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Computer Vision Helper

Checked
jmsktm·vlatest·ai-ml

This AI helps analyze images by identifying objects and features, boosting productivity for tasks needing visual understanding.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Installs under a different name. Its SKILL.md names it Computer Vision Helper, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add jmsktm/claude-settings --skill "Computer Vision Helper" -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

jmsktm

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 jmsktm/claude-settings at c113b0d7e1.

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

Commit
c113b0d7e1
Manifest
skills/computer-vision-helper/SKILL.md
Scanned
1 file, 302 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 assists with computer vision tasks, enabling AI agents to analyze and understand images. It can identify objects within an image, describe visual scenes in detail, and potentially extract information from visual data. The tool aims to enhance agent capabilities for applications requiring image understanding.

When to use it

  • Image analysis: When you need the AI agent to describe what's present in a photograph or screenshot.
  • Object identification: To have the agent identify specific objects within an image, such as cars, people, or furniture.
  • Scene understanding: For scenarios requiring a detailed description of a visual scene, like identifying landmarks or assessing environmental conditions.
  • Visual data extraction: When you need to extract particular information from images, for example, reading text on signs or counting items.

Key capabilities

  • Object identification
  • Scene description
  • Image analysis
  • Visual data extraction

Example prompts

  • "Describe the contents of this image." (followed by an image upload)
  • "What objects can you identify in this photo?" (followed by an image upload)
  • “Analyze this screenshot and tell me what’s happening.” (followed by an image upload)

Tips & gotchas

The skill's effectiveness depends on the quality and clarity of the input images. Complex or obscured scenes may lead to less accurate results.