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Swift Observation

Checked
nonameplum·vlatest·frontend

Quickly identifies and extracts key UI elements and data from webpages for automated testing and analysis.

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 swift-observation -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
swift-observation/SKILL.md
Scanned
9 files, 1,991 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 swift-observation skill allows an AI agent to quickly and efficiently analyze visual data. It can identify key elements within images, extract relevant information, and provide concise summaries of observed details. This capability is particularly useful for tasks requiring rapid assessment of visual content.

When to use it

  • Image Categorization: Automatically classify images based on their contents (e.g., "landscape," "portrait," "product").
  • Object Detection in Screenshots: Identify and label objects within a screenshot, such as buttons or text fields.
  • Visual Data Summarization: Provide a brief description of the key elements present in an image for accessibility purposes.
  • Content Moderation Assistance: Flag potentially inappropriate content based on visual cues.

Key capabilities

  • Image analysis
  • Object identification
  • Concise summarization
  • Screenshot assessment

Example prompts

  • "Describe what's visible in this screenshot."
  • "What objects can you identify in this image?"
  • "Categorize this image and provide a short description."

Tips & gotchas

The skill requires access to an image URL or file. Performance may vary depending on the complexity of the image and the number of objects present.