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Image Processing

Checked
jezweb·vlatest·video-media·MIT

Analyzes video frames to identify objects, track motion, and extract data like license plates or text.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add jezweb/claude-skills --skill image-processing -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

jezweb

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned jezweb/claude-skills at 1260fa7439.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
1260fa7439
Manifest
plugins/design-assets/skills/image-processing/SKILL.md
Scanned
1 file, 194 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill enables AI agents to perform a variety of image processing tasks using Python and the Pillow library. It supports resizing, cropping, format conversion (PNG, WebP, JPG), compression, thumbnail generation, and Open Graph card creation. If Pillow is unavailable, it falls back to alternative tools like sips (macOS), sharp (Node.js), or ffmpeg.

When to use it

  • To resize images for website hero sections (e.g., "resize hero.png --width 1920").
  • When converting image formats, such as changing a PNG logo to WebP ("convert logo.png --format webp").
  • For optimizing images by reducing file size while maintaining quality ("optimise hero.jpg --quality 85 --max-width 1920").
  • To generate Open Graph cards for social media sharing ("og-card -o og.png --title "My App" --subtitle "Built for speed"").
  • For batch processing a directory of images into a different format ("batch ./images --action convert --format webp -o ./optimised").

Key capabilities

  • Image Resizing: Adjusts image dimensions.
  • Format Conversion: Converts between PNG, WebP, and JPG formats.
  • Optimization: Compresses images for smaller file sizes.
  • Thumbnail Generation: Creates smaller versions of images.
  • Open Graph Card Creation: Generates images with title and subtitle for social sharing.
  • Batch Processing: Applies operations to multiple images at once.
  • Fallback Options: Uses sips, sharp, or ffmpeg if Pillow is not installed.

Example prompts

  • "Resize this image to a width of 1920 pixels."
  • "Convert this PNG logo to WebP format."
  • "Create an Open Graph card for my app with the title 'My App' and subtitle 'Built for speed'."
  • "Optimize all images in this folder, limiting their maximum width to 1920 pixels."

Tips & gotchas

  • Prerequisites: Pillow is required for full functionality. Install it using pip install Pillow.
  • img-process vs. Custom Scripts: Use the img-process command line tool for standard operations. For more complex tasks (compositing, watermarks), generate a custom Python script.
  • Format-Specific Quality Settings: WebP images use a quality setting of 85, JPG uses 90, and PNG is optimized by default.