What is Skill?
A skill is a modular, reusable capability that extends an AI agent's functionality, enabling it to perform specific tasks or access specialized knowledge through defined interfaces and prompts.
Quick Facts
| Full Name | AI Agent Skill |
|---|---|
| Created | Concept evolved with AI agents, formalized around 2023-2024 |
| Specification | Official Specification |
How It Works
Skills are fundamental building blocks in AI agent systems that encapsulate specific capabilities. In the context of AI coding assistants and agent frameworks, a skill typically consists of a prompt template, instructions, and optionally tool definitions that guide the agent's behavior for particular tasks. Skills enable separation of concerns, allowing complex agent behaviors to be composed from simpler, well-tested components. The Model Context Protocol (MCP) and similar frameworks use skills to extend agent capabilities without modifying core functionality. Skills can range from simple prompt templates to complex multi-step workflows with tool integrations.
Key Characteristics
- Modular and reusable across different contexts
- Encapsulates specific domain knowledge or task expertise
- Defined through prompts, instructions, and tool configurations
- Can be composed to create complex agent behaviors
- Enables separation of concerns in agent architecture
- Supports versioning and iterative improvement
Common Use Cases
- Code generation skills for specific frameworks or languages
- Documentation writing and formatting skills
- Data analysis and visualization workflows
- Domain-specific task automation (e.g., SEO, testing)
- Integration skills for external APIs and services
Example
Loading code...Frequently Asked Questions
What is the difference between a skill and a prompt?
A prompt is a single instruction or query to an AI model. A skill is a more comprehensive package that may include multiple prompts, instructions, tool configurations, and contextual knowledge. Skills are reusable modules that define how an agent should behave for specific tasks, while prompts are individual inputs within that behavior.
How do skills relate to the Model Context Protocol (MCP)?
MCP provides a standardized way to extend AI assistants with external capabilities. Skills in MCP-compatible systems define specific functionalities that agents can invoke. MCP handles the communication protocol, while skills define what capabilities are available and how they should be used.
How do I create a custom skill for an AI agent?
Creating a skill typically involves: 1) Defining the skill's purpose and scope, 2) Writing clear instructions and prompt templates, 3) Specifying any required tools or APIs, 4) Testing the skill with various inputs, 5) Iterating based on results. Most agent frameworks use markdown or JSON files to define skills.
Can skills be shared between different AI agents?
Yes, well-designed skills are portable across compatible agent systems. Skills that follow standard formats (like MCP) can be shared and reused. However, skills may need adaptation for different agents due to varying capabilities, tool access, or context window limitations.
What makes a good AI agent skill?
Good skills are: focused on a specific task or domain, clearly documented with examples, modular and composable with other skills, tested across edge cases, versioned for tracking changes, and designed with appropriate guardrails. They should enhance agent capabilities without introducing unpredictable behavior.