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微信公众号文章抓取 (Jeff版)

Name: 微信公众号文章抓取 (Jeff版)
Author: jeffli2002

by jeffli2002 · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ✓ Security Clean

146

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Install in OpenClaw

/install jeffli-wechat-article

Description

微信公众号文章抓取工具。将微信公众号文章转换为 Markdown 格式，支持图片本地下载。当用户提到抓取微信公众号文章、提取公众号内容、爬取微信文章时触发。

README (SKILL.md)

微信公众号文章抓取

将微信公众号文章转换为 Markdown 格式，支持图片本地下载。

脚本位置

主程序：scripts/main.py
MCP Server：scripts/mcp_server.py

快速使用

cd ~/.openclaw/workspace/skills/wechat-article
python3 scripts/main.py "文章URL" -o /root/.openclaw/workspace/output

参数

参数	说明
`-o DIR`	输出目录（默认 ./output）
`-v`	调试日志
`--no-images`	不下载图片，保持远程 URL
`--force`	覆盖已存在文件
`--no-headless`	显示浏览器（用于处理验证码）

输出结构

output/
 └── 文章标题/
     ├── 文章标题.md
     └── images/
         ├── img_001.jpg
         └── ...

注意事项

验证码：遇到验证页面时加 --no-headless 手动处理
反爬：微信有频率限制，建议间隔操作
图片失败：保留远程 URL，可用 --force 重试

依赖

camoufox
markdownify
beautifulsoup4
httpx
aiohttp

Usage Guidance

This skill appears to do what it says: fetch WeChat article pages in a headless browser, convert HTML to Markdown, and download images into an output folder. Before installing or running: - Be aware it performs live web requests and will download a camoufox browser binary on first run — run it in an isolated environment if you want to limit risk. - You may need to pip-install requirements (requirements.txt) before running; confirm dependency sources. - Running the MCP server exposes conversion tools to any MCP-capable client (over stdio by default); that lets an AI invoke scraping and write files — only enable the server for trusted clients. - If you need stricter assurance, review the camoufox package and its download behavior (where the browser binary comes from) and run the tool manually on a sample URL in a safe workspace first.

Capability Analysis

Type: OpenClaw Skill Name: jeffli-wechat-article Version: 1.0.0 The skill is a well-structured and legitimate tool for converting WeChat Official Account articles into Markdown format. It uses the Camoufox stealth browser (scripts/scraper.py) to handle WeChat's anti-bot measures and JavaScript rendering, and includes robust logic for concurrent image downloading (scripts/downloader.py) and metadata extraction (scripts/parser.py). No evidence of data exfiltration, malicious execution, or prompt injection was found; the code logic is entirely consistent with its stated purpose.

Capability Assessment

✓ Purpose & Capability

Name/description match the code and scripts: the package fetches rendered WeChat pages (camoufox), parses content, converts to Markdown, and optionally downloads images. The use of a stealth browser (camoufox) and an MCP server is coherent for anti-detection scraping and AI integration.

✓ Instruction Scope

SKILL.md instructs the agent to run the included CLI or MCP server and to write outputs into an output directory. The runtime instructions and code operate on article URLs and local output paths only; they do not ask the agent to read unrelated files, environment variables, or exfiltrate data to unexpected endpoints.

ℹ Install Mechanism

The registry contains no formal install spec (instruction-only), but the repository includes requirements.txt and uses camoufox which will auto-download a browser binary on first run. Running the skill will therefore pull packages (pip) and possibly large browser artifacts from the internet — review and run in a controlled environment if you do not trust those origins.

✓ Credentials

The skill declares no required environment variables or credentials and the code does not access secrets. Network access is required to fetch WeChat pages and images (expected for a scraper). There are minor dependency-list mismatches (SKILL.md lists aiohttp while requirements.txt lists mcp), but nothing requesting unrelated credentials.

✓ Persistence & Privilege

The skill does not request always:true and does not modify other skills or system-wide configs. It exposes an MCP server (stdio transport) so an AI client can invoke its tools; autonomous invocation is the platform default and not a concern by itself. Outputs are written to the provided output directory (and debug HTML when parsing fails).

How to Use

Make sure OpenClaw is installed (local or Docker)
Run the install command in chat: /install jeffli-wechat-article
After installation, invoke the skill by name or use /jeffli-wechat-article
Provide required inputs per the skill's parameter spec and get structured output

Version History

v1.0.0

首次发布：微信公众号文章抓取工具，支持转换为Markdown格式和图片本地下载

Metadata

Slug jeffli-wechat-article

Version 1.0.0

License MIT-0

All-time Installs 0

Active Installs 0

Total Versions 1

Frequently Asked Questions

What is 微信公众号文章抓取 (Jeff版)?

微信公众号文章抓取工具。将微信公众号文章转换为 Markdown 格式，支持图片本地下载。当用户提到抓取微信公众号文章、提取公众号内容、爬取微信文章时触发。 It is an AI Agent Skill for Claude Code / OpenClaw, with 146 downloads so far.

How do I install 微信公众号文章抓取 (Jeff版)?

Run "/install jeffli-wechat-article" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is 微信公众号文章抓取 (Jeff版) free?

Yes, 微信公众号文章抓取 (Jeff版) is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does 微信公众号文章抓取 (Jeff版) support?

微信公众号文章抓取 (Jeff版) is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created 微信公众号文章抓取 (Jeff版)?

It is built and maintained by jeffli2002 (@jeffli2002); the current version is v1.0.0.

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