Skillquality 0.48

lovstudio-pdf2png

Convert 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",

Price
free
Protocol
skill
Verified
no

What it does

pdf2png — PDF to Vertically Concatenated PNG

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 lovstudio-pdf2png/scripts/pdf2png.sh /path/to/file.pdf

Output: /path/to/file.png (same directory, same name, .png extension).

For multiple files:

bash lovstudio-pdf2png/scripts/pdf2png.sh file1.pdf file2.pdf file3.pdf

Step 3: Verify

Check the output file exists and report its size.

CLI Reference

ArgumentDescription
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 lovstudio/mac-pdf2png for the Automator workflow.

Dependencies

pip install pyobjc-framework-Quartz --break-system-packages

Capabilities

skillsource-lovstudioskill-pdf2pngtopic-agent-skillstopic-ai-coding-assistanttopic-cjktopic-claude-codetopic-cursortopic-gemini-clitopic-markdown-to-docxtopic-markdown-to-pdf

Install

Installnpx skills add lovstudio/skills
Transportskills-sh
Protocolskill

Quality

0.48/ 1.00

deterministic score 0.48 from registry signals: · indexed on github topic:agent-skills · 54 github stars · SKILL.md body (1,551 chars)

Provenance

Indexed fromgithub
Enriched2026-05-18 18:57:49Z · deterministic:skill-github:v1 · v1
First seen2026-04-18
Last seen2026-05-18

Agent access