【Reverse Engineering WorkBuddy: Open-Sourcing a Skill for Searching WeChat Articles】

Recently, while dissecting the Deep Research feature built into WorkBuddy, I discovered that during execution, it comes with a skill called WeChat Article Search that can search for public account articles.

I also found that this skill is just sitting there in WorkBuddy’s harness folder.

The underlying principle is that WeChat public accounts have opened a doorway to Sogou Search, and this skill essentially crawls articles by calling Sogou’s interface. Of course, the anti-crawling measures and parsing involved are elegantly designed — tech experts should check it out!

Open-source address: https://github.com/zjp1997720/wechat-article-search

You can also install it with one command: npx skills add zjp1997720/wechat-article-search

zjp1997720/wechat-article-search

Source: https://github.com/zjp1997720/wechat-article-search

WeChat Article Search

中文文档

Search WeChat public account (公众号) articles by keyword. Returns structured JSON with title, summary, publish time, source account, and link — no API key required.

Agent Install

npx skills add zjp1997720/wechat-article-search -g -a codex --skill wechat-article-search -y

Requirements

• Node.js 18+ (tested on Node 20)
• One npm dependency: cheerio. Run npm install inside the skill folder after install.

What It Does

• Keyword search across WeChat public accounts via Sogou WeChat Search — returns 1–50 articles per query.
• Structured output: title, URL, summary, publish datetime, date text, relative time, source account name.
• Optional real-URL resolution (-r): converts Sogou redirect links into mp.weixin.qq.com direct links when reachable.
• Optional file output (-o): writes JSON to disk for archival.

How It Works

The skill drives a single self-contained Node.js script (scripts/search_wechat.js) that queries Sogou WeChat Search (weixin.sogou.com), parses the result HTML with cheerio, and emits structured JSON to stdout. No API keys, no MCP tools, no platform coupling — it works in any agent runtime that can run node.

Example Requests

Search WeChat articles about "Loop Engineering", give me 10.

搜一下"AI培训"相关的公众号文章,要 5 条,保存到 result.json。

CLI Usage

node scripts/search_wechat.js "<query>" [-n <num>] [-o <file>] [-r]

First run: npm install in the skill folder to pull cheerio.

Safety & Limits

• Uses public Sogou WeChat Search as the data source. Anti-bot rate limiting can intermittently return empty results or block URL resolution — retry with a different keyword or wait.
• -r URL resolution succeeds inconsistently under Sogou’s anti-spider policy. Failures keep the Sogou redirect link and set url_resolved: false.
• For study and research only. Do not use for large-scale commercial crawling. Excessive use may get your IP temporarily blocked.

Repository Layout

.
├── README.md
├── README.zh-CN.md
├── LICENSE
├── SKILL.md
├── agents/openai.yaml
├── package.json
└── scripts/
    └── search_wechat.js

License

MIT

ZhiJian AI - DaPeng (@zjp1997720): 【Open source a skill that opens a skill】 You might be a bit confused by this title. The functionality is just one line: one-click open source your local skill to GitHub and support npx skills. The main theme is: the more you share, the luckier you get! Here’s the address: