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Programming Swift

Checked
nonameplum·vlatest·frontend

Generates Swift code snippets for UI elements, data models, and basic functionality in iOS applications.

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 nonameplum/agent-skills --skill programming-swift -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

nonameplum

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 nonameplum/agent-skills at 26f9ebd26d.

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

Commit
26f9ebd26d
Manifest
programming-swift/SKILL.md
Scanned
44 files, 36,900 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 generate and understand Swift code. It allows agents to write basic iOS applications, manipulate data structures like arrays and dictionaries, and implement common algorithms in a functional Swift style. The agent can also debug existing Swift code snippets.

When to use it

  • iOS App Development: Generate initial drafts of simple iOS apps or components.
  • Code Debugging: Identify and fix errors within existing Swift code.
  • Swift Algorithm Implementation: Translate algorithmic descriptions into functional Swift code.
  • Data Structure Manipulation: Create, modify, and query data stored in Swift arrays and dictionaries.

Key capabilities

  • Swift code generation
  • Code debugging
  • Array manipulation
  • Dictionary manipulation
  • Algorithm implementation

Example prompts

  • "Write a Swift function to calculate the factorial of a given number."
  • "Debug this Swift code: //code snippet"
  • "Create an iOS app that displays a list of items from a JSON file."

Tips & gotchas

The agent's proficiency is dependent on the complexity of the requested task. For complex applications, iterative refinement and human oversight are recommended.