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 agentmods add skills/lovstudio/any2pdf/lov-any2pdfnpx skills add lovstudio/any2pdf --skill lov-any2pdfgit clone --depth 1 https://github.com/lovstudio/any2pdfWhat 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 | $0.00197 | $0.02863 |
| Opus 5 | $0.00098 | $0.01432 |
| Sonnet 5 | $0.00039 | $0.00573 |
| Haiku 4.5 | $0.00020 | $0.00286 |
Grade B, and why
lov-any2pdf scanned grade B 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 2d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo apt install fonts-dejavu-core fonts-liberation fonts-freefont-ttf fonts-noto fonts-noto-cjk fonts-noto-color-emoji How it starts
The opening of the file, as written. The whole thing — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
any2pdf — Markdown to Professional PDF
This skill converts any Markdown file into a publication-quality PDF using Python's reportlab library. It was developed through extensive iteration on real Chinese technical reports and solves several hard problems that naive MD→PDF converters get wrong.
When to Use
- User wants to convert
.md→.pdf - User has a markdown report/document and wants professional typesetting
- Document contains CJK characters (Chinese/Japanese/Korean) mixed with Latin text
- Document has fenced code blocks, markdown tables, or nested lists
- Document has local/remote images, Obsidian callouts, emoji, or math formulas
- User wants a cover page, table of contents, or watermark in their PDF
Quick Start
python md2pdf/scripts/md2pdf.py \
--input report.md \
--output report.pdf \
--title "My Report" \
--author "Author Name" \
--theme warm-academic
All parameters except --input are optional — sensible defaults are applied.
Pre-Conversion Options (MANDATORY)
IMPORTANT: You MUST use the AskUserQuestion tool to ask these questions BEFORE
running the conversion. Do NOT list options as plain text — use the tool so the user
gets a proper interactive prompt. Ask all options in a SINGLE AskUserQuestion call.
Use AskUserQuestion with the following template. The tone should be friendly and
concise — like a design assistant, not a config form:
开始转 PDF!先帮你确认几个选项 👇
━━━ 📐 设计风格 ━━━
a) 暖学术 — 陶土色调,温润典雅,适合人文/社科报告
b) 经典论文 — 棕色调,灵感源自 LaTeX classicthesis,适合学术论文
c) Tufte — 极简留白,深红点缀,适合数据叙事/技术写作
d) 期刊蓝 — 藏蓝严谨,灵感源自 IEEE,适合正式发表风格
e) 精装书 — 咖啡色调,书卷气,适合长篇专著/技术书
f) 中国红 — 朱红配暖纸,适合中文正式报告/白皮书
g) 水墨 — 纯灰黑,素雅克制,适合文学/设计类内容
h) GitHub — 蓝白极简,程序员熟悉的风格
i) Nord 冰霜 — 蓝灰北欧风,清爽现代
j) 海洋 — 青绿色调,清新自然
━━━ 🖼 扉页图片(封面之后的全页插图) ━━━
1) 跳过
2) 我提供本地图片路径
3) AI 根据内容自动生成一张
━━━ 💧 水印 ━━━
1) 不加
2) 自定义文字(如 "DRAFT"、"内部资料")
━━━ 📇 封底物料(名片/二维码/品牌) ━━━
1) 跳过
2) 我提供图片
3) 纯文字信息
示例回复:"a, 扉页跳过, 水印:仅供学习参考, 封底图片:/path/qr.png"
直接说人话就行,不用记编号 😄
What ships with it
3 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.
- 2d ago First seen · 232 lines · 197 tokens per session scan B 4cd085303480
lov-any2pdf is a skill published in the GitHub repository lovstudio/any2pdf (204 stars, last pushed 22d ago), licensed MIT. It adds 197 tokens to every session and 2,863 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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