Creator · lovstudio
Last updated · Sep 6, 2026
Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code blocks, tables, blockquotes, Obsidian callouts, inline images, emoji fallback, LaTeX-style formulas, cover pages, clickable TOC, PDF bookmarks, watermarks, and
Creator · lovstudio
Last updated · Sep 6, 2026
Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code blocks, tables, blockquotes, Obsidian callouts, inline images, emoji fallback, LaTeX-style formulas, cover pages, clickable TOC, PDF bookmarks, watermarks, and
Creator · lovstudio
Last updated · Sep 6, 2026
Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code blocks, tables, blockquotes, Obsidian callouts, inline images, emoji fallback, LaTeX-style formulas, cover pages, clickable TOC, PDF bookmarks, watermarks, and
Creator · lovstudio
Last updated · Sep 6, 2026
Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code blocks, tables, blockquotes, Obsidian callouts, inline images, emoji fallback, LaTeX-style formulas, cover pages, clickable TOC, PDF bookmarks, watermarks, and
Sandbox only
Install targets
Codex install prompt
Install the "lov-any2pdf" agent skill from https://github.com/lovstudio/any2pdf/tree/main/lov-any2pdf. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code blocks, tables, blockquotes, Obsidian callouts, inline images, emoji fallback, LaTeX-style formulas, cover pages, clickable TOC, PDF bookmarks, watermarks, and page numbers. Supports multiple color themes (Configurable Academic, Nord, GitHub Light, Solarized, etc.) and is battle-tested for Chinese technical reports. Use this skill whenever the user wants to turn a .md file into a styled PDF, generate a report PDF from markdown, or create a print-ready document from markdown content — especially if CJK characters, code blocks, or tables are involved. Also trigger when the user mentions "markdown to PDF", "md2pdf", "any2pdf", "md转pdf", "报告生成", or asks for a "typeset" or "professionally formatted" PDF from markdown source. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"lovstudio-lov-any2pdf","task":"Install lov-any2pdf","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Document processing
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add lovstudio/any2pdf --skill lov-any2pdf
Maintenance
fresh
26d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
207
70/100 Quality · 73/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · The script fetches remote images via urllib, which could be a vector for SSRF or downloading malicious content if the markdown is untrusted. However, this is user-controlled and typical for such tools.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
207 GitHub stars
Repo activity
207 stars, 32 forks
Maintenance
26d since push
License
MIT
Install
npx skills add lovstudio/any2pdf --skill lov-any2pdf
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add lovstudio/any2pdf --skill lov-any2pdfDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill may drive a browser or interact with web pages.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20lov-any2pdf%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20lov-any2pdf%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/lovstudio-lov-any2pdf/install
Agent should check
Copy prompt
Task: Use lov-any2pdf in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20lov-any2pdf%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/lovstudio-lov-any2pdf/install
Install command: npx skills add lovstudio/any2pdf --skill lov-any2pdf
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/lovstudio-lov-any2pdf/install
LLM text format
/api/skills/lovstudio-lov-any2pdf/install?format=text
Find alternatives
/api/skills/search?q=lov-any2pdf&limit=3
Agent prompt
Use lov-any2pdf for this task. Review https://www.openagentskill.com/api/skills/lovstudio-lov-any2pdf/install, then install with: npx skills add lovstudio/any2pdf --skill lov-any2pdfRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/lovstudio-lov-any2pdf
LLM text
/api/registry/manifest/lovstudio-lov-any2pdf?format=text
Install alias
/api/registry/install/lovstudio-lov-any2pdf
Recommend
/api/registry/recommend?task=Use%20lov-any2pdf%20in%20an%20agent%20workflow&limit=3
Agent fit
Document processing
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Document processing
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO207 GitHub stars
Stars/forks activity
CHECK207 stars, 32 forks; issue activity unavailable in current metadata
Recent maintenance
PASS26d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Create assets
I need my agent to produce design assets, UI directions, presentations, or creative media workflows.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Design, build, test, and ship interfaces
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: lov-any2pdf description: > Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code blocks, tables, blockquotes, Obsidian callouts, inline images, emoji fallback, LaTeX-style formulas, cover pages, clickable TOC, PDF bookmarks, watermarks, and page numbers. Supports multiple color themes (Configurable Academic, Nord, GitHub Light, Solarized, etc.) and is battle-tested for Chinese technical reports. Use this skill whenever the user wants to turn a .md file into a styled PDF, generate a report PDF from markdown, or create a print-ready document from markdown content — especially if CJK characters, code blocks, or tables are involved. Also trigger when the user mentions "markdown to PDF", "md2pdf", "any2pdf", "md转pdf", "报告生成", or asks for a "typeset" or "professionally formatted" PDF from markdown source. license: MIT compatibility: > Requires Python 3.8+ and reportlab (`pip install reportlab`). Optional: matplotlib (`pip install matplotlib`) for rendered display formulas. macOS: uses Palatino, Songti SC, Menlo (pre-installed). Linux: uses DejaVu/Liberation/FreeFont/Noto, Noto CJK, Droid Sans Fallback, DejaVu Sans Mono, and Noto Emoji when available. metadata: author: contributors version: "1.1.0" tags: markdown pdf cjk reportlab typesetting ---
# 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
```bash 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 😄 ```
