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Module1 Llm Basics

Checked
olorolor·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 olorolor/fundamentals-with-ai --skill module1-llm-basics -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

olorolor

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 olorolor/fundamentals-with-ai at 039e6d4b68.

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

Commit
039e6d4b68
Manifest
.claude/skills/module1-llm-basics/SKILL.md
Scanned
1 file, 105 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 foundational knowledge for interacting with Large Language Models (LLMs). It covers basic prompting techniques and understanding how to structure requests to elicit desired responses. The skill aims to improve the quality and relevance of LLM outputs by guiding users in crafting effective prompts.

When to use it

  • New AI agent users: To learn the fundamentals of interacting with LLMs before tackling more complex tasks.
  • Improving prompt effectiveness: When current prompts are yielding unsatisfactory or irrelevant results.
  • Understanding LLM limitations: To gain a basic understanding of what LLMs can and cannot do effectively.
  • Troubleshooting AI agent behavior: When an AI agent is producing unexpected or incorrect outputs, this skill can help identify issues with prompting.

Key capabilities

  • Basic Prompting Techniques
  • Understanding LLM Response Structure
  • Guidance on Request Formulation
  • Improving Output Relevance

Example prompts

  • "Explain the basics of prompt engineering for large language models."
  • "Give me examples of how to structure a request to an AI agent."
  • "What are some common pitfalls when prompting LLMs?"

Tips & gotchas

This skill assumes no prior experience with LLMs. While it provides a foundation, more advanced techniques and specific model nuances will require further exploration.