Agent Skills: A Standardized Way to Give AI Agents New Capabilities

Introduction

Agent Skills is an open standard that defines a standardized way to give AI agents new capabilities and expertise. It offers a lightweight, open format for extending AI agent capabilities with specialized knowledge and workflows. At its core, a skill is a folder containing a SKILL.md file, which includes metadata and instructions for an agent to perform a specific task, optionally bundling scripts, reference materials, and templates.

How Agent Skills Work

Agent Skills are not 'installed' in the traditional sense, but rather integrated into AI agent clients. Agents load skills through progressive disclosure, in three stages:

• Discovery: Agents load only the name and description of available skills.
• Activation: When a task matches a skill's description, the agent reads the full SKILL.md instructions.
• Execution: The agent follows instructions, potentially executing bundled code or loading referenced files.

This approach ensures agents can manage many skills with a small context footprint. To get started, refer to the official documentation and client showcase.

Examples

A skill is structured as a folder, typically containing a SKILL.md file along with optional scripts/, references/, and assets/ directories. For practical examples and inspiration, you can explore the Example Skills repository to see how various capabilities are defined.

my-skill/
??? SKILL.md          # Required: metadata + instructions
??? scripts/          # Optional: executable code
??? references/       # Optional: documentation
??? assets/           # Optional: templates, resources
??? ...               # Any additional files or directories

Why Use Agent Skills?

Agent Skills address the challenge of providing AI agents with the necessary context to perform real work reliably. By packaging procedural knowledge and specific context into portable, version-controlled folders, agents gain:

• Domain expertise: Capture specialized knowledge, from legal review to data analysis, as reusable instructions.
• Repeatable workflows: Transform multi-step tasks into consistent, auditable procedures.
• Cross-product reuse: Build a skill once and utilize it across any skills-compatible agent.

Links

For more detailed information and to get involved, please visit the official resources:

• Documentation
• Specification
• Example Skills
• Discord
• Client Showcase
• GitHub Repository