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Llm Inference

Checked
eyadsibai·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 eyadsibai/ltk --skill llm-inference -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

eyadsibai

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 eyadsibai/ltk at f8e85697b9.

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

Commit
f8e85697b9
Manifest
plugins/ltk-data/skills/llm-inference/SKILL.md
Scanned
1 file, 141 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

This skill provides essential guidance and assistance specifically for building artificial intelligence and machine learning applications. It helps developers navigate the complexities of integrating Large Language Models into their projects through targeted support and best practices.

When to use it

  • You are architecting a new AI application and need strategic advice on model selection.
  • Your development team requires assistance troubleshooting integration issues with LLMs.
  • You want to ensure your machine learning workflow aligns with current industry standards.
  • You need guidance on optimizing performance for specific AI use cases.

Key capabilities

  • Delivers targeted guidance for constructing AI and ML systems.
  • Offers assistance tailored to the full lifecycle of application development.
  • Supports developers in leveraging Large Language Models effectively.

Example prompts

  • "What are the best practices for integrating an LLM into a customer support chatbot?"
  • "How can I optimize inference costs while maintaining high accuracy for my NLP model?"
  • "I need guidance on selecting the right architecture for a real-time translation app using AI."

Tips & gotchas

Ensure you have a clear understanding of your specific application requirements before seeking guidance, as the advice will be tailored to those constraints. While this skill offers broad assistance, complex mathematical derivations or proprietary model weights may require additional specialized resources beyond general inference guidance.