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 qrcode-makergit 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/qrcode-maker)<a href="https://agentmods.dev/skills/dongsheng123132/u-claw/qrcode-maker"><img src="https://agentmods.dev/badge/skills/dongsheng123132/u-claw/qrcode-maker/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/qrcode-maker"><img src="https://agentmods.dev/badge/skills/dongsheng123132/u-claw/qrcode-maker.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 | $0.00456 |
| Opus 5 | $0.00012 | $0.00228 |
| Sonnet 5 | $0.00005 | $0.00091 |
| Haiku 4.5 | $0.00002 | $0.00046 |
Grade A, and why
qrcode-maker 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
二维码生成
帮用户把网址、文本、联系方式、WiFi 信息生成二维码图片，本地离线生成，不上传任何数据。
能力概述
- 网址/文本二维码：任意内容转二维码 PNG
- WiFi 二维码：扫码即连，免手输密码
- 终端预览：直接在对话里用字符画展示二维码
操作方式
用 Bash 工具，Python 的 qrcode 库（轻量、纯本地）：
python -c "import qrcode" 2>/dev/null || pip install -q "qrcode[pil]"
# 网址/文本 -> PNG
python - <<'PY'
import qrcode
qrcode.make("https://u-claw.org").save("qrcode.png")
print("已生成 -> qrcode.png")
PY
# WiFi 二维码（扫码自动连网）
python - <<'PY'
import qrcode
ssid, pwd, enc = "MyWiFi", "password123", "WPA" # enc: WPA / WEP / nopass
data = f"WIFI:T:{enc};S:{ssid};P:{pwd};;"
qrcode.make(data).save("wifi-qr.png")
print("已生成 WiFi 二维码 -> wifi-qr.png")
PY
# 终端字符画预览（不存文件，直接看）
python - <<'PY'
import qrcode
q = qrcode.QRCode(); q.add_data("https://u-claw.org"); q.make()
q.print_ascii(invert=True)
PY
使用建议
- 先确认用户要编码的内容、是否保存为文件
- 生成后用 Read 工具把 PNG 展示给用户看
- 内容过长（如整段文字）二维码会很密集，提示用户改用短链
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 · 53 lines · 24 tokens per session scan A eb43aa3af2fb
qrcode-maker is a skill published in the GitHub repository dongsheng123132/u-claw (1,746 stars, last pushed 2d ago), licensed MIT. It adds 24 tokens to every session and 456 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.
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