### Mapping User Choices to CLI Args
| Choice | CLI arg | |--------|---------| | Design style a-j | `--theme` with value from table below | | Frontispiece local | `--frontispiece <path>` | | Frontispiece AI | Generate image first, then `--frontispiece /tmp/frontispiece.png` | | Watermark text | `--watermark "文字"` | | Back cover image | `--banner <path>` | | Back cover text | `--disclaimer "声明"` and/or `--copyright "© 信息"` |
### Theme Name Mapping
| Choice | `--theme` value | Inspiration | |--------|----------------|-------------| | a) 暖学术 | `warm-academic` | Skill Publisher design system | | b) 经典论文 | `classic-thesis` | LaTeX classicthesis | | c) Tufte | `tufte` | Edward Tufte's books | | d) 期刊蓝 | `ieee-journal` | IEEE journal format | | e) 精装书 | `elegant-book` | LaTeX ElegantBook | | f) 中国红 | `chinese-red` | Chinese formal documents | | g) 水墨 | `ink-wash` | 水墨画 / ink wash painting | | h) GitHub | `github-light` | GitHub Markdown style | | i) Nord | `nord-frost` | Nord color scheme | | j) 海洋 | `ocean-breeze` | — |
### Handling AI-Generated Frontispiece
If user chose AI generation: read the document title + first paragraphs, use an image generation tool to create a themed illustration matching the chosen design style, show for approval, then pass via `--frontispiece /path/to/image.png`
## Architecture
``` Markdown → Preprocess (split merged headings) → Parse (code-fence-aware) → Story (reportlab flowables) → PDF build ```
Key components: 1. **Font system**: Palatino (Latin body), Songti SC (CJK body), Menlo (code) on macOS; auto-fallback on Linux 2. **CJK wrapper**: `_font_wrap()` wraps CJK character runs in `<font>` tags for automatic font switching 3. **Mixed text renderer**: `_draw_mixed()` handles CJK/Latin mixed text on canvas (cover, headers, footers) 4. **Code block handler**: `esc_code()` preserves indentation and line breaks in reportlab Paragraphs 5. **Smart table widths**: Proportional column widths based on content length, with 18mm minimum 6. **Bookmark system**: `ChapterMark` flowable creates PDF sidebar bookmarks + named anchors 7. **Heading preprocessor**: `_preprocess_md()` splits merged headings like `# Part## Chapter` into separate lines 8. **Image handler**: local, relative, `file://`, and remote markdown images are scaled into the body frame with fallback text on errors 9. **Callout renderer**: Obsidian-style `> [!NOTE]` blocks render as themed boxed callouts 10. **Formula renderer**: display formulas use optional matplotlib mathtext images, with styled text fallback 11. **Emoji fallback**: emoji are rendered as cached Twemoji PNGs when available, or with a local emoji font fallback
## Hard-Won Lessons
### CJK Characters Rendering as □
reportlab's `Paragraph` only uses the font in ParagraphStyle. If `fontName="Mono"` but text contains Chinese, they render as □. **Fix**: Always apply `_font_wrap()` to ALL text that might contain CJK, including code blocks.
### Code Blocks Losing Line Breaks
reportlab treats `\n` as whitespace. **Fix**: `esc_code()` converts `\n` → `<br/>` and all spaces → ` `, preserving indentation and mid-line alignment before `_font_wrap()`.
### CJK/Latin Word Wrapping
Default reportlab breaks lines only at spaces, causing ugly splits like "Claude\nCode". **Fix**: Set `wordWrap='CJK'` on body/bullet styles to allow breaks at CJK character boundaries.
### Canvas Text with CJK (Cover/Footer)
`drawString()` / `drawCentredString()` with a Latin font can't render 年/月/日 etc. **Fix**: Use `_draw_mixed()` for ALL user-content canvas text (dates, stats, disclaimers).
## Configuration Reference
Most options can also be set in top-of-file YAML-style frontmatter. Explicit CLI arguments take precedence over frontmatter values.
| Argument | Frontmatter Key | Default | Description | |----------|----------------|---------|-------------| | `--input` | — | (required) | Path to markdown file | | `--output` | — | `output.pdf` | Output PDF path | | `--title` | `title` | From first H1 | Document title for cover page | | `--subtitle` | `subtitle` | `""` | Subtitle text | | `--author` | `author` | `""` | Author name | | `--date` | `date` | Today | Date string | | `--version` | `version` | `""` | Version string for cover | | `--watermark` | `watermark` | `""` | Watermark text (empty = none) | | `--theme` | `theme` | `warm-academic` | Color theme name | | `--theme-file` | — | `""` | Custom theme JSON file path | | `--cover` | `cover` | `true` | Generate cover page | | `--toc` | `toc` | `true` | Generate table of contents | | `--page-size` | `page-size` | `A4` | Page size (A4 or Letter) | | `--frontispiece` | `frontispiece` | `""` | Full-page image after cover | | `--banner` | `banner` | `""` | Back cover banner image | | `--header-title` | `header-title` | `""` | Report title in page header | | `--footer-left` | `footer-left` | author | Brand/author in footer | | `--stats-line` | `stats-line` | `""` | Stats on cover | | `--stats-line2` | `stats-line2` | `""` | Second stats line | | `--edition-line` | `edition-line` | `""` | Edition line at cover bottom | | `--disclaimer` | `disclaimer` | `""` | Back cover disclaimer | | `--copyright` | `copyright` | `""` | Back cover copyright | | `--code-max-lines` | `code-max-lines` | `30` | Max lines per code block |
## Themes
Available: `warm-academic`, `nord-frost`, `github-light`, `solarized-light`, `paper-classic`, `ocean-breeze`.
Each theme defines: page background, ink color, accent color, faded text, border, code background, watermark tint.
## Dependencies
```bash pip install reportlab --break-system-packages # Optional formula rendering: pip install matplotlib --break-system-packages ```
Recommended Ubuntu/Debian fonts:
```bash sudo apt install fonts-dejavu-core fonts-liberation fonts-freefont-ttf fonts-noto fonts-noto-cjk fonts-noto-color-emoji ```
## Runtime context (shared)
运行前读取本 Skill 包的 `skill.yaml`,由宿主提供 `skill-runtime/v1` 上下文。字段解析顺序为:当前请求、项目上下文、个人 Preferences、品牌 Profile、通用默认值。
- 只使用 Manifest 声明的字段;Profile 保存公开品牌事实,Preferences 保存个人工作偏好。 - `required: true` 字段缺失时,按 Manifest 的问题配置向用户提出一个聚焦问题;用户明确同意后再保存回答。 - 报错提供可复制的 `context_id`、字段路径与来源,诊断内容避开秘密、完整私人路径和原始配置。
Source provenance
Decision snapshot
recent repository activity
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for lov-any2pdf, ready for a manual X post.
