U-Claw is a portable AI workspace that places an OpenClaw assistant, its configuration, memory, sessions, and tools on a USB drive. Users set it up on supported computers and carry the workspace between them, configuring a model with their own API key. The catalogue contains skills and instructions related to using or preparing this portable setup.
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 dongsheng123132/u-claw --skill wechat-articlegit clone --depth 1 https://github.com/dongsheng123132/u-clawWrote 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/dongsheng123132/u-claw/wechat-article)<a href="https://agentmods.dev/skills/dongsheng123132/u-claw/wechat-article"><img src="https://agentmods.dev/badge/skills/dongsheng123132/u-claw/wechat-article/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/dongsheng123132/u-claw/wechat-article"><img src="https://agentmods.dev/badge/skills/dongsheng123132/u-claw/wechat-article.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 | $0.00025 | $0.00938 |
| Opus 5 | $0.00013 | $0.00469 |
| Sonnet 5 | $0.00005 | $0.00188 |
| Haiku 4.5 | $0.00003 | $0.00094 |
Grade A, and why
wechat-article 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 10d 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
微信公众号文章写作助手
帮助运营者写出高阅读、高转发的微信公众号文章，覆盖从选题到排版的全流程。
功能概述
- 文章结构: 标题 → 引言 → 正文 → 总结 → 引导关注
- 排版规范: 符合微信阅读习惯的段落、字号、配色建议
- 标题优化: 生成符合微信生态的标题（主标题 + 副标题）
- 封面建议: 头图尺寸（900x383）、配色、文字排版建议
- 互动引导: 点赞、在看、转发的 CTA 话术
文章结构模板
【标题】控制在 30 字以内，前 15 字抓眼球
【摘要】出现在分享卡片，控制在 54 字
【引言】1-2 段，建立共鸣或抛出问题
（配图：与主题相关的首图）
【正文】
## 小标题一
内容段落...（每段 3-5 行）
## 小标题二
内容段落...
## 小标题三
内容段落...
【总结】回扣主题，升华观点
【尾部】
觉得有收获？点个「在看」让更多人看到 👇
关注我，每周分享 XX 干货
使用示例
写完整文章
帮我写一篇公众号文章，主题是"为什么35岁是程序员的分水岭"，3000字左右
优化标题
文章主题是AI工具推荐，帮我写10个公众号标题
改写排版
这篇文章内容不错但排版太密了，帮我优化成适合微信阅读的格式
写引导语
帮我写一段文章开头，主题是教育焦虑，要能引起家长共鸣
微信排版规范
- 正文字号: 15-16px（推荐15px）
- 字间距: 1-2px
- 行间距: 1.75-2倍
- 段间距: 空一行
- 两端缩进: 16px（手机端留白）
- 配色: 正文 #3f3f3f，强调 #007AFF 或品牌色
- 图片: 宽度 100%，JPG 格式，单张不超过 5MB
标题技巧
- 数字开头: "3个方法/5分钟学会"
- 疑问式: "为什么XX？答案出乎意料"
- 对比式: "XX和XX的差距，在于这一点"
- 紧迫感: "再不XX就晚了"
- 权威背书: "XX专家/XX万人验证"
适用场景
- 撰写公众号原创文章（干货、观点、故事等）
- 优化已有文章的标题和结构
- 为文章设计排版方案
- 写分享卡片的摘要文案
- 设计文章尾部的关注引导
不适用场景
- 写小红书笔记（风格不同，请用 xiaohongshu-writer）
- 需要直接在微信编辑器排版（本技能输出 Markdown 格式）
- 涉及时政新闻等需要资质的内容
- 需要真实数据支撑的行业报告（框架可用，数据需自备）
提升阅读量的关键
- 标题决定打开率，前 15 字是关键
- 首屏内容决定是否继续阅读
- 文章长度建议 1500-3000 字（太长容易跳出）
- 每 300 字配一张图，打破阅读疲劳
- 结尾的「在看」引导直接影响二次传播
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.
- 10d ago First seen · 107 lines · 25 tokens per session scan A 22d836238a70
wechat-article is a skill published in the GitHub repository dongsheng123132/u-claw (1,746 stars, last pushed 2d ago), licensed MIT. It adds 25 tokens to every session and 938 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 2026-08-30.
Other skills, from other repositories
qa-testing
Verify your work by actually operating the app or website you changed, instead of assuming it works. Strongly recommended whenever you build, modify, or debug a web app, website, or desktop GUI app. Drive real browsers with the agent-browser CLI and native desktop apps with the cua-driver CLI. These are installed on…
codex-app-threads
Create, list, read, message, wait on, fork, rename, archive, and pin Codex threads (sidebar tasks), plus automations and app navigation, using the app-native codexapp tools. Use when the session uses a custom (non-OpenAI) model, for example deepseek-v4-flash or mimo-v2.5, and the user asks to create a thread or a new…
codex-router-media
Generate video, music, speech, or images with the operator's MiniMax Token Plan subscription through the codex-router media CLI. Use when the session runs a MiniMax custom (non-OpenAI) model (for example minimax-m3) with the MiniMax Token Plan provider connected, and the user explicitly asks to create a video, a song…
codex-computer-use
Control local apps through Computer Use (the @oai/sky runtime) inside the Codex app. Use when the session uses a custom (non-OpenAI) model, for example deepseek-v4-flash or mimo-v2.5, and the user asks to control the computer, operate a desktop app's UI, use Safari or Chrome through computer use, click or type in an…
codex-in-app-browser
Drive the Codex in-app browser (open, navigate, click, type, screenshot, read page state) through the app's own noderepl runtime. Use when the session uses a custom (non-OpenAI) model, for example deepseek-v4-flash or mimo-v2.5, and the user asks to use the in-app browser, open or navigate a page in it, test a local…
codex-router
Orientation for custom (non-OpenAI) models running in the Codex app through the codex-router proxy. Explains that the app's native tools arrive as flattened codexapp and mcp names, that the router restores them so the app executes them, which companion skills to read before threads, browser, or computer-use work, and…