Production Agent Skills Engineering

Production Agent Skills Engineering

Agent Skills Mastery taught you to say “I know how to create and use SKILL.md.” This course exists for the much harder claim on the other side of it: “I can design skills used by thousands of agents.”

Those are genuinely different disciplines. A skill on your laptop only has to work for you, once you’ve tested it a few times, in an environment you fully control. A skill running across an organization has to keep working when a hundred different people use it in ways you didn’t anticipate, when the underlying model changes, when someone malicious tries to abuse it, and when six months have passed and nobody remembers exactly why it was written the way it was. Recent research studying public SKILL.md files found that over 99% contain at least one quality issue — a “skill smell.” That number isn’t a syntax problem. Nearly everyone who’s picked up the format already knows how to write valid YAML frontmatter. What’s missing is engineering discipline around the parts that don’t show up in the spec: how a skill fails, how it’s tested, how it’s secured, how it’s versioned, how it’s found.

This course is that discipline, organized into thirteen lessons.

What You’ll Build

• A design-pattern catalog applied to real skills — six named patterns, each with a working example you build yourself
• A structured evaluation workspace — with/without-skill comparisons, graded assertions, and benchmarks across cost, latency, and reliability
• A real CI/CD pipeline for a skill — lint, test, evaluate, security-scan, and deploy, as an actual GitHub Actions workflow
• An enterprise skill pack — the capstone, built using every practice in this course, alongside a worked case study on Smart SDLC, a real production skill framework already giving Copilot, Claude, and Cursor structured software-development-lifecycle expertise

How This Course Is Organized

The first five lessons build a vocabulary and a mental model: what patterns skills recur in, what separates a good skill from a bad one, how a skill’s failure modes are engineered rather than left to chance, and precisely where a skill sits in a full agent architecture. The next two take that model past a single skill — composing several into one agent, and distributing skill sets across a multi-agent system. The back half is where “production” stops being an adjective and starts being a checklist: testing and evaluation at scale, security and governance, lifecycle and versioning, CI/CD, and registries. The capstone puts all of it into one real deliverable.

Prerequisites, Honestly

This course assumes you can already write and test a working SKILL.md — if you can’t yet, Agent Skills Mastery is free and covers exactly that in about four weeks. It also assumes some existing engineering background: CI/CD, backend API design, or production ML/LLM systems. This isn’t a second beginner course wearing an advanced title — it moves fast, and it’s meant to.