Wanwu is an enterprise platform for building AI agents, workflows, retrieval-augmented applications, and managing models in multi-tenant environments. It is designed for developers and enterprise teams delivering AI applications and integrations. The catalogue entries provide skills and agents for using the platform.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add UnicomAI/wanwu --skill wechat-article-spidergit clone --depth 1 https://github.com/UnicomAI/wanwuWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/unicomai/wanwu/wechat-article-spider)<a href="https://agentmods.dev/skills/unicomai/wanwu/wechat-article-spider"><img src="https://agentmods.dev/badge/skills/unicomai/wanwu/wechat-article-spider/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/unicomai/wanwu/wechat-article-spider"><img src="https://agentmods.dev/badge/skills/unicomai/wanwu/wechat-article-spider.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00024 | $0.00355 |
| Opus 5 | $0.00012 | $0.00178 |
| Sonnet 5 | $0.00005 | $0.00071 |
| Haiku 4.5 | $0.00002 | $0.00036 |
Grade A, and why
wechat-article-spider scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
wechat-article-spider
微信公众号文章爬虫 - 将微信公号文章转换为 Markdown + 本地图片
执行指令
cd scripts && pip install -r requirements.txt && python main.py
功能
- ✅ 输入微信公号文章 URL
- ✅ 自动抓取文章内容
- ✅ 下载所有图片到
images/文件夹 - ✅ 生成 Markdown 文件，图片使用相对路径引用
安装
cd wechat-article-dl/scripts
pip install -r requirements.txt
用法
命令行
python main.py <文章 URL> [输出目录]
示例
# 下载到当前目录
python main.py https://mp.weixin.qq.com/s/xxxxx
# 指定输出目录
python main.py https://mp.weixin.qq.com/s/xxxxx ./my-articles
输出结构
output/
├── 文章标题.md
└── images/
├── img_001_xxx.jpg
├── img_002_xxx.png
└── ...
注意事项
- 微信文章可能有反爬机制，如遇失败可稍后重试
- 部分动态加载的图片可能无法获取
- 图片文件名使用哈希值避免重复
依赖
- requests
- beautifulsoup4
- lxml
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 71 lines · 24 tokens per session scan A 8ea273321e47
wechat-article-spider is a skill published in the GitHub repository UnicomAI/wanwu (2,461 stars, last pushed 5d ago), licensed Apache-2.0. It adds 24 tokens to every session and 355 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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