A specialized CLI tool for searching and extracting metadata from WeChat Public Account articles based on specific keywords.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install wechat-article-search
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-search 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 Search?
The WeChat Article Search skill provides a streamlined way to access the vast repository of content within the WeChat ecosystem. It allows users to search for articles across various sectors, including technology, AI, finance, and social trends, directly through a command-line interface. This skill is particularly valuable for Openclaw Skills users who need to perform deep research or content monitoring within Chinese-language digital media.
By automating the retrieval of article titles, summaries, publication times, and source account names, it eliminates the need for manual searching. The tool is designed to assist developers and researchers in gathering structured data from one of the most significant social platforms in Asia, supporting both quick lookups and bulk data collection for analytical purposes.
WeChat Article Search Use Cases
- Finding the latest industry reports and articles from specific WeChat Official Accounts.
- Gathering reference materials and summaries for research topics like AI or social trends.
- Automating the collection of article links and metadata for content curation workflows.
- Programmatically retrieving structured data from the WeChat ecosystem for data analysis.
How WeChat Article Search Works
- The user provides a search keyword and specifies optional parameters such as the number of results or output format.
- The skill utilizes the cheerio library to parse search results from WeChat's content index.
- The script extracts core metadata including the article title, snippet, timestamp, and the publishing account's name.
- If requested, the tool performs an additional request to resolve intermediate redirects into direct WeChat article URLs.
- The final dataset is either displayed in the terminal or exported to a JSON file for use with other Openclaw Skills.
WeChat Article Search Setup
To get started with this skill, you must first install the required NodeJS dependency:
npm install -g cheerio
Once installed, you can perform a basic search by running:
node scripts/search_wechat.js "your_keyword"
WeChat Article Search Data Schema & Taxonomy
The skill generates structured article objects containing the following fields:
| Field | Description |
|---|---|
| Title | The headline of the WeChat article |
| URL | The direct or resolved link to the content |
| Summary | A brief abstract or snippet of the article content |
| Publish Time | The date and time the article was originally posted |
| Source | The name of the WeChat Official Account that published it |
You can export this data to a JSON file using the -o parameter for better integration with Openclaw Skills workflows.
WeChat Article Search Advanced Features
- Support for custom result limits up to 50 items per query using the
-nflag. - Real URL resolution capability to bypass intermediate links and get direct access to content.
- Automated JSON export functionality for data persistence and multi-agent integration.
- Flexible keyword matching across technology, education, and finance categories.
SKILL.md
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