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Swift Lang

Checked
makgunay·vlatest·frontend·MIT

Generates clean, efficient SwiftUI code snippets from natural language descriptions, accelerating frontend development workflows.

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 makgunay/claude-swift-skills --skill swift-lang -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.

Commit
1c20cb3232
Manifest
swift-lang/SKILL.md
Scanned
3 files, 577 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 understand and generate Swift code. It allows users to request assistance with tasks ranging from simple syntax questions to more complex coding problems, leveraging the power of a large language model's understanding of the Swift programming language. The agent can also be used for generating basic Swift code snippets based on user requests.

When to use it

  • Swift Coding Assistance: Get help debugging or understanding existing Swift code.
  • Code Generation: Request simple Swift code snippets for common tasks.
  • Learning Swift: Ask questions about Swift syntax and concepts.
  • Project Prototyping: Quickly generate basic Swift code to test ideas.

Key capabilities

  • Swift Code Understanding
  • Swift Code Generation
  • Syntax Assistance
  • Conceptual Explanations

Example prompts

  • "Can you explain the difference between struct and class in Swift?"
  • "Generate a simple Swift function to calculate the factorial of a number."
  • "I'm getting an error 'use of unresolved identifier'. What could be causing this in my Swift code?"

Tips & gotchas

The agent’s ability is limited by its training data; it may struggle with very complex or niche Swift libraries. Providing context, such as the specific version of Swift being used, can improve results.