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Baoyu Compress Image

Checked
jimliu·vlatest·video-media·MIT

Compress images using advanced AI techniques for smaller file sizes while preserving visual quality.

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 jimliu/baoyu-skills --skill baoyu-compress-image -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

jimliu

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 jimliu/baoyu-skills at 1567581c26.

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

Commit
1567581c26
Manifest
skills/baoyu-compress-image/SKILL.md
Scanned
2 files, 394 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

The baoyu-compress-image skill allows AI agents to compress image files efficiently while maintaining visual quality. It supports various image formats and provides options to adjust compression levels, ensuring optimal file size reduction without significant loss of detail.

When to use it

  • Reducing the file size of images before uploading them to a website or social media platform.
  • Preparing high-resolution photos for email sharing by making them more lightweight.
  • Optimizing image assets for mobile applications where storage space is limited.

Key capabilities

  • Compression of common image formats (e.g., JPEG, PNG).
  • Adjustable compression levels to balance quality and file size.
  • Batch processing support for multiple images at once.

Example prompts

  • "Compress this photo to 80% quality."
  • "Reduce the file size of these five images without losing clarity."
  • "Optimize this image for web use."

Tips & gotchas

  • Ensure that the original image is not already compressed, as further compression may yield minimal results.
  • Be cautious with extreme compression settings, which can lead to visible quality degradation in the final output.