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 web-to-markdowngit 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/web-to-markdown)<a href="https://agentmods.dev/skills/dongsheng123132/u-claw/web-to-markdown"><img src="https://agentmods.dev/badge/skills/dongsheng123132/u-claw/web-to-markdown/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/web-to-markdown"><img src="https://agentmods.dev/badge/skills/dongsheng123132/u-claw/web-to-markdown.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 | $0.00034 | $0.00531 |
| Opus 5 | $0.00017 | $0.00266 |
| Sonnet 5 | $0.00007 | $0.00106 |
| Haiku 4.5 | $0.00003 | $0.00053 |
Grade A, and why
web-to-markdown scanned grade A with 1 finding 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 11d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "https://r.jina.ai/https://example.com/article" -o article.md What it actually says
网页转 Markdown
把用户给的网页链接抓下来，提取正文，转成干净的 Markdown，方便保存、总结或二次创作。
能力概述
- 正文提取：去掉导航/广告/页脚，只留主体内容
- 转 Markdown：标题、列表、链接、代码块保留结构
- 保存：可写入本地 .md 文件
操作方式
用 Bash 工具。首选 jina.ai 的免费 reader（无需依赖，最省事）：
# 最简：jina reader 直接返回干净 Markdown（在链接前加 https://r.jina.ai/）
curl -s "https://r.jina.ai/https://example.com/article" -o article.md
echo "已保存 -> article.md"; head -40 article.md
离线或 jina 不可用时，用 Python 本地转换：
python -c "import markdownify,requests" 2>/dev/null || pip install -q markdownify requests beautifulsoup4
python - <<'PY'
import requests, re
from bs4 import BeautifulSoup
from markdownify import markdownify as md
url = "https://example.com/article"
html = requests.get(url, timeout=15, headers={"User-Agent":"Mozilla/5.0"}).text
soup = BeautifulSoup(html, "html.parser")
for t in soup(["script","style","nav","footer","aside"]): t.decompose()
body = soup.find("article") or soup.find("main") or soup.body
out = md(str(body), heading_style="ATX")
out = re.sub(r"\n{3,}", "\n\n", out).strip()
open("article.md","w",encoding="utf-8").write(out)
print("已保存 -> article.md，", len(out), "字")
PY
使用建议
- 先问用户要不要保存到文件、文件名
- 微信公众号/知乎等需要登录的页面可能抓取受限，如失败如实告知
- 抓取后可顺手做"总结要点"，结合 china-search / deepseek-helper 技能
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.
- 11d ago First seen · 52 lines · 34 tokens per session scan A c8dc60cc30a4
web-to-markdown is a skill published in the GitHub repository dongsheng123132/u-claw (1,747 stars, last pushed 3d ago), licensed MIT. It adds 34 tokens to every session and 531 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). 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…