A practical pick for design or creative work: lov-any2pdf: Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code bl... 207 stars https://www.openagentskill.com/skills/lovstudio-lov-any2pdf?ref=x
Listing + install path for lov-any2pdf: https://www.openagentskill.com/skills/lovstudio-lov-any2pdf?ref=x Install: npx skills add lovstudio/any2pdf --skill lov-any2pdf
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to lovstudio but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
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Sandbox only
mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
61.0K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsSandbox only
Install targets
Codex install prompt
Install the "lov-any2pdf" agent skill from https://github.com/lovstudio/any2pdf/tree/main/lov-any2pdf. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code blocks, tables, blockquotes, Obsidian callouts, inline images, emoji fallback, LaTeX-style formulas, cover pages, clickable TOC, PDF bookmarks, watermarks, and page numbers. Supports multiple color themes (Configurable Academic, Nord, GitHub Light, Solarized, etc.) and is battle-tested for Chinese technical reports. Use this skill whenever the user wants to turn a .md file into a styled PDF, generate a report PDF from markdown, or create a print-ready document from markdown content — especially if CJK characters, code blocks, or tables are involved. Also trigger when the user mentions "markdown to PDF", "md2pdf", "any2pdf", "md转pdf", "报告生成", or asks for a "typeset" or "professionally formatted" PDF from markdown source. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"lovstudio-lov-any2pdf","task":"Install lov-any2pdf","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Document processing
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add lovstudio/any2pdf --skill lov-any2pdf
Maintenance
fresh
26d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
207
70/100 Quality · 73/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · The script fetches remote images via urllib, which could be a vector for SSRF or downloading malicious content if the markdown is untrusted. However, this is user-controlled and typical for such tools.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
207 GitHub stars
Repo activity
207 stars, 32 forks
Maintenance
26d since push
License
MIT
Install
npx skills add lovstudio/any2pdf --skill lov-any2pdf
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add lovstudio/any2pdf --skill lov-any2pdfDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill may drive a browser or interact with web pages.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20lov-any2pdf%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20lov-any2pdf%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/lovstudio-lov-any2pdf/install
Agent should check
Copy prompt
Task: Use lov-any2pdf in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20lov-any2pdf%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/lovstudio-lov-any2pdf/install
Install command: npx skills add lovstudio/any2pdf --skill lov-any2pdf
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/lovstudio-lov-any2pdf/install
LLM text format
/api/skills/lovstudio-lov-any2pdf/install?format=text
Find alternatives
/api/skills/search?q=lov-any2pdf&limit=3
Agent prompt
Use lov-any2pdf for this task. Review https://www.openagentskill.com/api/skills/lovstudio-lov-any2pdf/install, then install with: npx skills add lovstudio/any2pdf --skill lov-any2pdfRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/lovstudio-lov-any2pdf
LLM text
/api/registry/manifest/lovstudio-lov-any2pdf?format=text
Install alias
/api/registry/install/lovstudio-lov-any2pdf
Recommend
/api/registry/recommend?task=Use%20lov-any2pdf%20in%20an%20agent%20workflow&limit=3
Agent fit
Document processing
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Document processing
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO207 GitHub stars
Stars/forks activity
CHECK207 stars, 32 forks; issue activity unavailable in current metadata
Recent maintenance
PASS26d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Create assets
I need my agent to produce design assets, UI directions, presentations, or creative media workflows.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Design, build, test, and ship interfaces
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: lov-any2pdf description: > Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code blocks, tables, blockquotes, Obsidian callouts, inline images, emoji fallback, LaTeX-style formulas, cover pages, clickable TOC, PDF bookmarks, watermarks, and page numbers. Supports multiple color themes (Configurable Academic, Nord, GitHub Light, Solarized, etc.) and is battle-tested for Chinese technical reports. Use this skill whenever the user wants to turn a .md file into a styled PDF, generate a report PDF from markdown, or create a print-ready document from markdown content — especially if CJK characters, code blocks, or tables are involved. Also trigger when the user mentions "markdown to PDF", "md2pdf", "any2pdf", "md转pdf", "报告生成", or asks for a "typeset" or "professionally formatted" PDF from markdown source. license: MIT compatibility: > Requires Python 3.8+ and reportlab (`pip install reportlab`). Optional: matplotlib (`pip install matplotlib`) for rendered display formulas. macOS: uses Palatino, Songti SC, Menlo (pre-installed). Linux: uses DejaVu/Liberation/FreeFont/Noto, Noto CJK, Droid Sans Fallback, DejaVu Sans Mono, and Noto Emoji when available. metadata: author: contributors version: "1.1.0" tags: markdown pdf cjk reportlab typesetting ---
# 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
```bash 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 😄 ```
### Mapping User Choices to CLI Args
| Choice | CLI arg | |--------|---------| | Design style a-j | `--theme` with value from table below | | Frontispiece local | `--frontispiece <path>` | | Frontispiece AI | Generate image first, then `--frontispiece /tmp/frontispiece.png` | | Watermark text | `--watermark "文字"` | | Back cover image | `--banner <path>` | | Back cover text | `--disclaimer "声明"` and/or `--copyright "© 信息"` |
