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Ai Llm Engineering

Checked
microck·vlatest·ai-ml

Helps with AI, LLMs as part of building AI and machine learning applications workflows.

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 microck/ordinary-claude-skills --skill ai-llm-engineering -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

microck

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: github.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

    github.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 microck/ordinary-claude-skills at 1056d293d4.

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

Commit
1056d293d4
Manifest
skills_all/ai-llm-engineering/SKILL.md
Scanned
4 files, 514 lines
Copies in repo
2 — 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 allows you to engineer Large Language Models (LLMs) through prompt optimization and iterative refinement. It facilitates the creation of more effective prompts, enabling agents to produce higher quality outputs and achieve desired outcomes. The skill focuses on improving agent performance by systematically adjusting prompting strategies.

When to use it

  • Improving Agent Accuracy: When an AI agent consistently provides inaccurate or irrelevant responses.
  • Refining Task Completion: To enhance the agent's ability to successfully complete complex tasks, such as writing code or summarizing documents.
  • Optimizing Output Style: When you need the agent to adopt a specific tone, format, or style in its generated content.
  • Debugging Agent Behavior: When an agent exhibits unexpected or undesirable behavior and needs targeted adjustments.

Key capabilities

  • Prompt Optimization
  • Iterative Refinement
  • Performance Improvement
  • Output Quality Enhancement

Example prompts

  • "Optimize this prompt for generating a marketing email: 'Write an email about our new product.'"
  • "Refine the following prompt to improve its clarity and reduce ambiguity: 'Summarize this article.'"
  • "Can you help me debug why my agent isn't following these instructions?"

Tips & gotchas

This skill requires a clear understanding of the underlying task and desired outcomes. It’s most effective when used in conjunction with careful observation and analysis of the AI agent's responses.