lov-any2pdf

lov-any2pdf is a skill for Claude Code, Codex from lovstudio/any2pdf. It costs 197 tokens per session (2,863 once invoked), scanned B, original, MIT.

A Markdown-to-PDF conversion procedure that creates professionally formatted PDF documents with reportlab, a Python document-generation library.

In plain words
What is it for?
Use it to convert Markdown into PDFs with options such as cover pages, clickable tables of contents, bookmarks, watermarks, page numbers, and selectable visual themes.
Why use it?
It handles document details that simple converters often mishandle, including mixed writing systems, code, tables, images, formulas, and navigation.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: names the AskUserQuestion tool.

Good fit Use it to convert Markdown into PDFs with options such as cover pages, clickable tables of contents, bookmarks, watermarks, page numbers, and selectable visual themes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lovstudio/any2pdf/lov-any2pdf
Install

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.

Any agent
npx skills add lovstudio/any2pdf --skill lov-any2pdf
Clone the repo
git clone --depth 1 https://github.com/lovstudio/any2pdf

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for lov-any2pdf

README.md
[![agentmods](https://agentmods.dev/badge/skills/lovstudio/any2pdf/lov-any2pdf/github.svg)](https://agentmods.dev/skills/lovstudio/any2pdf/lov-any2pdf)
Your own site
<a href="https://agentmods.dev/skills/lovstudio/any2pdf/lov-any2pdf"><img src="https://agentmods.dev/badge/skills/lovstudio/any2pdf/lov-any2pdf/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.

agentmods 80×15 button for lov-any2pdf

Your own site · 80×15
<a href="https://agentmods.dev/skills/lovstudio/any2pdf/lov-any2pdf"><img src="https://agentmods.dev/badge/skills/lovstudio/any2pdf/lov-any2pdf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 197 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,863 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Privilege Escalation · line 222
    Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.
    Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00197 $0.02863
Opus 5.5 $0.00079 $0.01145
Sonnet 5.5 $0.00039 $0.00573
Haiku 4.5 $0.00020 $0.00286

Measured 1mo ago against content hash 4cd085303480, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 1mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/md2pdf.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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
lov-any2pdf/SKILL.md · 232 lines

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 😄

Read the full file on GitHub · 232 lines

Files

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.

Changes

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.

  1. 1mo ago First seen · 232 lines · 197 tokens per session scan B 4cd085303480

Subscribe to this mod's changes

lov-any2pdf is a skill published in the GitHub repository lovstudio/any2pdf (212 stars, last pushed 2mo ago), licensed MIT. It adds 197 tokens to every session and 2,863 once invoked, about $0.0008 per session on Opus 5.5. 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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