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Implementation

Checked
matteocervelli·vlatest·backend·MIT

This skill executes your instructions as code, streamlining automation and rapidly prototyping solutions for efficient task completion.

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 matteocervelli/llms --skill implementation -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

matteocervelli

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 matteocervelli/llms at 1e1f2089eb.

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

Commit
1e1f2089eb
Manifest
.codex/skills/implementation/SKILL.md
Scanned
6 files, 3,076 lines
Copies in repo
3 — all of them scanned
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, "implementation," provides a way to execute code snippets within an AI agent's workflow. It allows agents to perform calculations, interact with external APIs via code, and generally extend their capabilities beyond simple text generation. The skill handles the execution of Python code, providing results back to the main conversation flow.

When to use it

  • Complex Calculations: When a task requires numerical processing or data manipulation that's difficult to express in natural language.
  • API Interactions: To automate tasks requiring interaction with external services through API calls (e.g., fetching weather data, sending emails).
  • Dynamic Content Generation: When the agent needs to generate content based on real-time data or complex logic.
  • Data Transformation: To reshape and prepare data for further analysis or use within the agent's responses.

Key capabilities

  • Executes Python code snippets.
  • Returns results of code execution to the main conversation flow.
  • Supports interaction with external APIs through code.

Example prompts

  • "Calculate 123 * 456 and tell me the result."
  • "Write a python script to fetch today's weather in London and summarize it."
  • “Can you write a Python function that converts Celsius to Fahrenheit, then use it to convert 25 degrees Celsius?”

Tips & gotchas

The agent will execute any provided code. Be mindful of potential security risks when allowing the execution of arbitrary code; ensure trusted sources are used and validate inputs carefully.