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Ruby Llm

Checked
faqndo97·vlatest·ai-ml

Provides LLMs guidance and assistance for building AI and machine learning 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 faqndo97/ai-skills --skill ruby-llm -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

faqndo97

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 faqndo97/ai-skills at ecebb45531.

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

Commit
ecebb45531
Manifest
ruby-llm/SKILL.md
Scanned
19 files, 3,565 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 ruby-llm skill allows AI agents to execute Ruby code snippets and leverage LLMs within those scripts. It enables complex logic, data manipulation, and external API calls that are difficult or impossible with standard prompt engineering alone. This provides a powerful way to extend the capabilities of an agent beyond simple text generation.

When to use it

  • Data Transformation: When you need to process structured data (e.g., CSV files) and perform calculations before generating output.
  • API Integration: To interact with external services or APIs that require Ruby-specific libraries or authentication methods.
  • Complex Logic: When the reasoning required goes beyond simple instructions, needing conditional logic or iterative processes best implemented in code.
  • Dynamic Content Generation: To generate content based on real-time data fetched from external sources via Ruby scripts.

Key capabilities

  • Ruby Code Execution: Executes provided Ruby code snippets.
  • LLM Integration: Allows the use of LLMs within Ruby code for enhanced functionality.
  • External API Calls: Enables interaction with external services and APIs through Ruby libraries.
  • Data Manipulation: Provides tools to process and manipulate data within Ruby scripts.

Example prompts

  • "Write a ruby script to fetch today's weather from the OpenWeatherMap API and then generate a summary."
  • "Can you use ruby to read this CSV file, calculate the average of column 'price', and output the result?"
  • "Generate a Ruby script that uses an LLM to translate this paragraph into French, then prints the translated text."

Tips & gotchas

  • Requires a working Ruby environment with necessary libraries installed. Ensure your agent has access to these dependencies.