Skills vs Agents: What's the Difference? ðŸ§
Both skills and agents extend AI capabilities, but they work in fundamentally different ways. Understanding the distinction helps you choose the right approach for your use case.
About Agent Skills
Agent Skills is an open standard that works across multiple AI platforms including Claude, OpenAI Codex, GitHub Copilot, and VS Code. The same skill file works everywhere. See all supported platforms.
Quick Comparison
| Aspect | Skills | Agents |
|---|---|---|
| What they are | Instructions & knowledge | Autonomous systems |
| Execution | Within conversation | Independent processes |
| Tool access | Uses the agent's built-in tools | Custom APIs & integrations |
| Setup | Copy & paste | Code & infrastructure |
| Best for | Improving outputs | Automating workflows |
Skills: Enhanced Conversation
Skills enhance what AI agents (like Claude, Codex, or Copilot) can do within a conversation. They're essentially detailed instructions that help the agent:
- Produce more accurate outputs for specific tasks
- Follow consistent formats and best practices
- Apply domain expertise to your requests
- Handle edge cases appropriately
Skills are passive—they inform the agent's responses but don't take autonomous action. You're still in control of the conversation.
Example: The "Excel Spreadsheet Creator" skill teaches the agent best practices for creating spreadsheets with proper formulas, formatting, and structure. You still ask the agent to create the spreadsheet—the skill just ensures it's done well.
Agents: Autonomous Action
Agents are autonomous systems that can take actions independently. They typically:
- Run as separate programs or services
- Make decisions and execute tasks without human intervention
- Integrate with external APIs and tools
- Maintain state across multiple interactions
Agents require more setup (code, infrastructure, API keys) but can automate entire workflows end-to-end.
Example: An email agent might monitor your inbox, categorize messages, draft responses, and send them—all without you being involved in each step.
When to Use Each
Use Skills When...
- You want better results from conversations with your AI
- You need consistent outputs for repeated tasks
- You want to leverage domain expertise without coding
- You're working interactively and want guidance
Use Agents When...
- You need fully automated workflows
- Tasks should run without human oversight
- You require integration with external systems
- You're building production applications
Can They Work Together?
Absolutely! Many developers use skills within their agents. An autonomous agent might use an LLM (like Claude, GPT-4, or other models) with specific skills loaded to ensure high-quality outputs for certain tasks.
Skills make agents smarter by providing domain expertise and best practices. Agents make skills actionable by executing workflows autonomously. Together, they create powerful, reliable automation.
Start with Skills
If you're new to extending AI capabilities, start with skills. They're easier to set up, work across platforms, and deliver immediate value. You can always build agents later when automation needs arise.