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Liquid Glass

Checked
makgunay·vlatest·writing·MIT

Liquid Glass generates smooth, flowing text mimicking natural language, enhancing creative writing and dialogue realism.

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 makgunay/claude-swift-skills --skill liquid-glass -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

makgunay

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 makgunay/claude-swift-skills at 1c20cb3232.

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

Scanned
5 files, 472 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 liquid-glass skill enhances AI agent responses with a polished, professional tone. It refines language to be more articulate and impactful, ensuring clarity and precision in communication. This skill aims to elevate the overall quality of written output by smoothing rough edges and creating a more refined presentation.

When to use it

  • Generating marketing materials that require a sophisticated brand voice.
  • Drafting formal emails or letters needing a professional touch.
  • Creating reports or presentations where clear, concise language is crucial.
  • Refining creative writing pieces for publication or public consumption.

Key capabilities

  • Polished Language
  • Professional Tone
  • Articulate Communication
  • Precise Writing

Example prompts

  • "Please rewrite this paragraph in a more professional tone: [paragraph text]"
  • "Can you refine the language of this email to be more articulate? [email text]"
  • "Make this report sound more polished and impactful. [report text]"

Tips & gotchas

The skill works best when applied to existing text; it's a refinement tool, not a content generator. While it improves clarity, it may subtly alter the original meaning, so always review the output carefully.