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Machine Learning

Checked
pluginagentmarketplace·vlatest·ai-ml

Machine Learning analyzes data to identify patterns & predict outcomes, boosting insights and automating decision-making processes.

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 Machine Learning, 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 pluginagentmarketplace/custom-plugin-python --skill "Machine Learning" -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

pluginagentmarketplace

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 pluginagentmarketplace/custom-plugin-python at 4415517654.

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

Commit
4415517654
Manifest
skills/machine-learning/SKILL.md
Scanned
6 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

The Machine Learning skill enables AI agents to discover and install specialized machine learning capabilities via the Custom Plugin Python marketplace. It facilitates the integration of advanced data analysis models directly into agent workflows for enhanced decision-making.

When to use it

  • You need an agent to analyze complex datasets or identify patterns in historical data.
  • Your workflow requires dynamic model selection based on specific input parameters.
  • You are building a system that needs predictive analytics or classification features without manual coding.
  • You want to extend agent functionality by installing pre-built Python-based ML libraries.

Key capabilities

  • Discovery and installation of machine learning skills from the Custom Plugin Python registry.
  • Integration of third-party ML models into autonomous agent environments.
  • Execution of data-driven tasks through plugin-based architecture.

Example prompts

  • "Install a sentiment analysis model from the marketplace to evaluate customer feedback."
  • "Configure an agent to use a custom regression plugin for predicting sales trends."
  • "Deploy a classification skill to categorize incoming support tickets automatically."

Tips & gotchas

Ensure your environment supports Python execution, as this skill relies on the Custom Plugin Python infrastructure. Verify that installed models are compatible with your specific data formats before running production workflows.