### Theme Name Mapping
| Choice | `--theme` value | Inspiration | |--------|----------------|-------------| | a) 暖学术 | `warm-academic` | Skill Publisher design system | | b) 经典论文 | `classic-thesis` | LaTeX classicthesis | | c) Tufte | `tufte` | Edward Tufte's books | | d) 期刊蓝 | `ieee-journal` | IEEE journal format | | e) 精装书 | `elegant-book` | LaTeX ElegantBook | | f) 中国红 | `chinese-red` | Chinese formal documents | | g) 水墨 | `ink-wash` | 水墨画 / ink wash painting | | h) GitHub | `github-light` | GitHub Markdown style | | i) Nord | `nord-frost` | Nord color scheme | | j) 海洋 | `ocean-breeze` | — |
### Handling AI-Generated Frontispiece
If user chose AI generation: read the document title + first paragraphs, use an image generation tool to create a themed illustration matching the chosen design style, show for approval, then pass via `--frontispiece /path/to/image.png`
## Architecture
``` Markdown → Preprocess (split merged headings) → Parse (code-fence-aware) → Story (reportlab flowables) → PDF build ```
Key components: 1. **Font system**: Palatino (Latin body), Songti SC (CJK body), Menlo (code) on macOS; auto-fallback on Linux 2. **CJK wrapper**: `_font_wrap()` wraps CJK character runs in `<font>` tags for automatic font switching 3. **Mixed text renderer**: `_draw_mixed()` handles CJK/Latin mixed text on canvas (cover, headers, footers) 4. **Code block handler**: `esc_code()` preserves indentation and line breaks in reportlab Paragraphs 5. **Smart table widths**: Proportional column widths based on content length, with 18mm minimum 6. **Bookmark system**: `ChapterMark` flowable creates PDF sidebar bookmarks + named anchors 7. **Heading preprocessor**: `_preprocess_md()` splits merged headings like `# Part## Chapter` into separate lines 8. **Image handler**: local, relative, `file://`, and remote markdown images are scaled into the body frame with fallback text on errors 9. **Callout renderer**: Obsidian-style `> [!NOTE]` blocks render as themed boxed callouts 10. **Formula renderer**: display formulas use optional matplotlib mathtext images, with styled text fallback 11. **Emoji fallback**: emoji are rendered as cached Twemoji PNGs when available, or with a local emoji font fallback
## Hard-Won Lessons
### CJK Characters Rendering as □
reportlab's `Paragraph` only uses the font in ParagraphStyle. If `fontName="Mono"` but text contains Chinese, they render as □. **Fix**: Always apply `_font_wrap()` to ALL text that might contain CJK, including code blocks.
### Code Blocks Losing Line Breaks
reportlab treats `\n` as whitespace. **Fix**: `esc_code()` converts `\n` → `<br/>` and all spaces → ` `, preserving indentation and mid-line alignment before `_font_wrap()`.
### CJK/Latin Word Wrapping
Default reportlab breaks lines only at spaces, causing ugly splits like "Claude\nCode". **Fix**: Set `wordWrap='CJK'` on body/bullet styles to allow breaks at CJK character boundaries.
### Canvas Text with CJK (Cover/Footer)
`drawString()` / `drawCentredString()` with a Latin font can't render 年/月/日 etc. **Fix**: Use `_draw_mixed()` for ALL user-content canvas text (dates, stats, disclaimers).
## Configuration Reference
Most options can also be set in top-of-file YAML-style frontmatter. Explicit CLI arguments take precedence over frontmatter values.
| Argument | Frontmatter Key | Default | Description | |----------|----------------|---------|-------------| | `--input` | — | (required) | Path to markdown file | | `--output` | — | `output.pdf` | Output PDF path | | `--title` | `title` | From first H1 | Document title for cover page | | `--subtitle` | `subtitle` | `""` | Subtitle text | | `--author` | `author` | `""` | Author name | | `--date` | `date` | Today | Date string | | `--version` | `version` | `""` | Version string for cover | | `--watermark` | `watermark` | `""` | Watermark text (empty = none) | | `--theme` | `theme` | `warm-academic` | Color theme name | | `--theme-file` | — | `""` | Custom theme JSON file path | | `--cover` | `cover` | `true` | Generate cover page | | `--toc` | `toc` | `true` | Generate table of contents | | `--page-size` | `page-size` | `A4` | Page size (A4 or Letter) | | `--frontispiece` | `frontispiece` | `""` | Full-page image after cover | | `--banner` | `banner` | `""` | Back cover banner image | | `--header-title` | `header-title` | `""` | Report title in page header | | `--footer-left` | `footer-left` | author | Brand/author in footer | | `--stats-line` | `stats-line` | `""` | Stats on cover | | `--stats-line2` | `stats-line2` | `""` | Second stats line | | `--edition-line` | `edition-line` | `""` | Edition line at cover bottom | | `--disclaimer` | `disclaimer` | `""` | Back cover disclaimer | | `--copyright` | `copyright` | `""` | Back cover copyright | | `--code-max-lines` | `code-max-lines` | `30` | Max lines per code block |
## Themes
Available: `warm-academic`, `nord-frost`, `github-light`, `solarized-light`, `paper-classic`, `ocean-breeze`.
Each theme defines: page background, ink color, accent color, faded text, border, code background, watermark tint.
## Dependencies
```bash pip install reportlab --break-system-packages # Optional formula rendering: pip install matplotlib --break-system-packages ```
Recommended Ubuntu/Debian fonts:
```bash sudo apt install fonts-dejavu-core fonts-liberation fonts-freefont-ttf fonts-noto fonts-noto-cjk fonts-noto-color-emoji ```
## Runtime context (shared)
运行前读取本 Skill 包的 `skill.yaml`,由宿主提供 `skill-runtime/v1` 上下文。字段解析顺序为:当前请求、项目上下文、个人 Preferences、品牌 Profile、通用默认值。
- 只使用 Manifest 声明的字段;Profile 保存公开品牌事实,Preferences 保存个人工作偏好。 - `required: true` 字段缺失时,按 Manifest 的问题配置向用户提出一个聚焦问题;用户明确同意后再保存回答。 - 报错提供可复制的 `context_id`、字段路径与来源,诊断内容避开秘密、完整私人路径和原始配置。
Source provenance
Decision snapshot
recent repository activity
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for lov-any2pdf, ready for a manual X post.
