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Update Llms

Official
github·vlatest·ai-ml·MIT

This skill updates Large Language Models (LLMs) with new data, ensuring your AI stays current and performs optimally.

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 github/awesome-copilot --skill update-llms -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

github

Matched to the vendor's own GitHub organisation.

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • Declares what it does: failed

    No SKILL.md was found in the skill's directory.

    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 github/awesome-copilot at 6c4d33b9cf.

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

Scanned
0 files
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 update-llms skill automates the process of updating large language models (LLMs) by fetching and applying the latest model versions from a specified source. It ensures that AI agents are always using the most recent and optimized LLMs, improving performance and accuracy over time.

When to use it

  • When deploying an AI agent in production and needing regular updates for improved functionality.
  • When integrating with external model repositories or version control systems like GitHub.
  • When maintaining a pipeline that requires consistent access to the latest LLM versions.
  • When troubleshooting issues related to outdated models affecting performance.

Key capabilities

  • Automatic fetching of updated LLMs from remote sources.
  • Integration with version control and package management tools.
  • Seamless deployment of new model versions without manual intervention.

Example prompts

  • "Update the large language model to the latest version available on GitHub."
  • "Fetch and apply the most recent changes to the AI agent's LLM."
  • "Check for updates in the model repository and install them if available."

Tips & gotchas

  • Ensure that your environment has internet access to fetch remote updates.
  • Verify compatibility between new model versions and existing systems before deployment.