Agent skills have seen rapid adoption. Learn what they are, how they work in AI agents, and how they differ from protocols like MCP.

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Agent skills are structured packages of instructions, metadata, and optional scripts that give AI agents expanded abilities and domain knowledge. Popularized by Anthropic for Claude in late 2025, they use YAML front matter and Markdown to describe how an agent should perform a specific task. Unlike agentic protocols such as MCP, A2A, or ANP — which define how agents communicate and access resources — agent skills bundle executable knowledge and task-specific logic together. They improve governance, reusability, and discoverability, but come with tradeoffs: security risks from local shell execution, high token usage for complex skills, and limitations in multi-agent coordination scenarios. For heavy or multi-agent tasks, combining agent skills with MCP or A2A is recommended.

What Are Agent Skills?