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Ray So Code Snippet

Checked
intellectronica·vlatest·backend·CC0-1.0

Ray So Code Snippet generates concise code snippets for various programming languages, boosting developer productivity and accelerating coding tasks.

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 intellectronica/agent-skills --skill ray-so-code-snippet -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

intellectronica

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

    Only contacts known or declared hosts: raw.githubusercontent.com.

    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.

    Hosts contacted

    raw.githubusercontent.comsource host

  • 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 intellectronica/agent-skills at 9b0e00ad1b.

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

Commit
9b0e00ad1b
Manifest
skills/ray-so-code-snippet/SKILL.md
Scanned
1 file, 290 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 ray-so-code-snippet skill allows an AI agent to generate and execute Python code snippets directly within a Ray environment. It can be used for tasks like data processing, model training, or running simulations that benefit from distributed computing capabilities. The skill leverages the power of Ray's parallel execution framework to accelerate these operations.

When to use it

  • Distributed Data Processing: When you need to process large datasets and want to leverage multiple cores or machines for faster performance.
  • Ray Program Debugging: Quickly test and debug small pieces of Ray code without needing a full development environment.
  • Model Training Experiments: Run short, isolated training experiments with different hyperparameters in parallel.
  • Simulation Execution: Execute simulations that require distributed resources to handle complex calculations or large-scale environments.

Key capabilities

  • Python Code Generation: Generates executable Python code snippets.
  • Ray Environment Integration: Executes generated code within a Ray cluster.
  • Parallel Execution: Leverages Ray's parallel processing capabilities for faster execution.
  • Snippet Management: Handles the creation, submission, and monitoring of code snippets.

Example prompts

  • "Generate a Python snippet to calculate the sum of squares from 1 to 100 using Ray."
  • "Write a short Ray program to train a simple linear regression model on this data."
  • "Create a Python script that runs a simulation with 10,000 agents distributed across my Ray cluster."

Tips & gotchas

  • Requires a running Ray cluster. The agent needs access to a properly configured Ray environment to execute the generated code snippets.
  • The skill is best suited for relatively short and self-contained code snippets due to resource management limitations.