A Detailed Explanation of Agent Skills: FAQ

AI agents don't know context like a team's processes or quality standards, requiring repetitive prompt input to get accurate responses. Agent skills are an open standard that packages instructions, scripts, and resources so agents can automatically discover and use them.

Skills go beyond simple functions to provide complete workflows, including when to use which tool for a specific task, what the order of operations should be, and what the success criteria are. This is best suited for complex, repetitive, domain-specific multi-step processes.

The differences between agent components are as follows:

• Agent skills: Packaging complete workflows with context and guardrails
• MCP servers: Providing standardized interfaces to external tools and services (APIs, databases, etc.)
• Tools: Performing individual single functions such as API calls, web search, etc.
• Rules: Defining behavioral constraints such as security policies and data handling standards
• System prompts: Setting an agent's basic personality and foundational behavior

Using skills can solve problems such as prompt drift, where prompts lose consistency, loss of workflow conventions, and instruction sprawl, where prompts become bloated and obscure core context.