Agent Skills tutorial

Teach AI coding agents your team's repeatable workflows with skills, then build, test and share a DevKit of everyday developer skills.

Course contents

Agent Skills Overview — What agent skills are and why developers use them: repeated prompts and lost context, the skill folder and SKILL.md, prompt vs skill, benefits and limits, and the coding tools that support skills.
Skill Anatomy — The parts of a skill: the folder layout, the SKILL.md file, YAML front matter fields, the body sections that make a skill dependable, the optional references, scripts, templates and examples folders, and building your first hello-skill.

Loading and Context Cost — How agents load skills in three levels (catalog, one SKILL.md body, extra files on demand), and how to keep each level small: short descriptions, a minimum reliable workflow, and pointers to files.
Activation and Descriptions — How agents find installed skills and pick one for a request: matching descriptions, writing what/when/when-not descriptions in users' words, fixing overlapping skills, calling skills by name and manual-only skills.

Skill Installation — Where to put a skill so your tool finds it: project and personal folders, one shared folder for the team, the three install checks, and how to confirm a skill loaded.
Release Note Skill — Choose a good first task, answer the five design questions, and build release-note-helper: grouping rules, fixed headings, style guide, check script, an AI-drafted version you review, and a with and without test.

Workflow Instructions — Turn a vague skill body into a clear workflow: inputs, numbered steps with one action each, decision points, stop conditions and final checks.
Output Format and Examples — Defining the exact shape of a skill's reply: fixed headings, field formats, allowed values, None for empty sections, JSON for programs, one good example line, and templates with blanks to fill.

Reference Files — What to move into a skill's references folder, how to split big guides into topic files, and how to write clear pointers that open each file only when a task needs it.
Scripts and Validators — Which rules need a script instead of the model, how the agent runs a validator and fixes its reply, real validators across the stack, short OK/FAIL output, and telling the agent when to run each script.

Choosing the Right Owner — Choosing who owns each rule and task: prompts, AGENTS.md, skills, scripts and MCP tools. Five questions to find the owner, the cost of always-on text, one owner per rule, and plugins that share skills and tools.

Diagnosing Skills — Find why a skill does not work: the six layers every request passes through, how to find the first broken one, skills that fire for the wrong request, and changing one thing at a time.
Skill Evaluation — Testing skills at five levels: structure, activation, output, behavior and human review, with control cases, baselines and regression checks.
Skill Security — Checking skills before you use them: red flags in instructions and scripts, reading the raw file, inputs as data, keeping secrets out, and reviewing every update.

Maintaining and Sharing Skills — Keeping shared skills healthy: owners and versions, patch/minor/major changes, changelogs, turning feedback into one fix, retiring old skills safely, and one reviewed team library.
Everyday Skill Patterns — Five everyday skill patterns (Reviewer, Generator, Transformer, Triage and Tool-backed), how to spot them in your DevKit, and how to build a new skill by copying a pattern.
Agent Skills Reference — A one-page look-up for agent skills: the course at a glance, a SKILL.md template, front matter, body sections, what loads when, skill folders per tool, who owns a job, patterns, checklists, troubleshooting, testing and a glossary.