PDF 长图 · PDF Scroll
SkillFiles & storageConvert PDF files to a single vertically concatenated PNG image using macOS native CoreGraphics. Each page is rendered at 2x scale and stitched top-to-bottom. ~20x faster than pdftoppm+ImageMagick, zero external dependencies on macOS. Trigger when the user mentions "pdf to png", "pdf转png", "PDF转图片", "pdf拼接", "pdf截图", "convert pdf to image", or wants to turn a multi-page PDF into one long PNG.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the PDF 长图 · PDF Scroll skill
What this skill tells your AI
The instructions your AI receives, as published by lovstudio/skills in skills/pdf2png/SKILL.md and read by ahel’s review.
Convert multi-page PDF files into a single tall PNG image. All pages are rendered at 2x scale (Retina quality) and stitched vertically. Uses macOS CoreGraphics directly — no pdftoppm, no ImageMagick, no Ghostscript.
When to Use
- User wants to convert a PDF to a single PNG image
- User needs a long screenshot-style image of a PDF
- User wants to share PDF content as an image (WeChat, social media, etc.)
Workflow
Step 1: Identify PDF files
Locate the PDF file(s) the user wants to convert. If multiple PDFs or output
location choices are ambiguous, use AskUserQuestion to confirm the path(s)
before running conversion.
Step 2: Execute
bash lov-pdf2png/scripts/pdf2png.sh /path/to/file.pdf
Output: /path/to/file.png (same directory, same name, .png extension).
For multiple files:
bash lov-pdf2png/scripts/pdf2png.sh file1.pdf file2.pdf file3.pdf
Step 3: Verify
Check the output file exists and report its size.
CLI Reference
| Argument | Description |
|---|---|
file1.pdf [file2.pdf ...] | One or more PDF files to convert |
Output is always <input>.png in the same directory as the input file.
Finder Quick Action
This skill can also be installed as a macOS Finder Quick Action for right-click conversion. See skill-publisher/mac-pdf2png for the Automator workflow.
Dependencies
pip install pyobjc-framework-Quartz --break-system-packages
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。
通用反馈闭环
用户在 Skill 驱动任务中提出修改意见时,继续当前产物前必须执行:
- 先判断意见是
task-specific(仅本次)还是reusable(可跨任务复用)。 task-specific只修改当前任务,不改 Skill。reusable先确定作用域:领域规则先更新对应 canonical Skill;适用于所有 Skill 的规则先更新共享规范。- 完成规则更新、版本、lint 与分发核验后,再把修改应用到当前任务。
reusable修改会使此前的“确认”“继续”“发吧”失效;完成当前产物修改和回读后必须停下,等待用户下一步指示,不自动进入发布、提交或其他外部写入。
Signals
- GitHub stars
- 66
- Forks
- 17
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
lov-pdf2png- Source
- github.com/lovstudio/skills