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.
