A standardized way to give AI agents new capabilities and expertise.
Agent Skills are 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. This file includes metadata (name and description, at minimum) and instructions that tell an agent how to perform a specific task. Skills can also bundle scripts, reference materials, templates, and other resources.
my-skill/
├── SKILL.md # Required: metadata + instructions
├── scripts/ # Optional: executable code
├── references/ # Optional: documentation
├── assets/ # Optional: templates, resources
└── ... # Any additional files or directories
Agents are increasingly capable, but often don't have the context they need to do real work reliably. Skills solve this by packaging procedural knowledge and company-, team-, and user-specific context into portable, version-controlled folders that agents load on demand. This gives agents:
- Domain expertise: Capture specialized knowledge — from legal review processes to data analysis pipelines to presentation formatting — as reusable instructions and resources.
- Repeatable workflows: Turn multi-step tasks into consistent, auditable procedures.
- Cross-product reuse: Build a skill once and use it across any skills-compatible agent.
Agents load skills through progressive disclosure, in three stages:
-
Discovery: At startup, agents load only the name and description of each available skill, just enough to know when it might be relevant.
-
Activation: When a task matches a skill's description, the agent reads the full
SKILL.mdinstructions into context. -
Execution: The agent follows the instructions, optionally executing bundled code or loading referenced files as needed.
Full instructions load only when a task calls for them, so agents can keep many skills on hand with only a small context footprint.