A practical pick for design or creative work: lov-any2pdf: Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code bl... 207 stars https://www.openagentskill.com/skills/lovstudio-lov-any2pdf?ref=x
Listing + install path for lov-any2pdf: https://www.openagentskill.com/skills/lovstudio-lov-any2pdf?ref=x Install: npx skills add lovstudio/any2pdf --skill lov-any2pdf
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
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@lovstudio
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Sandbox only
mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
61.0K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsSandbox only
Install targets
Codex install prompt
Install the "lov-any2pdf" agent skill from https://github.com/lovstudio/any2pdf/tree/main/lov-any2pdf. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code blocks, tables, blockquotes, Obsidian callouts, inline images, emoji fallback, LaTeX-style formulas, cover pages, clickable TOC, PDF bookmarks, watermarks, and page numbers. Supports multiple color themes (Configurable Academic, Nord, GitHub Light, Solarized, etc.) and is battle-tested for Chinese technical reports. Use this skill whenever the user wants to turn a .md file into a styled PDF, generate a report PDF from markdown, or create a print-ready document from markdown content — especially if CJK characters, code blocks, or tables are involved. Also trigger when the user mentions "markdown to PDF", "md2pdf", "any2pdf", "md转pdf", "报告生成", or asks for a "typeset" or "professionally formatted" PDF from markdown source. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"lovstudio-lov-any2pdf","task":"Install lov-any2pdf","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Document processing
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add lovstudio/any2pdf --skill lov-any2pdf
Maintenance
fresh
26d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
207
70/100 Quality · 73/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · The script fetches remote images via urllib, which could be a vector for SSRF or downloading malicious content if the markdown is untrusted. However, this is user-controlled and typical for such tools.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
207 GitHub stars
Repo activity
207 stars, 32 forks
Maintenance
26d since push
License
MIT
Install
npx skills add lovstudio/any2pdf --skill lov-any2pdf
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add lovstudio/any2pdf --skill lov-any2pdfDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill may drive a browser or interact with web pages.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20lov-any2pdf%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20lov-any2pdf%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/lovstudio-lov-any2pdf/install
Agent should check
Copy prompt
Task: Use lov-any2pdf in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20lov-any2pdf%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/lovstudio-lov-any2pdf/install
Install command: npx skills add lovstudio/any2pdf --skill lov-any2pdf
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/lovstudio-lov-any2pdf/install
LLM text format
/api/skills/lovstudio-lov-any2pdf/install?format=text
Find alternatives
/api/skills/search?q=lov-any2pdf&limit=3
Agent prompt
Use lov-any2pdf for this task. Review https://www.openagentskill.com/api/skills/lovstudio-lov-any2pdf/install, then install with: npx skills add lovstudio/any2pdf --skill lov-any2pdfRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/lovstudio-lov-any2pdf
LLM text
/api/registry/manifest/lovstudio-lov-any2pdf?format=text
Install alias
/api/registry/install/lovstudio-lov-any2pdf
Recommend
/api/registry/recommend?task=Use%20lov-any2pdf%20in%20an%20agent%20workflow&limit=3
Agent fit
Document processing
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Document processing
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO207 GitHub stars
Stars/forks activity
CHECK207 stars, 32 forks; issue activity unavailable in current metadata
Recent maintenance
PASS26d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Create assets
I need my agent to produce design assets, UI directions, presentations, or creative media workflows.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Design, build, test, and ship interfaces
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: lov-any2pdf description: > Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code blocks, tables, blockquotes, Obsidian callouts, inline images, emoji fallback, LaTeX-style formulas, cover pages, clickable TOC, PDF bookmarks, watermarks, and page numbers. Supports multiple color themes (Configurable Academic, Nord, GitHub Light, Solarized, etc.) and is battle-tested for Chinese technical reports. Use this skill whenever the user wants to turn a .md file into a styled PDF, generate a report PDF from markdown, or create a print-ready document from markdown content — especially if CJK characters, code blocks, or tables are involved. Also trigger when the user mentions "markdown to PDF", "md2pdf", "any2pdf", "md转pdf", "报告生成", or asks for a "typeset" or "professionally formatted" PDF from markdown source. license: MIT compatibility: > Requires Python 3.8+ and reportlab (`pip install reportlab`). Optional: matplotlib (`pip install matplotlib`) for rendered display formulas. macOS: uses Palatino, Songti SC, Menlo (pre-installed). Linux: uses DejaVu/Liberation/FreeFont/Noto, Noto CJK, Droid Sans Fallback, DejaVu Sans Mono, and Noto Emoji when available. metadata: author: contributors version: "1.1.0" tags: markdown pdf cjk reportlab typesetting ---
# 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
```bash 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 😄 ```
### Mapping User Choices to CLI Args
| Choice | CLI arg | |--------|---------| | Design style a-j | `--theme` with value from table below | | Frontispiece local | `--frontispiece <path>` | | Frontispiece AI | Generate image first, then `--frontispiece /tmp/frontispiece.png` | | Watermark text | `--watermark "文字"` | | Back cover image | `--banner <path>` | | Back cover text | `--disclaimer "声明"` and/or `--copyright "© 信息"` |
### Theme Name Mapping
| Choice | `--theme` value | Inspiration | |--------|----------------|-------------| | a) 暖学术 | `warm-academic` | Skill Publisher design system | | b) 经典论文 | `classic-thesis` | LaTeX classicthesis | | c) Tufte | `tufte` | Edward Tufte's books | | d) 期刊蓝 | `ieee-journal` | IEEE journal format | | e) 精装书 | `elegant-book` | LaTeX ElegantBook | | f) 中国红 | `chinese-red` | Chinese formal documents | | g) 水墨 | `ink-wash` | 水墨画 / ink wash painting | | h) GitHub | `github-light` | GitHub Markdown style | | i) Nord | `nord-frost` | Nord color scheme | | j) 海洋 | `ocean-breeze` | — |
### Handling AI-Generated Frontispiece
If user chose AI generation: read the document title + first paragraphs, use an image generation tool to create a themed illustration matching the chosen design style, show for approval, then pass via `--frontispiece /path/to/image.png`
## Architecture
``` Markdown → Preprocess (split merged headings) → Parse (code-fence-aware) → Story (reportlab flowables) → PDF build ```
Key components: 1. **Font system**: Palatino (Latin body), Songti SC (CJK body), Menlo (code) on macOS; auto-fallback on Linux 2. **CJK wrapper**: `_font_wrap()` wraps CJK character runs in `<font>` tags for automatic font switching 3. **Mixed text renderer**: `_draw_mixed()` handles CJK/Latin mixed text on canvas (cover, headers, footers) 4. **Code block handler**: `esc_code()` preserves indentation and line breaks in reportlab Paragraphs 5. **Smart table widths**: Proportional column widths based on content length, with 18mm minimum 6. **Bookmark system**: `ChapterMark` flowable creates PDF sidebar bookmarks + named anchors 7. **Heading preprocessor**: `_preprocess_md()` splits merged headings like `# Part## Chapter` into separate lines 8. **Image handler**: local, relative, `file://`, and remote markdown images are scaled into the body frame with fallback text on errors 9. **Callout renderer**: Obsidian-style `> [!NOTE]` blocks render as themed boxed callouts 10. **Formula renderer**: display formulas use optional matplotlib mathtext images, with styled text fallback 11. **Emoji fallback**: emoji are rendered as cached Twemoji PNGs when available, or with a local emoji font fallback
## Hard-Won Lessons
### CJK Characters Rendering as □
reportlab's `Paragraph` only uses the font in ParagraphStyle. If `fontName="Mono"` but text contains Chinese, they render as □. **Fix**: Always apply `_font_wrap()` to ALL text that might contain CJK, including code blocks.
