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Skills

Skills are like professional certifications for AI agents. A general-purpose agent knows a little about everything, but an agent equipped with Skills has deep, structured knowledge in a specific domain — code patterns, testing strategies, documentation standards. Just as a certified electrician follows specific codes and practices that a general laborer might not know, a Skill-equipped agent follows domain-specific rules and patterns that produce work that is consistently high-quality and team-aligned. Skills turn generic agents into domain experts.

Prerequisites​

Before reading this page, make sure you're familiar with:

  • Agents — the autonomous AI systems that load and use Skills
  • Agentic Workflows — multi-step patterns where Skills provide domain expertise
  • MCP — the protocol layer that Skills can complement for tool access

How It Works​

As the diagram shows, a skill is a self-contained directory with a standardized layout that plugs into an agent as a module.

Each skill has three components:

  • SKILL.md — the index file that describes what the skill does, when to use it, and what capabilities it provides. This is the entry point an agent reads first to decide whether the skill is relevant.
  • Rules — markdown files containing domain-specific guidelines, constraints, and best practices. These are the "do this, don't do that" instructions the agent follows: coding standards, naming conventions, security requirements, architectural patterns.
  • Patterns — reusable templates, code snippets, and structural examples the agent can apply directly. Instead of generating code from scratch, the agent adapts proven patterns to the current task.

When an agent loads a skill, it reads the SKILL.md index, internalizes the rules, and applies the patterns to its work. The result is output that consistently adheres to the skill's domain standards — not because the agent was prompted with detailed instructions every time, but because the knowledge is packaged in a reusable module.

Skills are modular and shareable. A team creates a skill once — encoding their coding standards, architecture decisions, and testing patterns — and every agent in the organization benefits. New team members (human or AI) get the same institutional knowledge from day one.

Why It Matters​

Without Skills, you'd repeat the same instructions in every prompt. "Use TypeScript interfaces for props." "Follow our naming convention." "Always add error handling." These instructions get lost, forgotten, or applied inconsistently.

Skills solve this by encoding institutional knowledge in a structured, versioned format. They are the mechanism that turns "AI that writes code" into "AI that writes code the way your team writes code." The agent doesn't just know how to write a Vue component — it knows how your team writes Vue components: with <script setup>, with typed props, with your specific patterns.

In practice, Skills are often shared through catalogs and can be installed with a single command. Teams publish Skills for their domain, others adopt and adapt them, and the collective knowledge grows. This is how AI-assisted development scales beyond individual prompts into organizational capability.