

Github Stars: 0
forks: 0

Featured*