### Code Blocks Losing Line Breaks
reportlab treats `\n` as whitespace. **Fix**: `esc_code()` converts `\n` → `<br/>` and all spaces → ` `, preserving indentation and mid-line alignment before `_font_wrap()`.
### CJK/Latin Word Wrapping
Default reportlab breaks lines only at spaces, causing ugly splits like "Claude\nCode". **Fix**: Set `wordWrap='CJK'` on body/bullet styles to allow breaks at CJK character boundaries.
### Canvas Text with CJK (Cover/Footer)
`drawString()` / `drawCentredString()` with a Latin font can't render 年/月/日 etc. **Fix**: Use `_draw_mixed()` for ALL user-content canvas text (dates, stats, disclaimers).
## Configuration Reference
Most options can also be set in top-of-file YAML-style frontmatter. Explicit CLI arguments take precedence over frontmatter values.
| Argument | Frontmatter Key | Default | Description | |----------|----------------|---------|-------------| | `--input` | — | (required) | Path to markdown file | | `--output` | — | `output.pdf` | Output PDF path | | `--title` | `title` | From first H1 | Document title for cover page | | `--subtitle` | `subtitle` | `""` | Subtitle text | | `--author` | `author` | `""` | Author name | | `--date` | `date` | Today | Date string | | `--version` | `version` | `""` | Version string for cover | | `--watermark` | `watermark` | `""` | Watermark text (empty = none) | | `--theme` | `theme` | `warm-academic` | Color theme name | | `--theme-file` | — | `""` | Custom theme JSON file path | | `--cover` | `cover` | `true` | Generate cover page | | `--toc` | `toc` | `true` | Generate table of contents | | `--page-size` | `page-size` | `A4` | Page size (A4 or Letter) | | `--frontispiece` | `frontispiece` | `""` | Full-page image after cover | | `--banner` | `banner` | `""` | Back cover banner image | | `--header-title` | `header-title` | `""` | Report title in page header | | `--footer-left` | `footer-left` | author | Brand/author in footer | | `--stats-line` | `stats-line` | `""` | Stats on cover | | `--stats-line2` | `stats-line2` | `""` | Second stats line | | `--edition-line` | `edition-line` | `""` | Edition line at cover bottom | | `--disclaimer` | `disclaimer` | `""` | Back cover disclaimer | | `--copyright` | `copyright` | `""` | Back cover copyright | | `--code-max-lines` | `code-max-lines` | `30` | Max lines per code block |
## Themes
Available: `warm-academic`, `nord-frost`, `github-light`, `solarized-light`, `paper-classic`, `ocean-breeze`.
Each theme defines: page background, ink color, accent color, faded text, border, code background, watermark tint.
## Dependencies
```bash pip install reportlab --break-system-packages # Optional formula rendering: pip install matplotlib --break-system-packages ```
Recommended Ubuntu/Debian fonts:
```bash sudo apt install fonts-dejavu-core fonts-liberation fonts-freefont-ttf fonts-noto fonts-noto-cjk fonts-noto-color-emoji ```
## Runtime context (shared)
运行前读取本 Skill 包的 `skill.yaml`,由宿主提供 `skill-runtime/v1` 上下文。字段解析顺序为:当前请求、项目上下文、个人 Preferences、品牌 Profile、通用默认值。
- 只使用 Manifest 声明的字段;Profile 保存公开品牌事实,Preferences 保存个人工作偏好。 - `required: true` 字段缺失时,按 Manifest 的问题配置向用户提出一个聚焦问题;用户明确同意后再保存回答。 - 报错提供可复制的 `context_id`、字段路径与来源,诊断内容避开秘密、完整私人路径和原始配置。
Source provenance
Decision snapshot
recent repository activity
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for lov-any2pdf, ready for a manual X post.
