A high-performance real-time search tool for fetching articles, videos, and media from the WeChat ecosystem without requiring a personal WeChat account.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install wechat-search-sou
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-search-sou 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 Search?
The WeChat Search tool is a robust utility designed to fetch real-time data from the WeChat (Weixin) ecosystem. It interfaces directly with WeChat search entry points to deliver seconds-level updates on articles, videos, and image media. This tool is built to assist content creators, data analysts, and researchers in gathering authoritative information from verified publishers and mainstream media.
By integrating WeChat Search into your repertoire of Openclaw Skills, you gain the ability to mine trending topics, perform competitor analysis, and track public opinion with precision. Since it only requires a Node.js environment and does not require active WeChat account credentials, it provides a safe, lightweight, and completely cross-platform solution (Windows, macOS, Linux) for automation.
WeChat Search Use Cases
- Content Trend Analysis: Retrieve hot articles or videos on topics like AI or tech to understand what is currently capturing attention.
- Real-Time Event Tracking: Monitor breaking news and industry updates on WeChat as they happen with second-level updates.
- Competitor Auditing: Analyze the publishing strategy of competitors by filtering search results based on publication date or popularity.
- Market Research: Collect structured data from WeChat's verified accounts for academic, business, or marketing intelligence.
How WeChat Search Works
- Trigger: The AI agent identifies a search request containing WeChat-specific keywords (e.g., articles, videos, or real-time dynamics).
- Authentication: The CLI utility reads the GUAIKEI_API_TOKEN environment variable to authenticate the API request.
- Query Execution: It invokes specialized Node.js command-line scripts (article-cli.js or video-cli.js) to query the WeChat ecosystem based on keywords, duration, and sorting parameters.
- Data Retrieval & Serialization: The tool securely fetches matching results from verified publishers and writes them as structured JSON logs into the designated logs directory.
WeChat Search Setup
Prerequisites
Ensure you have Node.js installed on your machine and a valid API token from the provider.
To acquire a token, contact WeChat support via <13395823479> or visit the Guaikei Website.
Configuration
Set your GUAIKEI_API_TOKEN environment variable.
On macOS/Linux:
export GUAIKEI_API_TOKEN="your_api_token_here"
On Windows (Command Prompt):
set GUAIKEI_API_TOKEN="your_api_token_here"
Running Search Commands
Run article search:
node scripts/wechat/article-cli.js --keyword "AI"
Run video search:
node scripts/wechat/video-cli.js --keyword "AI"
WeChat Search Data Schema & Taxonomy
The WeChat Search tool organizes search inputs and saves outputs locally. This makes it incredibly efficient to integrate with other Openclaw Skills that require structured input/output flows.
Execution Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
keyword |
string | Yes | The search keyword or phrase. |
sort |
number | No | Sorting criteria (e.g., 2 for hot articles, 1 for latest videos). |
publishTime |
number | No | Filter articles by publish timeframe (e.g., 1 for the past 24 hours). |
duration |
number | No | Filter videos by duration (e.g., 2 for 5-20 minutes). |
Output Logs Directory
Results are automatically saved inside the skill's logs/ directory in JSON format:
- Articles Log: Saved as
[timestamp]_[keyword]_article.json - Videos Log: Saved as
[timestamp]_[keyword]_video.json
These schemas are fully compliant with JSON Schema Draft-07 for clean LLM and programmatic ingestion.
WeChat Search Advanced Features
- Granular Filters: Supports precise filtering including publishing timestamps, content hotness, and video duration constraints.
- No-Account Scraping: Conduct search queries safely without providing personal WeChat credentials, preventing account flags.
- LLM-Friendly Integration: Designed with strict JSON schemas (
assets/*_cli_req.schema.json) to allow seamless parsing and triggering by LLM agents. - Cross-Platform Compatibility: Fully compatible with Linux, macOS, and Windows environments, making it ideal for self-hosted cron automation.
SKILL.md
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