
Explore why skills matter for LLMs and what agent skills bring to the table. Understand the context problem, why it exists, and how skills address it for effective use.
Understand the context window of a large language model as its working memory—the finite amount of content it can process, including input and output.
Explore markdown, a lightweight markup language that marks up plain text to convey meaning for llms. Learn to use headers, bold, italics, and lists to structure content and provide context.
Learn how YAML front matter provides metadata for agent skills, guiding the LLM to activate PPTX skills for reading and editing presentations.
Learn how agent skills use scripts to enable the LLM to run executable code via an external agent, emphasizing self-contained scripts, clear dependencies, robust error handling, and security considerations.
See an open-source PowerPoint PPTX skill augmented inside an agent to create animated slides with morph transitions, using Python scripts to edit and read PowerPoint files.
Learn how skills work, decide which skills to create, and author them effectively to extend your AI agent's capabilities, with practical examples.
Understand domain expertise as a skill aligned to a business or technical domain, and see branding and widget skills improve LLM code readability and domain-driven prompts.
Design repeatable workflows with agent skills using structured stages, clear triggers, and iterative refinement to guide large language models reliably, illustrated by co-authoring documentation patterns.
Explore a growing repository of pre-existing skills, learn to use open-source skills from skills.sh and GitHub, and share trusted skills with your team.
NEW COURSE! AI coding agents like Claude Code, GitHub Copilot, Cursor, and Codex are powerful, but they don't know your workflows, your standards, or your domain expertise.
You've probably experienced the frustration: the agent "forgets" your instructions mid-session, produces inconsistent outputs, or requires you to repeat the same context every single time.
This isn't a prompting problem. It's a context problem.
And there's now an official standard that solves it.
What Are AI Agent Skills?
Agent Skills is a new open standard, maintained by Anthropic and adopted by Claude Code, GitHub Copilot, Cursor, OpenAI Codex, and others, that lets you extend any compatible AI agent with portable, reusable capabilities.
Instead of stuffing everything into a bloated system prompt and hoping the agent pays attention, Skills use progressive disclosure: the agent loads only what it needs, when it needs it.
The result? Leaner context, more consistent outputs, and expertise that travels with you across tools.
Write a skill once. Use it everywhere.
What You'll Learn
The Context Problem
Why AI agents struggle with long conversations, what "context rot" actually is, and why bigger context windows don't solve the problem.
How Skills Work
How do AI Agents use Agent Skills under-the-hood? The progressive disclosure pattern: discovery, metadata loading, task matching, activation, and execution. You'll understand why skills are architected this way, not just how to use them.
Skill Anatomy
SKILL file and folder structure, YAML frontmatter, instructions, scripts, references, and assets. What goes where and why.
Skill Authoring
How to write skills that actually work: good metadata for discoverability, clear instructions, token budget awareness, and designing for portability across agents.
Final Project
You'll create a production-ready skill for your own workflow, something you can actually use the day you finish this course.
How This Course Teaches
If you've taken my other courses, you know the approach: Don't Imitate, Understand.
This isn't a tutorial where you copy what I type and hope it works. We'll go under the hood. You'll learn why context windows create problems for agents, why progressive disclosure solves them, why the skill specification is designed the way it is, and how AI Agents use Skills under-the-hood.
When you understand the mechanics, you can adapt. You can debug. You can build skills the documentation doesn't cover.
Who This Is For
Developers using Claude Code, GitHub Copilot, Cursor, or Codex who want consistent, repeatable results.
Team leads who want to encode standards and workflows that agents follow automatically.
Anyone tired of repeating the same instructions every session.
Prerequisites: Basic familiarity with AI coding agents. No specific programming language required. Skills are language-agnostic.
Why Now?
Agent Skills is new. The specification was open-sourced in late 2025 by Anthropic, and adoption is accelerating fast. OpenAI, Google, and Microsoft have all added support.
The developers who understand this standard early will be the ones building the skills everyone else uses.
This is a short course. You can finish it in an afternoon and have a working skill by dinner.