A practical pick for design or creative work: lov-any2pdf: Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code bl... 207 stars https://www.openagentskill.com/skills/lovstudio-lov-any2pdf?ref=x
Listing + install path for lov-any2pdf: https://www.openagentskill.com/skills/lovstudio-lov-any2pdf?ref=x Install: npx skills add lovstudio/any2pdf --skill lov-any2pdf
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@lovstudio
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mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
61.0K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsSandbox only
Install targets
Codex install prompt
Install the "lov-any2pdf" agent skill from https://github.com/lovstudio/any2pdf/tree/main/lov-any2pdf. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code blocks, tables, blockquotes, Obsidian callouts, inline images, emoji fallback, LaTeX-style formulas, cover pages, clickable TOC, PDF bookmarks, watermarks, and page numbers. Supports multiple color themes (Configurable Academic, Nord, GitHub Light, Solarized, etc.) and is battle-tested for Chinese technical reports. Use this skill whenever the user wants to turn a .md file into a styled PDF, generate a report PDF from markdown, or create a print-ready document from markdown content — especially if CJK characters, code blocks, or tables are involved. Also trigger when the user mentions "markdown to PDF", "md2pdf", "any2pdf", "md转pdf", "报告生成", or asks for a "typeset" or "professionally formatted" PDF from markdown source. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"lovstudio-lov-any2pdf","task":"Install lov-any2pdf","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Document processing
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add lovstudio/any2pdf --skill lov-any2pdf
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fresh
26d since push
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Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
207
70/100 Quality · 73/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · The script fetches remote images via urllib, which could be a vector for SSRF or downloading malicious content if the markdown is untrusted. However, this is user-controlled and typical for such tools.
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Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
207 GitHub stars
Repo activity
207 stars, 32 forks
Maintenance
26d since push
License
MIT
Install
npx skills add lovstudio/any2pdf --skill lov-any2pdf
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Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
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Install command
npx skills add lovstudio/any2pdf --skill lov-any2pdfDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
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38.4K Stars
npx skills add Imbad0202/academic-research-skills
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28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill may drive a browser or interact with web pages.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
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The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20lov-any2pdf%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20lov-any2pdf%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
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Copy prompt
Task: Use lov-any2pdf in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20lov-any2pdf%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/lovstudio-lov-any2pdf/install
Install command: npx skills add lovstudio/any2pdf --skill lov-any2pdf
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/lovstudio-lov-any2pdf/install
LLM text format
/api/skills/lovstudio-lov-any2pdf/install?format=text
Find alternatives
/api/skills/search?q=lov-any2pdf&limit=3
Agent prompt
Use lov-any2pdf for this task. Review https://www.openagentskill.com/api/skills/lovstudio-lov-any2pdf/install, then install with: npx skills add lovstudio/any2pdf --skill lov-any2pdfRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/lovstudio-lov-any2pdf
LLM text
/api/registry/manifest/lovstudio-lov-any2pdf?format=text
Install alias
/api/registry/install/lovstudio-lov-any2pdf
Recommend
/api/registry/recommend?task=Use%20lov-any2pdf%20in%20an%20agent%20workflow&limit=3
Agent fit
Document processing
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Document processing
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO207 GitHub stars
Stars/forks activity
CHECK207 stars, 32 forks; issue activity unavailable in current metadata
Recent maintenance
PASS26d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Parse messy files
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Create assets
I need my agent to produce design assets, UI directions, presentations, or creative media workflows.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Design, build, test, and ship interfaces
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: lov-any2pdf description: > Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code blocks, tables, blockquotes, Obsidian callouts, inline images, emoji fallback, LaTeX-style formulas, cover pages, clickable TOC, PDF bookmarks, watermarks, and page numbers. Supports multiple color themes (Configurable Academic, Nord, GitHub Light, Solarized, etc.) and is battle-tested for Chinese technical reports. Use this skill whenever the user wants to turn a .md file into a styled PDF, generate a report PDF from markdown, or create a print-ready document from markdown content — especially if CJK characters, code blocks, or tables are involved. Also trigger when the user mentions "markdown to PDF", "md2pdf", "any2pdf", "md转pdf", "报告生成", or asks for a "typeset" or "professionally formatted" PDF from markdown source. license: MIT compatibility: > Requires Python 3.8+ and reportlab (`pip install reportlab`). Optional: matplotlib (`pip install matplotlib`) for rendered display formulas. macOS: uses Palatino, Songti SC, Menlo (pre-installed). Linux: uses DejaVu/Liberation/FreeFont/Noto, Noto CJK, Droid Sans Fallback, DejaVu Sans Mono, and Noto Emoji when available. metadata: author: contributors version: "1.1.0" tags: markdown pdf cjk reportlab typesetting ---
# 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
```bash 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 😄 ```
### Mapping User Choices to CLI Args
| Choice | CLI arg | |--------|---------| | Design style a-j | `--theme` with value from table below | | Frontispiece local | `--frontispiece <path>` | | Frontispiece AI | Generate image first, then `--frontispiece /tmp/frontispiece.png` | | Watermark text | `--watermark "文字"` | | Back cover image | `--banner <path>` | | Back cover text | `--disclaimer "声明"` and/or `--copyright "© 信息"` |
### Theme Name Mapping
| Choice | `--theme` value | Inspiration | |--------|----------------|-------------| | a) 暖学术 | `warm-academic` | Skill Publisher design system | | b) 经典论文 | `classic-thesis` | LaTeX classicthesis | | c) Tufte | `tufte` | Edward Tufte's books | | d) 期刊蓝 | `ieee-journal` | IEEE journal format | | e) 精装书 | `elegant-book` | LaTeX ElegantBook | | f) 中国红 | `chinese-red` | Chinese formal documents | | g) 水墨 | `ink-wash` | 水墨画 / ink wash painting | | h) GitHub | `github-light` | GitHub Markdown style | | i) Nord | `nord-frost` | Nord color scheme | | j) 海洋 | `ocean-breeze` | — |
### Handling AI-Generated Frontispiece
If user chose AI generation: read the document title + first paragraphs, use an image generation tool to create a themed illustration matching the chosen design style, show for approval, then pass via `--frontispiece /path/to/image.png`
## Architecture
``` Markdown → Preprocess (split merged headings) → Parse (code-fence-aware) → Story (reportlab flowables) → PDF build ```
Key components: 1. **Font system**: Palatino (Latin body), Songti SC (CJK body), Menlo (code) on macOS; auto-fallback on Linux 2. **CJK wrapper**: `_font_wrap()` wraps CJK character runs in `<font>` tags for automatic font switching 3. **Mixed text renderer**: `_draw_mixed()` handles CJK/Latin mixed text on canvas (cover, headers, footers) 4. **Code block handler**: `esc_code()` preserves indentation and line breaks in reportlab Paragraphs 5. **Smart table widths**: Proportional column widths based on content length, with 18mm minimum 6. **Bookmark system**: `ChapterMark` flowable creates PDF sidebar bookmarks + named anchors 7. **Heading preprocessor**: `_preprocess_md()` splits merged headings like `# Part## Chapter` into separate lines 8. **Image handler**: local, relative, `file://`, and remote markdown images are scaled into the body frame with fallback text on errors 9. **Callout renderer**: Obsidian-style `> [!NOTE]` blocks render as themed boxed callouts 10. **Formula renderer**: display formulas use optional matplotlib mathtext images, with styled text fallback 11. **Emoji fallback**: emoji are rendered as cached Twemoji PNGs when available, or with a local emoji font fallback
## Hard-Won Lessons
### CJK Characters Rendering as □
reportlab's `Paragraph` only uses the font in ParagraphStyle. If `fontName="Mono"` but text contains Chinese, they render as □. **Fix**: Always apply `_font_wrap()` to ALL text that might contain CJK, including code blocks.
