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 pdf-toolkitgit 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/pdf-toolkit)<a href="https://agentmods.dev/skills/dongsheng123132/u-claw/pdf-toolkit"><img src="https://agentmods.dev/badge/skills/dongsheng123132/u-claw/pdf-toolkit/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/pdf-toolkit"><img src="https://agentmods.dev/badge/skills/dongsheng123132/u-claw/pdf-toolkit.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 | $0.00030 | $0.00566 |
| Opus 5 | $0.00015 | $0.00283 |
| Sonnet 5 | $0.00006 | $0.00113 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
pdf-toolkit 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 13d 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
PDF 工具箱
帮用户对本地 PDF 文件做常见处理：合并、拆分、提取文字、转图片。优先用系统已有工具，
没有就用 Python 的 pypdf（轻量纯 Python，必要时 pip install pypdf 自动安装）。
能力概述
- 合并：把多个 PDF 拼成一个
- 拆分：按页拆成多份，或抽取指定页
- 提取文字：把 PDF 内容导出成纯文本，便于总结/检索
- 页数/信息：查看 PDF 总页数、元信息
操作方式
用 Bash 工具执行。下面以 pypdf 为例（跨平台、无需 Office/Acrobat）：
# 确保依赖（仅首次，已装会秒过）
python -c "import pypdf" 2>/dev/null || pip install -q pypdf
# 合并 a.pdf b.pdf -> merged.pdf
python - <<'PY'
from pypdf import PdfWriter
w = PdfWriter()
for f in ["a.pdf", "b.pdf"]:
w.append(f)
w.write("merged.pdf"); w.close()
print("已合并 -> merged.pdf")
PY
# 提取全部文字
python - <<'PY'
from pypdf import PdfReader
r = PdfReader("input.pdf")
print("\n".join((p.extract_text() or "") for p in r.pages))
PY
# 抽取第 1-3 页 -> sub.pdf
python - <<'PY'
from pypdf import PdfReader, PdfWriter
r = PdfReader("input.pdf"); w = PdfWriter()
for i in range(0, 3):
w.add_page(r.pages[i])
w.write("sub.pdf"); w.close()
print("已抽取 1-3 页 -> sub.pdf")
PY
使用建议
- 处理前先
ls确认文件存在、用python -c "from pypdf import PdfReader;print(len(PdfReader('x.pdf').pages))"看页数 - 扫描件（图片型 PDF）提取不到文字属正常，需 OCR（提示用户）
- 输出文件默认放在与源文件同目录，操作完告诉用户生成的文件名
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.
- 13d ago First seen · 60 lines · 30 tokens per session scan A 399ae303d80d
pdf-toolkit is a skill published in the GitHub repository dongsheng123132/u-claw (1,748 stars, last pushed 5d ago), licensed MIT. It adds 30 tokens to every session and 566 once invoked, about $0.0002 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
pdf-generator
A document tool that turns Markdown, HTML, plain text, or template data into paginated PDF files. It supports A4 pages, page numbers, automatic page breaks, and Chinese text.
pdf-processor
A tool for working with PDF files: it can read text and tables, combine or split documents, convert pages to images, and show basic file details.
document-suite
A single document-processing toolkit for PDF, Word, Excel, PowerPoint, and Markdown files. It chooses a document-specific handler based on the file type or requested task.
pdf-analysis
A PDF analysis method for reading both normal PDFs with selectable text and scanned PDFs made from page images.
sn-da-non-spreadsheet-analysis
A skill for extracting and analysing content from Word files, PDFs, and PowerPoint presentations. It can work with text, tables, numbers, charts, formatting, and information across multiple documents.
ocr-and-documents
Extract text from PDFs and scanned documents. Use webextract for remote URLs, pymupdf for local text-based PDFs, marker-pdf for OCR/scanned docs. For DOCX use python-docx, for PPTX see the powerpoint skill.