### Code Blocks Losing Line Breaks
reportlab treats `\n` as whitespace. **Fix**: `esc_code()` converts `\n` → `<br/>` and all spaces → ` `, preserving indentation and mid-line alignment before `_font_wrap()`.
### CJK/Latin Word Wrapping
Default reportlab breaks lines only at spaces, causing ugly splits like "Claude\nCode". **Fix**: Set `wordWrap='CJK'` on body/bullet styles to allow breaks at CJK character boundaries.
### Canvas Text with CJK (Cover/Footer)
`drawString()` / `drawCentredString()` with a Latin font can't render 年/月/日 etc. **Fix**: Use `_draw_mixed()` for ALL user-content canvas text (dates, stats, disclaimers).
## Configuration Reference
Most options can also be set in top-of-file YAML-style frontmatter. Explicit CLI arguments take precedence over frontmatter values.
| Argument | Frontmatter Key | Default | Description | |----------|----------------|---------|-------------| | `--input` | — | (required) | Path to markdown file | | `--output` | — | `output.pdf` | Output PDF path | | `--title` | `title` | From first H1 | Document title for cover page | | `--subtitle` | `subtitle` | `""` | Subtitle text | | `--author` | `author` | `""` | Author name | | `--date` | `date` | Today | Date string | | `--version` | `version` | `""` | Version string for cover | | `--watermark` | `watermark` | `""` | Watermark text (empty = none) | | `--theme` | `theme` | `warm-academic` | Color theme name | | `--theme-file` | — | `""` | Custom theme JSON file path | | `--cover` | `cover` | `true` | Generate cover page | | `--toc` | `toc` | `true` | Generate table of contents | | `--page-size` | `page-size` | `A4` | Page size (A4 or Letter) | | `--frontispiece` | `frontispiece` | `""` | Full-page image after cover | | `--banner` | `banner` | `""` | Back cover banner image | | `--header-title` | `header-title` | `""` | Report title in page header | | `--footer-left` | `footer-left` | author | Brand/author in footer | | `--stats-line` | `stats-line` | `""` | Stats on cover | | `--stats-line2` | `stats-line2` | `""` | Second stats line | | `--edition-line` | `edition-line` | `""` | Edition line at cover bottom | | `--disclaimer` | `disclaimer` | `""` | Back cover disclaimer | | `--copyright` | `copyright` | `""` | Back cover copyright | | `--code-max-lines` | `code-max-lines` | `30` | Max lines per code block |
## Themes
Available: `warm-academic`, `nord-frost`, `github-light`, `solarized-light`, `paper-classic`, `ocean-breeze`.
Each theme defines: page background, ink color, accent color, faded text, border, code background, watermark tint.
## Dependencies
```bash pip install reportlab --break-system-packages # Optional formula rendering: pip install matplotlib --break-system-packages ```
Recommended Ubuntu/Debian fonts:
```bash sudo apt install fonts-dejavu-core fonts-liberation fonts-freefont-ttf fonts-noto fonts-noto-cjk fonts-noto-color-emoji ```
## Runtime context (shared)
运行前读取本 Skill 包的 `skill.yaml`,由宿主提供 `skill-runtime/v1` 上下文。字段解析顺序为:当前请求、项目上下文、个人 Preferences、品牌 Profile、通用默认值。
- 只使用 Manifest 声明的字段;Profile 保存公开品牌事实,Preferences 保存个人工作偏好。 - `required: true` 字段缺失时,按 Manifest 的问题配置向用户提出一个聚焦问题;用户明确同意后再保存回答。 - 报错提供可复制的 `context_id`、字段路径与来源,诊断内容避开秘密、完整私人路径和原始配置。
Source provenance
Decision snapshot
recent repository activity
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for lov-any2pdf, ready for a manual X post.
A practical pick for design or creative work: lov-any2pdf: Convert Markdown documents to professionally typeset PDF files with reportlab. Handles CJK/Latin mixed text, fenced code bl... 207 stars https://www.openagentskill.com/skills/lovstudio-lov-any2pdf?ref=x
Listing + install path for lov-any2pdf: https://www.openagentskill.com/skills/lovstudio-lov-any2pdf?ref=x Install: npx skills add lovstudio/any2pdf --skill lov-any2pdf
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mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
61.0K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsPermission surface
shell or command execution, filesystem or document access
Agent outcomes
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Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
shell or command execution, filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
shell or command execution, filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
shell or command execution, filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness